Carlos Guestrin

Orcid: 0000-0001-6348-5939

Affiliations:
  • University of Washington, Seattle, WA, USA
  • Carnegie Mellon University, Pittsburgh, USA


According to our database1, Carlos Guestrin authored at least 165 papers between 1998 and 2024.

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Bibliography

2024
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data.
Proc. ACM Manag. Data, 2024

Text2SQL is Not Enough: Unifying AI and Databases with TAG.
CoRR, 2024

LOTUS: Enabling Semantic Queries with LLMs Over Tables of Unstructured and Structured Data.
CoRR, 2024

Learning to (Learn at Test Time): RNNs with Expressive Hidden States.
CoRR, 2024

TextGrad: Automatic "Differentiation" via Text.
CoRR, 2024

Post-Hoc Reversal: Are We Selecting Models Prematurely?
CoRR, 2024

Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks.
Proceedings of the IEEE Security and Privacy, 2024

Unifying Corroborative and Contributive Attributions in Large Language Models.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

2023
Learning to (Learn at Test Time).
CoRR, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.
CoRR, 2023

Beyond Confidence: Reliable Models Should Also Consider Atypicality.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021
Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract).
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Neural Network Subspaces.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
The rise and fall of network stars: Analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time.
Inf. Process. Manag., 2020

Set Distribution Networks: a Generative Model for Sets of Images.
CoRR, 2020

Equivariant Neural Rendering.
CoRR, 2020

AdaScale SGD: A User-Friendly Algorithm for Distributed Training.
Proceedings of the 37th International Conference on Machine Learning, 2020

Beyond Accuracy: Behavioral Testing of NLP Models with CheckList.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
A Hardware-Software Blueprint for Flexible Deep Learning Specialization.
IEEE Micro, 2019

Adversarial Fisher Vectors for Unsupervised Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

4 Systems Perspectives into Human-Centered Machine Learning.
Proceedings of the 25th Annual International Conference on Mobile Computing and Networking, 2019

Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

4 Perspectives in Human-Centered Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment.
Proceedings of the 36th International Conference on Machine Learning, 2019

App Usage Predicts Cognitive Ability in Older Adults.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Are Red Roses Red? Evaluating Consistency of Question-Answering Models.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Model-Based Querying in Sensor Networks.
Proceedings of the Encyclopedia of Database Systems, Second Edition, 2018

Over-Optimization of Academic Publishing Metrics: Observing Goodhart's Law in Action.
CoRR, 2018

A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear Structure in Convex Problems.
CoRR, 2018

VTA: An Open Hardware-Software Stack for Deep Learning.
CoRR, 2018

Compact Factorization of Matrices Using Generalized Round-Rank.
CoRR, 2018

TVM: End-to-End Optimization Stack for Deep Learning.
CoRR, 2018

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning.
Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

Training Deep Models Faster with Robust, Approximate Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning to Optimize Tensor Programs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Semantically Equivalent Adversarial Rules for Debugging NLP models.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Anchors: High-Precision Model-Agnostic Explanations.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
The Rise and Fall of Network Stars.
CoRR, 2017

StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent.
Proceedings of the 34th International Conference on Machine Learning, 2017

Scaling Submodular Maximization via Pruned Submodularity Graphs.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Model-Agnostic Interpretability of Machine Learning.
CoRR, 2016

Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance.
CoRR, 2016

Analyzing Complex Network User Arrival Patterns and Their Effect on Network Topologies.
CoRR, 2016

Training Deep Nets with Sublinear Memory Cost.
CoRR, 2016

Programs as Black-Box Explanations.
CoRR, 2016

Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

"Why Should I Trust You?": Explaining the Predictions of Any Classifier.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

XGBoost: A Scalable Tree Boosting System.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015
Information cartography.
Commun. ACM, 2015

The Wisdom of Multiple Guesses.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Efficient Second-Order Gradient Boosting for Conditional Random Fields.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
The Swarm at the Edge of the Cloud.
IEEE Des. Test, 2014

GraphChi-DB: Simple Design for a Scalable Graph Database System - on Just a PC.
CoRR, 2014

Personalized collaborative clustering.
Proceedings of the 23rd International World Wide Web Conference, 2014

Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014.
Proceedings of The Twenty-Third Text REtrieval Conference, 2014

Divide-and-Conquer Learning by Anchoring a Conical Hull.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Reducing Data Loading Bottleneck with Coarse Feature Vectors for Large Scale Learning.
Proceedings of the 3rd International Workshop on Big Data, 2014

Stochastic Gradient Hamiltonian Monte Carlo.
Proceedings of the 31th International Conference on Machine Learning, 2014

GraphGen: An FPGA Framework for Vertex-Centric Graph Computation.
Proceedings of the 22nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2014

Learning Everything about Anything: Webly-Supervised Visual Concept Learning.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
"Metro maps of information" by Dafna Shahaf, Carlos Guestrin and Eric Horvitz, with Ching-man Au Yeung as coordinator.
SIGWEB Newsl., 2013

Representing documents through their readers.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Usability in machine learning at scale with graphlab.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012
Connecting Two (or Less) Dots: Discovering Structure in News Articles.
ACM Trans. Knowl. Discov. Data, 2012

Distributed GraphLab: A Framework for Machine Learning in the Cloud.
Proc. VLDB Endow., 2012

Sample Complexity of Composite Likelihood.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Riffled Independence for Efficient Inference with Partial Rankings.
J. Artif. Intell. Res., 2012

Concept Modeling with Superwords
CoRR, 2012

Trains of thought: generating information maps.
Proceedings of the 21st World Wide Web Conference 2012, 2012

GraphChi: Large-Scale Graph Computation on Just a PC.
Proceedings of the 10th USENIX Symposium on Operating Systems Design and Implementation, 2012

PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs.
Proceedings of the 10th USENIX Symposium on Operating Systems Design and Implementation, 2012

Metro maps of science.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Hierarchical Exploration for Accelerating Contextual Bandits.
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

Kernel Belief Propagation.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

GraphLab: A Distributed Framework for Machine Learning in the Cloud
CoRR, 2011

Efficient Probabilistic Inference with Partial Ranking Queries.
Proceedings of the UAI 2011, 2011

Linear Submodular Bandits and their Application to Diversified Retrieval.
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

Beyond keyword search: discovering relevant scientific literature.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Parallel Coordinate Descent for L1-Regularized Loss Minimization.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Nonparametric Tree Graphical Models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Focused Belief Propagation for Query-Specific Inference.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Linear Characteristic Graphical Models: Representation, Inference and Applications
CoRR, 2010

Uncovering the Riffled Independence Structure of Rankings
CoRR, 2010

AI Theory and Practice: A Discussion on Hard Challenges and Opportunities Ahead.
AI Mag., 2010

GraphLab: A New Framework For Parallel Machine Learning.
Proceedings of the UAI 2010, 2010

Evidence-Specific Structures for Rich Tractable CRFs.
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

Inference with Multivariate Heavy-Tails in Linear Models.
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

Connecting the dots between news articles.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Learning Hierarchical Riffle Independent Groupings from Rankings.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Learning Tree Conditional Random Fields.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Multiresolution Cube Estimators for Sensor Network Aggregate Queries.
Proceedings of the 4th Alberto Mendelzon International Workshop on Foundations of Data Management, 2010

2009
Model-based Querying in Sensor Networks.
Proceedings of the Encyclopedia of Database Systems, 2009

Learning Thin Junction Trees via Graph Cuts.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Exploiting Probabilistic Independence for Permutations.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Fourier Theoretic Probabilistic Inference over Permutations.
J. Mach. Learn. Res., 2009

Residual Splash for Optimally Parallelizing Belief Propagation.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

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

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

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

Distributed Parallel Inference on Large Factor Graphs.
Proceedings of the UAI 2009, 2009

Riffled Independence for Ranked Data.
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

How optimized environmental sensing helps address information overload on the web.
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, 2009

Turning down the noise in the blogosphere.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

Approximating sensor network queries using in-network summaries.
Proceedings of the 8th International Conference on Information Processing in Sensor Networks, 2009

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

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

Efficient Inference for Distributions on Permutations.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Efficient Principled Learning of Thin Junction Trees.
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

Information Survival Threshold in Sensor and P2P Networks.
Proceedings of the INFOCOM 2007. 26th IEEE International Conference on Computer Communications, 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
Solving Factored MDPs with Hybrid State and Action Variables.
J. Artif. Intell. Res., 2006

Distributed Inference in Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Data gathering tours in sensor networks.
Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, 2006

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

Distributed localization of networked cameras.
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
Model-based approximate querying in sensor networks.
VLDB J., 2005

Modeling Link Qualities in a Sensor Network.
Informatica (Slovenia), 2005

Resource-Aware Wireless Sensor-Actuator Networks.
IEEE Data Eng. Bull., 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


A robust architecture for distributed inference in sensor networks.
Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, 2005

Concurrent Hierarchical Reinforcement Learning.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 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

Learning structured prediction models: a large margin approach.
Proceedings of the Machine Learning, 2005

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

Exploiting Correlated Attributes in Acquisitional Query Processing.
Proceedings of the 21st International Conference on Data Engineering, 2005

Using Probabilistic Models for Data Management in Acquisitional Environments.
Proceedings of the Second Biennial Conference on Innovative Data Systems Research, 2005

2004
Model-Driven Data Acquisition in Sensor Networks.
Proceedings of the (e)Proceedings of the Thirtieth International Conference on Very Large Data Bases, VLDB 2004, Toronto, Canada, August 31, 2004

Robust Probabilistic Inference in Distributed Systems.
Proceedings of the UAI '04, 2004

Solving Factored MDPs with Continuous and Discrete Variables.
Proceedings of the UAI '04, 2004

Distributed regression: an efficient framework for modeling sensor network data.
Proceedings of the Third International Symposium on Information Processing in Sensor Networks, 2004

2003
Planning under uncertainty in complex structured environments.
PhD thesis, 2003

Stochastic Roadmap Simulation: An Efficient Representation and Algorithm for Analyzing Molecular Motion.
J. Comput. Biol., 2003

Efficient Solution Algorithms for Factored MDPs.
J. Artif. Intell. Res., 2003

Max-Margin Markov Networks.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Generalizing Plans to New Environments in Relational MDPs.
Proceedings of the IJCAI-03, 2003

2002
Stochastic Conformational Roadmaps for Computing Ensemble Properties of Molecular Motion.
Proceedings of the Algorithmic Foundations of Robotics V, 2002

Distributed Planning in Hierarchical Factored MDPs.
Proceedings of the UAI '02, 2002

Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion.
Proceedings of the Sixth Annual International Conference on Computational Biology, 2002

Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs.
Proceedings of the Machine Learning, 2002

Coordinated Reinforcement Learning.
Proceedings of the Machine Learning, 2002

Using robotics to fold proteins and dock ligands.
Proceedings of the European Conference on Computational Biology (ECCB 2002), 2002

Stochastic roadmap simulation for the study of ligand-protein interactions.
Proceedings of the European Conference on Computational Biology (ECCB 2002), 2002

Greedy Linear Value-Approximation for Factored Markov Decision Processes.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

Context-Specific Multiagent Coordination and Planning with Factored MDPs.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Robust Combination of Local Controllers.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Multiagent Planning with Factored MDPs.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Max-norm Projections for Factored MDPs.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

2000
Outdoor Visual Position Estimation for Planetary Rovers.
Auton. Robots, 2000

1998
Industrial applications of image mosaicing and stabilization.
Proceedings of the Knowledge-Based Intelligent Electronic Systems, 1998

Fast software image stabilization with color registration.
Proceedings of the Proceedings 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, 1998


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