Andreas Krause

Orcid: 0000-0001-7260-9673

Affiliations:
  • ETH Zurich, Switzerland
  • California Institute of Technology, Pasadena, CA, USA
  • Carnegie Mellon University, Pittsburgh, PA, USA
  • Technical University of Munich, Germany


According to our database1, Andreas Krause authored at least 398 papers between 2003 and 2025.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
SafeRPlan: Safe deep reinforcement learning for intraoperative planning of pedicle screw placement.
Medical Image Anal., 2025

2024
Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning.
IEEE Robotics Autom. Lett., 2024

Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning.
J. Mach. Learn. Res., 2024

Data Summarization via Bilevel Optimization.
J. Mach. Learn. Res., 2024

3DReact: Geometric Deep Learning for Chemical Reactions.
J. Chem. Inf. Model., 2024

All models are wrong, some are useful: Model Selection with Limited Labels.
CoRR, 2024

ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning.
CoRR, 2024

Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs.
CoRR, 2024

Amortized SHAP values via sparse Fourier function approximation.
CoRR, 2024

Active Fine-Tuning of Generalist Policies.
CoRR, 2024

Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design.
CoRR, 2024

Towards safe and tractable Gaussian process-based MPC: Efficient sampling within a sequential quadratic programming framework.
CoRR, 2024

Directed Exploration in Reinforcement Learning from Linear Temporal Logic.
CoRR, 2024

Bandits with Preference Feedback: A Stackelberg Game Perspective.
CoRR, 2024

Standardizing Structural Causal Models.
CoRR, 2024

Breeding Programs Optimization with Reinforcement Learning.
CoRR, 2024

Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes.
CoRR, 2024

NeoRL: Efficient Exploration for Nonepisodic RL.
CoRR, 2024

When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL.
CoRR, 2024

Safe Exploration Using Bayesian World Models and Log-Barrier Optimization.
CoRR, 2024

Bridging the Sim-to-Real Gap with Bayesian Inference.
CoRR, 2024

Information-based Transductive Active Learning.
CoRR, 2024

Active Few-Shot Fine-Tuning.
CoRR, 2024

Transition Constrained Bayesian Optimization via Markov Decision Processes.
CoRR, 2024

Safe Guaranteed Exploration for Non-linear Systems.
CoRR, 2024

Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adversarial Causal Bayesian Optimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Submodular Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Provably Learning Nash Policies in Constrained Markov Potential Games.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Intrinsic Gaussian Vector Fields on Manifolds.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Distributionally Robust Model-based Reinforcement Learning with Large State Spaces.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Causal Modeling with Stationary Diffusions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Learning Safety Constraints from Demonstrations with Unknown Rewards.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Safe Risk-Averse Bayesian Optimization for Controller Tuning.
IEEE Robotics Autom. Lett., December, 2023

ChromaX: a fast and scalable breeding program simulator.
Bioinform., December, 2023

Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics.
Mach. Learn., October, 2023

GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems.
Artif. Intell., July, 2023

Incentive-Compatible Forecasting Competitions.
Manag. Sci., March, 2023

Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning.
Trans. Mach. Learn. Res., 2023

Leveraging Demonstrations with Latent Space Priors.
Trans. Mach. Learn. Res., 2023

Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice.
J. Mach. Learn. Res., 2023

Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications.
J. Mach. Learn. Res., 2023

Instance-Dependent Generalization Bounds via Optimal Transport.
J. Mach. Learn. Res., 2023

EquiReact: An equivariant neural network for chemical reactions.
CoRR, 2023

Sinkhorn Flow: A Continuous-Time Framework for Understanding and Generalizing the Sinkhorn Algorithm.
CoRR, 2023

Implicit Manifold Gaussian Process Regression.
CoRR, 2023

DockGame: Cooperative Games for Multimeric Rigid Protein Docking.
CoRR, 2023

Model-based Causal Bayesian Optimization.
CoRR, 2023

Unbalanced Diffusion Schrödinger Bridge.
CoRR, 2023

Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement.
CoRR, 2023

Aligned Diffusion Schrödinger Bridges.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Lifelong bandit optimization: no prior and no regret.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Hallucinated adversarial control for conservative offline policy evaluation.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Efficient Exploration in Continuous-time Model-based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimistic Active Exploration of Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning To Dive In Branch And Bound.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Anytime Model Selection in Linear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stochastic Approximation Algorithms for Systems of Interacting Particles.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Dynamical System View of Langevin-Based Non-Convex Sampling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contextual Stochastic Bilevel Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Riemannian stochastic optimization methods avoid strict saddle points.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Implicit Manifold Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Likelihood Ratio Confidence Sets for Sequential Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Gradient-Based Trajectory Optimization With Learned Dynamics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Model-based Causal Bayesian Optimization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MARS: Meta-learning as Score Matching in the Function Space.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Near-optimal Policy Identification in Active Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Replicable Bandits.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tuning Legged Locomotion Controllers via Safe Bayesian Optimization.
Proceedings of the Conference on Robot Learning, 2023

Active Exploration via Experiment Design in Markov Chains.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

BaCaDI: Bayesian Causal Discovery with Unknown Interventions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

The Schrödinger Bridge between Gaussian Measures has a Closed Form.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Isotropic Gaussian Processes on Finite Spaces of Graphs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Model-based Causal Bayesian Optimization.
CoRR, 2022

PAC-Bayesian Meta-Learning: From Theory to Practice.
CoRR, 2022

Reproducible Bandits.
CoRR, 2022

Invariant Causal Mechanisms through Distribution Matching.
CoRR, 2022

Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization.
CoRR, 2022

Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges.
CoRR, 2022

Scalable Safe Exploration for Global Optimization of Dynamical Systems.
CoRR, 2022

Learning Long-Term Crop Management Strategies with CyclesGym.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Bayesian Causal Inference.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Movement Penalized Bayesian Optimization with Application to Wind Energy Systems.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Near-Optimal Multi-Agent Learning for Safe Coverage Control.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Amortized Inference for Causal Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Exploration for Inverse Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph Neural Network Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supervised Training of Conditional Monge Maps.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation.
Proceedings of the International Conference on Machine Learning, 2022

Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning.
Proceedings of the International Conference on Machine Learning, 2022

Interactively Learning Preference Constraints in Linear Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Meta-Learning Hypothesis Spaces for Sequential Decision-making.
Proceedings of the International Conference on Machine Learning, 2022

Adaptive Gaussian Process Change Point Detection.
Proceedings of the International Conference on Machine Learning, 2022

Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Constrained Policy Optimization via Bayesian World Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning Priors for Safe Bayesian Optimization.
Proceedings of the Conference on Robot Learning, 2022

The Dynamics of Riemannian Robbins-Monro Algorithms.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Safe Reinforcement Learning via Confidence-Based Filters.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Automatic Termination for Hyperparameter Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2022

Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Sensing Cox Processes via Posterior Sampling and Positive Bases.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Neural Contextual Bandits without Regret.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Proximal Optimal Transport Modeling of Population Dynamics.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
JKOnet: Proximal Optimal Transport Modeling of Population Dynamics.
CoRR, 2021

Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations.
CoRR, 2021

Bias-Robust Bayesian Optimization via Dueling Bandit.
CoRR, 2021

Overfitting in Bayesian Optimization: an empirical study and early-stopping solution.
CoRR, 2021

Regret Bounds for Gaussian-Process Optimization in Large Domains.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust Generalization despite Distribution Shift via Minimum Discriminating Information.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multi-Scale Representation Learning on Proteins.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Graph Models for Retrosynthesis Prediction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-Learning Reliable Priors in the Function Space.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Risk-averse Heteroscedastic Bayesian Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DiBS: Differentiable Bayesian Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Information Directed Reward Learning for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hierarchical Skills for Efficient Exploration.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Misspecified Gaussian Process Bandit Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Addressing the Long-term Impact of ML Decisions via Policy Regret.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Safe and Efficient Model-free Adaptive Control via Bayesian Optimization.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Fast Projection Onto Convex Smooth Constraints.
Proceedings of the 38th International Conference on Machine Learning, 2021

PopSkipJump: Decision-Based Attack for Probabilistic Classifiers.
Proceedings of the 38th International Conference on Machine Learning, 2021

Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems.
Proceedings of the 38th International Conference on Machine Learning, 2021

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees.
Proceedings of the 38th International Conference on Machine Learning, 2021

No-regret Algorithms for Capturing Events in Poisson Point Processes.
Proceedings of the 38th International Conference on Machine Learning, 2021

Bias-Robust Bayesian Optimization via Dueling Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Risk-Averse Offline Reinforcement Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator.
Proceedings of the 9th International Conference on Learning Representations, 2021

Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Semi-Supervised Batch Active Learning Via Bilevel Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2021

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback.
Proceedings of the Algorithmic Learning Theory, 2021

Online Active Model Selection for Pre-trained Classifiers.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Stochastic Linear Bandits Robust to Adversarial Attacks.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Logistic Q-Learning.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Multi-Player Bandits: The Adversarial Case.
J. Mach. Learn. Res., 2020

Continuous Submodular Function Maximization.
CoRR, 2020

Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory.
CoRR, 2020

Learning Graph Models for Template-Free Retrosynthesis.
CoRR, 2020

SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives.
CoRR, 2020

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees.
CoRR, 2020

Safe Reinforcement Learning via Curriculum Induction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Play Sequential Games versus Unknown Opponents.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Contextual Games: Multi-Agent Learning with Side Information.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Gradient Estimation with Stochastic Softmax Tricks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adaptive Sampling for Stochastic Risk-Averse Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Coresets via Bilevel Optimization for Continual Learning and Streaming.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Safe non-smooth black-box optimization with application to policy search.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Mixed-Variable Bayesian Optimization.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models.
Proceedings of the 37th International Conference on Machine Learning, 2020

Hierarchical Image Classification using Entailment Cone Embeddings.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Information Directed Sampling for Linear Partial Monitoring.
Proceedings of the Conference on Learning Theory, 2020

Mixed Strategies for Robust Optimization of Unknown Objectives.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Distributionally Robust Bayesian Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Corruption-Tolerant Gaussian Process Bandit Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Experimental Design for Optimization of Orthogonal Projection Pursuit Models.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
No-Regret Bayesian Optimization with Unknown Hyperparameters.
J. Mach. Learn. Res., 2019

Log Barriers for Safe Non-convex Black-box Optimization.
CoRR, 2019

A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness.
CoRR, 2019

Convergence Analysis of the Randomized Newton Method with Determinantal Sampling.
CoRR, 2019

Noise Regularization for Conditional Density Estimation.
CoRR, 2019

Structured Variational Inference in Unstable Gaussian Process State Space Models.
CoRR, 2019

Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning.
CoRR, 2019

Predicting program properties from 'big code'.
Commun. ACM, 2019

Safe Exploration for Interactive Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

No-Regret Learning in Unknown Games with Correlated Payoffs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adaptive Sequence Submodularity.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stochastic Bandits with Context Distributions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Teaching Multiple Concepts to a Forgetful Learner.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Domain Agnostic Measure for Monitoring and Evaluating GANs.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficiently Learning Fourier Sparse Set Functions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Mobile Robotic Painting of Texture.
Proceedings of the International Conference on Robotics and Automation, 2019

Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Generative Models across Incomparable Spaces.
Proceedings of the 36th International Conference on Machine Learning, 2019

Online Variance Reduction with Mixtures.
Proceedings of the 36th International Conference on Machine Learning, 2019

Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Information-Directed Exploration for Deep Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy.
Proceedings of the 17th European Control Conference, 2019

Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Safe Convex Learning under Uncertain Constraints.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Projection Free Online Learning over Smooth Sets.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Consistent Online Optimization: Convex and Submodular.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations.
IEEE Robotics Autom. Lett., 2018

Evaluating GANs via Duality.
CoRR, 2018

The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems.
CoRR, 2018

Unsupervised Imitation Learning.
CoRR, 2018

Teaching Multiple Concepts to Forgetful Learners.
CoRR, 2018

Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference.
CoRR, 2018

Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations.
CoRR, 2018

Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning.
CoRR, 2018

Generalization and Search in Risky Environments.
Cogn. Sci., 2018

Fake News Detection in Social Networks via Crowd Signals.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Discrete Sampling using Semigradient-based Product Mixtures.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Provable Variational Inference for Constrained Log-Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable k -Means Clustering via Lightweight Coresets.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Differentiable Submodular Maximization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Preventing Disparate Treatment in Sequential Decision Making.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

An Online Learning Approach to Generative Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Information Directed Sampling and Bandits with Heteroscedastic Noise.
Proceedings of the Conference On Learning Theory, 2018

Online Variance Reduction for Stochastic Optimization.
Proceedings of the Conference On Learning Theory, 2018

Learning-Based Model Predictive Control for Safe Exploration.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Submodularity on Hypergraphs: From Sets to Sequences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Learning to Interact With Learning Agents.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Learning User Preferences to Incentivize Exploration in the Sharing Economy.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Training Gaussian Mixture Models at Scale via Coresets.
J. Mach. Learn. Res., 2017

Machine Learning and Formal Method (Dagstuhl Seminar 17351).
Dagstuhl Reports, 2017

Detecting Fake News in Social Networks via Crowdsourcing.
CoRR, 2017

Learning Implicit Generative Models Using Differentiable Graph Tests.
CoRR, 2017

Learning to Use Learners' Advice.
CoRR, 2017

Coordinated Online Learning With Applications to Learning User Preferences.
CoRR, 2017

Uniform Deviation Bounds for Unbounded Loss Functions like k-Means.
CoRR, 2017

Scalable and Distributed Clustering via Lightweight Coresets.
CoRR, 2017

Improving Optimization-Based Approximate Inference by Clamping Variables.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Stochastic Submodular Maximization: The Case of Coverage Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Differentiable Learning of Submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Safe Model-based Reinforcement Learning with Stability Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interactive Submodular Bandit.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Probabilistic Submodular Maximization in Sub-Linear Time.
Proceedings of the 34th International Conference on Machine Learning, 2017

Differentially Private Submodular Maximization: Data Summarization in Disguise.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten".
Proceedings of the 34th International Conference on Machine Learning, 2017

Guarantees for Greedy Maximization of Non-submodular Functions with Applications.
Proceedings of the 34th International Conference on Machine Learning, 2017

Uniform Deviation Bounds for k-Means Clustering.
Proceedings of the 34th International Conference on Machine Learning, 2017

Distributed and Provably Good Seedings for k-Means in Constant Rounds.
Proceedings of the 34th International Conference on Machine Learning, 2017

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Proper Proxy Scoring Rules.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Selecting Sequences of Items via Submodular Maximization.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem.
J. Mach. Learn. Res., 2016

Distributed Submodular Maximization.
J. Mach. Learn. Res., 2016

Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions.
CoRR, 2016

Learning programs from noisy data.
Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2016

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variational Inference in Mixed Probabilistic Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Cooperative Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fast and Provably Good Seedings for k-Means.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Linear-Time Outlier Detection via Sensitivity.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Safe controller optimization for quadrotors with Gaussian processes.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Horizontally Scalable Submodular Maximization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Evaluating Task-Dependent Taxonomies for Navigation.
Proceedings of the Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016

Learning and Feature Selection under Budget Constraints in Crowdsourcing.
Proceedings of the Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016

Bayesian optimization for maximum power point tracking in photovoltaic power plants.
Proceedings of the 15th European Control Conference, 2016

Suggesting Sounds for Images from Video Collections.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Better safe than sorry: Risky function exploitation through safe optimization.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Safe learning of regions of attraction for uncertain, nonlinear systems with Gaussian processes.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Learning Sparse Additive Models with Interactions in High Dimensions.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Approximate K-Means++ in Sublinear Time.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation.
Int. J. Robotics Res., 2015

Distributed Submodular Cover: Succinctly Summarizing Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Sampling from Probabilistic Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Discovering Valuable items from Massive Data.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Building Hierarchies of Concepts via Crowdsourcing.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Information Gathering in Networks via Active Exploration.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Non-Monotone Adaptive Submodular Maximization.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Safe Exploration for Optimization with Gaussian Processes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Scalable Variational Inference in Log-supermodular Models.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Coresets for Nonparametric Estimation - the Case of DP-Means.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Higher-Order Inference for Multi-class Log-Supermodular Models.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Learning to Hire Teams.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Crowd Access Path Optimization: Diversity Matters.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Sequential Information Maximization: When is Greedy Near-optimal?
Proceedings of The 28th Conference on Learning Theory, 2015

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Incentivizing Users for Balancing Bike Sharing Systems.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Lazier Than Lazy Greedy.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Submodular Surrogates for Value of Information.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization.
J. Mach. Learn. Res., 2014

Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments.
CoRR, 2014

Community sense and response systems: your phone as quake detector.
Commun. ACM, 2014

Sequential Decision Making in Computational Sustainability via Adaptive Submodularity.
AI Mag., 2014

Explore-exploit in top-N recommender systems via Gaussian processes.
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

Community sense-and-response systems: Your phone as seismometer.
Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, 2014

Efficient Partial Monitoring with Prior Information.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Efficient Sampling for Learning Sparse Additive Models in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

From MAP to Marginals: Variational Inference in Bayesian Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Streaming submodular maximization: massive data summarization on the fly.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Fully autonomous focused exploration for robotic environmental monitoring.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Near-Optimally Teaching the Crowd to Classify.
Proceedings of the 31th International Conference on Machine Learning, 2014

Active Detection via Adaptive Submodularity.
Proceedings of the 31th International Conference on Machine Learning, 2014

Contextual Procurement in Online Crowdsourcing Markets.
Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing, 2014

Near Optimal Bayesian Active Learning for Decision Making.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Submodular Function Maximization.
Proceedings of the Tractability: Practical Approaches to Hard Problems, 2014

2013
Navigating the protein fitness landscape with Gaussian processes.
Proc. Natl. Acad. Sci. USA, 2013

Optimizing waypoints for monitoring spatiotemporal phenomena.
Int. J. Robotics Res., 2013

Towards a living earth simulator
CoRR, 2013

Truthful incentives in crowdsourcing tasks using regret minimization mechanisms.
Proceedings of the 22nd International World Wide Web Conference, 2013

Distributed Submodular Maximization: Identifying Representative Elements in Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

High-Dimensional Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Robust landmark selection for mobile robot navigation.
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

A fresh perspective: learning to sparsify for detection in massive noisy sensor networks.
Proceedings of the 12th International Conference on Information Processing in Sensor Networks (co-located with CPS Week 2013), 2013

Active Learning for Level Set Estimation.
Proceedings of the IJCAI 2013, 2013

Robot navigation in dense human crowds: the case for cooperation.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

Active Learning for Multi-Objective Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

Incentives for Privacy Tradeoff in Community Sensing.
Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

Submodularity in Machine Learning and Vision.
Proceedings of the British Machine Vision Conference, 2013

2012
Inferring Networks of Diffusion and Influence.
ACM Trans. Knowl. Discov. Data, 2012

Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting.
IEEE Trans. Inf. Theory, 2012

Learning Fourier Sparse Set Functions.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

"Smart" design space sampling to predict Pareto-optimal solutions.
Proceedings of the SIGPLAN/SIGBED Conference on Languages, 2012

Joint Optimization and Variable Selection of High-dimensional Gaussian Processes.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Robust sensor placements at informative and communication-efficient locations.
ACM Trans. Sens. Networks, 2011

Submodularity and its applications in optimized information gathering.
ACM Trans. Intell. Syst. Technol., 2011

Simultaneous Optimization of Sensor Placements and Balanced Schedules.
IEEE Trans. Autom. Control., 2011

Greedy Dictionary Selection for Sparse Representation.
IEEE J. Sel. Top. Signal Process., 2011

Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization.
J. Artif. Intell. Res., 2011

Adaptive Submodular Optimization under Matroid Constraints
CoRR, 2011

Contextual Gaussian Process Bandit Optimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Crowdclustering.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Scalable Training of Mixture Models via Coresets.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Demo abstract, the next big one: Detecting earthquakes and other rare events from community-based sensors.
Proceedings of the 10th International Conference on Information Processing in Sensor Networks, 2011

The next big one: Detecting earthquakes and other rare events from community-based sensors.
Proceedings of the 10th International Conference on Information Processing in Sensor Networks, 2011

Randomized Sensing in Adversarial Environments.
Proceedings of the IJCAI 2011, 2011

Dynamic Resource Allocation in Conservation Planning.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
SFO: A Toolbox for Submodular Function Optimization.
J. Mach. Learn. Res., 2010

A Utility-Theoretic Approach to Privacy in Online Services.
J. Artif. Intell. Res., 2010

Efficient Minimization of Decomposable Submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Discriminative Clustering by Regularized Information Maximization.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Near-Optimal Bayesian Active Learning with Noisy Observations.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Unfreezing the robot: Navigation in dense, interacting crowds.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Online distributed sensor selection.
Proceedings of the 9th International Conference on Information Processing in Sensor Networks, 2010

Informative path planning for an autonomous underwater vehicle.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Submodular Dictionary Selection for Sparse Representation.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Budgeted Nonparametric Learning from Data Streams.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization.
Proceedings of the COLT 2010, 2010

2009
Efficient Informative Sensing using Multiple Robots.
J. Artif. Intell. Res., 2009

Optimal Value of Information in Graphical Models.
J. Artif. Intell. Res., 2009

Gaussian Process Bandits without Regret: An Experimental Design Approach
CoRR, 2009

Online Learning of Assignments that Maximize Submodular Functions
CoRR, 2009

Optimizing Sensing: From Water to the Web.
Computer, 2009

Online Learning of Assignments.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Simultaneous placement and scheduling of sensors.
Proceedings of the 8th International Conference on Information Processing in Sensor Networks, 2009

Nonmyopic Adaptive Informative Path Planning for Multiple Robots.
Proceedings of the IJCAI 2009, 2009

2008
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies.
J. Mach. Learn. Res., 2008

Toward Community Sensing.
Proceedings of the 7th International Conference on Information Processing in Sensor Networks, 2008

A Utility-Theoretic Approach to Privacy and Personalization.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Robust, low-cost, non-intrusive sensing and recognition of seated postures.
Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology, 2007

Selecting Observations against Adversarial Objectives.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Cost-effective outbreak detection in networks.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Efficient Planning of Informative Paths for Multiple Robots.
Proceedings of the IJCAI 2007, 2007

Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach.
Proceedings of the Machine Learning, 2007

Nonmyopic Informative Path Planning in Spatio-Temporal Models.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

Near-optimal Observation Selection using Submodular Functions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array.
IEEE Trans. Mob. Comput., 2006

Near-optimal sensor placements: maximizing information while minimizing communication cost.
Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, 2006

Data association for topic intensity tracking.
Proceedings of the Machine Learning, 2006

2005
Near-optimal Nonmyopic Value of Information in Graphical Models.
Proceedings of the UAI '05, 2005

Intelligent light control using sensor networks.
Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, 2005

Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing.
Proceedings of the Ninth IEEE International Symposium on Wearable Computers (ISWC 2005), 2005

Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Near-optimal sensor placements in Gaussian processes.
Proceedings of the Machine Learning, 2005

2004
Mobile decision support for transplantation patient data.
Int. J. Medical Informatics, 2004

Development and implementation of a parallel algorithm for the fast design of oligonucleotide probe sets for diagnostic DNA microarrays.
Concurr. Pract. Exp., 2004

2003
PDA-based decision support and documentation for transplantation surgery data.
Proceedings of the Mobiles Computing in der Medizin, 2003

Mobile wireless acess to EHR and PACS in clinical practice.
Proceedings of the Mobiles Computing in der Medizin, 2003

SenSay: A Context-Aware Mobile Phone.
Proceedings of the 7th International Symposium on Wearable Computers (ISWC 2003), 2003

Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing.
Proceedings of the 7th International Symposium on Wearable Computers (ISWC 2003), 2003

Accurate Method for Fast Design of Diagnostic Oligonucleotide Probe Sets for DNA Microarrays.
Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS 2003), 2003


  Loading...