Adrian Weller

CoRR, 2024

Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data.

[BibT_eX]

[DOI]

CoRR, 2024

On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Perspective.

[BibT_eX]

[DOI]

Shoaib Ahmed Siddiqui

CoRR, 2024

Linear Transformer Topological Masking with Graph Random Features.

[BibT_eX]

[DOI]

Krishnamurthy Dj Dvijotham

CoRR, 2024

On the Weaknesses of Backdoor-based Model Watermarking: An Information-theoretic Perspective.

[BibT_eX]

[DOI]

CoRR, 2024

Mutual Information Multinomial Estimation.

[BibT_eX]

[DOI]

CoRR, 2024

Can Large Language Models Understand Symbolic Graphics Programs?

[BibT_eX]

[DOI]

CoRR, 2024

Building Machines that Learn and Think with People.

[BibT_eX]

[DOI]

CoRR, 2024

People use fast, goal-directed simulation to reason about novel games.

[BibT_eX]

[DOI]

CoRR, 2024

Modulating Language Model Experiences through Frictions.

[BibT_eX]

[DOI]

CoRR, 2024

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation.

[BibT_eX]

[DOI]

CoRR, 2024

In-Context In-Context Learning with Transformer Neural Processes.

[BibT_eX]

[DOI]

CoRR, 2024

Approximately Equivariant Neural Processes.

[BibT_eX]

[DOI]

CoRR, 2024

Certificates of Differential Privacy and Unlearning for Gradient-Based Training.

[BibT_eX]

[DOI]

CoRR, 2024

Large Language Models Must Be Taught to Know What They Don't Know.

[BibT_eX]

[DOI]

CoRR, 2024

Representational Alignment Supports Effective Machine Teaching.

[BibT_eX]

[DOI]

CoRR, 2024

Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport.

[BibT_eX]

[DOI]

Stratis Markou

Richard E. Turner

CoRR, 2024

Computing Power and the Governance of Artificial Intelligence.

[BibT_eX]

[DOI]

CoRR, 2024

MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Confidential-DPproof: Confidential Proof of Differentially Private Training.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

General Graph Random Features.

[BibT_eX]

[DOI]

Eli Berger

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Repelling Random Walks.

[BibT_eX]

[DOI]

Eli Berger

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ALVIN: Active Learning Via INterpolation.

[BibT_eX]

[DOI]

Michalis Korakakis

Andreas Vlachos

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers.

[BibT_eX]

[DOI]

Shanda Li

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Perspectives on incorporating expert feedback into model updates.

[BibT_eX]

[DOI]

Patterns, July, 2023

Self-Guided Belief Propagation - A Homotopy Continuation Method.

[BibT_eX]

[DOI]

Christian Knoll

Franz Pernkopf

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Continual Learning by Modeling Intra-Class Variation.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

SphereFace Revived: Unifying Hyperspherical Face Recognition.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Estimation of Concept Explanations Should be Uncertainty Aware.

[BibT_eX]

[DOI]

CoRR, 2023

Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning.

[BibT_eX]

[DOI]

Matthew Ashman

Tommy Rochussen

CoRR, 2023

AI for Mathematics: A Cognitive Science Perspective.

[BibT_eX]

[DOI]

CoRR, 2023

Getting aligned on representational alignment.

[BibT_eX]

[DOI]

CoRR, 2023

Universal Graph Random Features.

[BibT_eX]

[DOI]

Eli Berger

CoRR, 2023

Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey.

[BibT_eX]

[DOI]

Victoria Smith

Carolyn Ashurst

CoRR, 2023

The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence.

[BibT_eX]

[DOI]

CoRR, 2023

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs.

[BibT_eX]

[DOI]

CoRR, 2023

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time.

[BibT_eX]

[DOI]

Matthew Barker

Katherine M. Collins

Krishnamurthy Dvijotham

CoRR, 2023

Evaluating Language Models for Mathematics through Interactions.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Personalized Decision Support Policies.

[BibT_eX]

[DOI]

Valerie Chen

Katherine M. Collins

Parameswaran Kamalaruban

Emma Kallina

Ameet Talwalkar

CoRR, 2023

Robust Learning from Explanations.

[BibT_eX]

[DOI]

CoRR, 2023

Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents.

[BibT_eX]

[DOI]

CoRR, 2023

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features.

[BibT_eX]

[DOI]

CoRR, 2023

On the informativeness of supervision signals.

[BibT_eX]

[DOI]

Ilia Sucholutsky

Ruairidh M. Battleday

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Mnemonist: Locating Model Parameters that Memorize Training Examples.

[BibT_eX]

[DOI]

Jamie Hayes

Borja Balle

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Human-in-the-Loop Mixup.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Learning to Receive Help: Intervention-Aware Concept Embedding Models.

[BibT_eX]

[DOI]

Katie Collins

Krishnamurthy Dvijotham

Zohreh Shams

Mateja Jamnik

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Certification of Distributional Individual Fairness.

[BibT_eX]

[DOI]

Matthew Wicker

Vihari Piratla

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quasi-Monte Carlo Graph Random Features.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Controlling Text-to-Image Diffusion by Orthogonal Finetuning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diffused Redundancy in Pre-trained Representations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Use perturbations when learning from explanations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Physics-Based Decoding Improves Magnetic Resonance Fingerprinting.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Simplex Random Features.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Efficient Graph Field Integrators Meet Point Clouds.

[BibT_eX]

[DOI]

Somnath Basu Roy Chowdhury

Proceedings of the International Conference on Machine Learning, 2023

Is Learning Summary Statistics Necessary for Likelihood-free Inference?

[BibT_eX]

[DOI]

Yanzhi Chen

Michael U. Gutmann

Proceedings of the International Conference on Machine Learning, 2023

Robust Explanation Constraints for Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Confidential-PROFITT: Confidential PROof of FaIr Training of Trees.

[BibT_eX]

[DOI]

Sierra Calanda Wyllie

Proceedings of the Eleventh International Conference on Learning Representations, 2023

GeValDi: Generative Validation of Discriminative Models.

[BibT_eX]

[DOI]

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Generalizing and Decoupling Neural Collapse via Hyperspherical Uniformity Gap.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Pairwise Similarity Learning is SimPLE.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Harms from Increasingly Agentic Algorithmic Systems.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Media Coverage of Predictive Policing: Bias, Police Engagement, and the Future of Transparency.

[BibT_eX]

[DOI]

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines.

[BibT_eX]

[DOI]

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Fairness Without Demographic Data: A Survey of Approaches.

[BibT_eX]

[DOI]

Carolyn Ashurst

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Iterative Teaching by Data Hallucination.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Human Uncertainty in Concept-Based AI Systems.

[BibT_eX]

[DOI]

Katherine Maeve Collins

Matthew Barker

Krishnamurthy Dvijotham

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Towards Robust Metrics for Concept Representation Evaluation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Do Invariances in Deep Neural Networks Align with Human Perception?

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Approximating Full Conformal Prediction at Scale via Influence Functions.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

On the Expressive Flexibility of Self-Attention Matrices.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Towards More Robust Interpretation via Local Gradient Alignment.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

How transparency modulates trust in artificial intelligence.

[BibT_eX]

[DOI]

John Zerilli

Patterns, 2022

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

[BibT_eX]

[DOI]

Pattanasak Mongkolwat

Lorena Escudero Sanchez

Nat. Mach. Intell., 2022

Web-based Elicitation of Human Perception on mixup Data.

[BibT_eX]

[DOI]

CoRR, 2022

Can We Automate the Analysis of Online Child Sexual Exploitation Discourse?

[BibT_eX]

[DOI]

CoRR, 2022

Concept Embedding Models.

[BibT_eX]

[DOI]

Michelangelo Diligenti

CoRR, 2022

Synthetic Data - what, why and how?

[BibT_eX]

[DOI]

CoRR, 2022

Partitioned Variational Inference: A Framework for Probabilistic Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets.

[BibT_eX]

[DOI]

Miri Zilka

Bradley Butcher

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

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off.

[BibT_eX]

[DOI]

Michelangelo Diligenti

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

Chefs' Random Tables: Non-Trigonometric Random Features.

[BibT_eX]

[DOI]

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

Scalable Infomin Learning.

[BibT_eX]

[DOI]

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

On the Utility of Prediction Sets in Human-AI Teams.

[BibT_eX]

[DOI]

Varun Babbar

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Measuring Representational Robustness of Neural Networks Through Shared Invariances.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

SphereFace2: Binary Classification is All You Need for Deep Face Recognition.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Hybrid Random Features.

[BibT_eX]

[DOI]

Dmitry Kalashnikov

Vikas Sindhwani

Proceedings of the Tenth International Conference on Learning Representations, 2022

Eliciting and Learning with Soft Labels from Every Annotator.

[BibT_eX]

[DOI]

Katherine M. Collins

Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022

Multi-disciplinary fairness considerations in machine learning for clinical trials.

[BibT_eX]

[DOI]

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Structural Causal 3D Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness.

[BibT_eX]

[DOI]

Proceedings of the Equity and Access in Algorithms, Mechanisms, and Optimization, 2022

Towards Principled Disentanglement for Domain Generalization.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Robust Learning from Observation with Model Misspecification.

[BibT_eX]

[DOI]

Luca Viano

Yu-Ting Huang

Parameswaran Kamalaruban

Craig Innes

Subramanian Ramamoorthy

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study.

[BibT_eX]

[DOI]

Miri Zilka

Holli Sargeant

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

Racial Disparities in the Enforcement of Marijuana Violations in the US.

[BibT_eX]

[DOI]

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates.

[BibT_eX]

[DOI]

Dan Ley

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

On the Fairness of Causal Algorithmic Recourse.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

CrossWalk: Fairness-Enhanced Node Representation Learning.

[BibT_eX]

[DOI]

Baharan Mirzasoleiman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

[BibT_eX]

[DOI]

Pattanasak Mongkolwat

Lorena Escudero Sanchez

Nat. Mach. Intell., 2021

Filling gaps in trustworthy development of AI.

[BibT_eX]

[DOI]

CoRR, 2021

Exploring Alignment of Representations with Human Perception.

[BibT_eX]

[DOI]

CoRR, 2021

PolyViT: Co-training Vision Transformers on Images, Videos and Audio.

[BibT_eX]

[DOI]

Anurag Arnab

CoRR, 2021

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

[BibT_eX]

[DOI]

Pattanasak Mongkolwat

Lorena Escudero Sanchez

Carola-Bibiane Schönlieb

Tian Xia

CoRR, 2021

DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement.

[BibT_eX]

[DOI]

CoRR, 2021

On the Expressive Power of Self-Attention Matrices.

[BibT_eX]

[DOI]

CoRR, 2021

Do Concept Bottleneck Models Learn as Intended?

[BibT_eX]

[DOI]

CoRR, 2021

Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches.

[BibT_eX]

[DOI]

CoRR, 2021

δ-CLUE: Diverse Sets of Explanations for Uncertainty Estimates.

[BibT_eX]

[DOI]

Dan Ley

CoRR, 2021

Unlocking Pixels for Reinforcement Learning via Implicit Attention.

[BibT_eX]

[DOI]

Deepali Jain

Jack Parker-Holder

CoRR, 2021

Robust Inverse Reinforcement Learning under Transition Dynamics Mismatch.

[BibT_eX]

[DOI]

Luca Viano

Yu-Ting Huang

Parameswaran Kamalaruban

Volkan Cevher

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Iterative Teaching by Label Synthesis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sub-Linear Memory: How to Make Performers SLiM.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Debiasing a First-order Heuristic for Approximate Bi-level Optimization.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Rethinking Attention with Performers.

[BibT_eX]

[DOI]

David Benjamin Belanger

Lucy J. Colwell

José Miguel Hernández-Lobato

Proceedings of the 9th International Conference on Learning Representations, 2021

Getting a CLUE: A Method for Explaining Uncertainty Estimates.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

An Algorithmic Framework for Positive Action.

[BibT_eX]

[DOI]

Proceedings of the EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5, 2021

Orthogonal Over-Parameterized Training.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Fast conformal classification using influence functions.

[BibT_eX]

[DOI]

Giovanni Cherubin

Proceedings of the Conformal and Probabilistic Prediction and Applications, 2021

Learning with Hyperspherical Uniformity.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Machine Learning and the Meaning of Equal Treatment.

[BibT_eX]

[DOI]

Joshua Simons

Sophia Adams Bhatti

Gabrielle Gauthier Melançon

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Beyond Reasonable Doubt: Improving Fairness in Budget-Constrained Decision Making using Confidence Thresholds.

[BibT_eX]

[DOI]

Michiel A. Bakker

Duy Patrick Tu

Krishna P. Gummadi

Alex 'Sandy' Pentland

Kush R. Varshney

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Leveraging Data Science to Combat COVID-19: A Comprehensive Review.

[BibT_eX]

[DOI]

Maged N. Kamel Boulos

Gabrielle Gauthier Melançon

Jon Crowcroft

IEEE Trans. Artif. Intell., 2020

Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training.

[BibT_eX]

[DOI]

CoRR, 2020

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

[BibT_eX]

[DOI]

CoRR, 2020

Machine Learning Explainability for External Stakeholders.

[BibT_eX]

[DOI]

CoRR, 2020

An Ode to an ODE.

[BibT_eX]

[DOI]

Jean-Jacques E. Slotine

CoRR, 2020

UFO-BLO: Unbiased First-Order Bilevel Optimization.

[BibT_eX]

[DOI]

CoRR, 2020

Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers.

[BibT_eX]

[DOI]

CoRR, 2020

Time Dependence in Non-Autonomous Neural ODEs.

[BibT_eX]

[DOI]

Jake Varley

Honglak Lee

Jean-Jacques E. Slotine

CoRR, 2020

Dimensions of Diversity in Human Perceptions of Algorithmic Fairness.

[BibT_eX]

[DOI]

Nina Grgic-Hlaca

Elissa M. Redmiles

CoRR, 2020

CWY Parametrization for Scalable Learning of Orthogonal and Stiefel Matrices.

[BibT_eX]

[DOI]

CoRR, 2020

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims.

[BibT_eX]

[DOI]

Thomas Krendl Gilbert

CoRR, 2020

Ode to an ODE.

[BibT_eX]

[DOI]

Jean-Jacques E. Slotine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks.

[BibT_eX]

[DOI]

Moein Khajehnejad

Ahmad Asgharian Rezaei

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Evaluating and Aggregating Feature-based Model Explanations.

[BibT_eX]

[DOI]

José M. F. Moura

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Stochastic Flows and Geometric Optimization on the Orthogonal Group.

[BibT_eX]

[DOI]

David Cheikhi

Proceedings of the 37th International Conference on Machine Learning, 2020

Explainable machine learning in deployment.

[BibT_eX]

[DOI]

Proceedings of the FAT* '20: Conference on Fairness, 2020

Now You See Me (CME): Concept-based Model Extraction.

[BibT_eX]

[DOI]

Proceedings of the CIKM 2020 Workshops co-located with 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020

Human-Centered Approaches to Fair and Responsible AI.

[BibT_eX]

[DOI]

Min Kyung Lee

Nina Grgic-Hlaca

Michael Carl Tschantz

Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Artificial Intelligence Safety, 2020

Fair Enough: Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds.

[BibT_eX]

[DOI]

Michiel A. Bakker

Humberto Riverón Valdés

Proceedings of the Workshop on Artificial Intelligence Safety, 2020

2019

Transparency: Motivations and Challenges.

[BibT_eX]

[DOI]

Proceedings of the Explainable AI: Interpreting, 2019

Motivations and Risks of Machine Ethics.

[BibT_eX]

[DOI]

Proc. IEEE, 2019

Train and Test Tightness of LP Relaxations in Structured Prediction.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2019

DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning.

[BibT_eX]

[DOI]

Michiel A. Bakker

Duy Patrick Tu

Humberto Riverón Valdés

CoRR, 2019

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision.

[BibT_eX]

[DOI]

CoRR, 2019

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks.

[BibT_eX]

[DOI]

CoRR, 2019

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models.

[BibT_eX]

[DOI]

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

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences.

[BibT_eX]

[DOI]

Proceedings of the Joint Post-proceedings of the First and Second International Conference on Microservices, 2019

Unifying Orthogonal Monte Carlo Methods.

[BibT_eX]

[DOI]

Wenyu Chen

Proceedings of the 36th International Conference on Machine Learning, 2019

TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning.

[BibT_eX]

[DOI]

Tameem Adel

Proceedings of the 36th International Conference on Machine Learning, 2019

Orthogonal Estimation of Wasserstein Distances.

[BibT_eX]

[DOI]

Jiri Hron

Yunhao Tang

Tamás Sarlós

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

One-Network Adversarial Fairness.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018).

[BibT_eX]

[DOI]

Been Kim

Kush R. Varshney

CoRR, 2018

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Geometrically Coupled Monte Carlo Sampling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Blind Justice: Fairness with Encrypted Sensitive Attributes.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Structured Evolution with Compact Architectures for Scalable Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Bucket Renormalization for Approximate Inference.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models.

[BibT_eX]

[DOI]

Tameem Adel

Zoubin Ghahramani

Proceedings of the 35th International Conference on Machine Learning, 2018

The Geometry of Random Features.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Gauged Mini-Bucket Elimination for Approximate Inference.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Purple Feed: Identifying High Consensus News Posts on Social Media.

[BibT_eX]

[DOI]

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017).

[BibT_eX]

[DOI]

CoRR, 2017

Challenges for Transparency.

[BibT_eX]

[DOI]

CoRR, 2017

On Fairness, Diversity and Randomness in Algorithmic Decision Making.

[BibT_eX]

[DOI]

CoRR, 2017

Mapping Intelligence: Requirements and Possibilities.

[BibT_eX]

[DOI]

Fernando Martínez-Plumed

José Hernández-Orallo

Proceedings of the Philosophy and Theory of Artificial Intelligence 2017, 2017

From Parity to Preference-based Notions of Fairness in Classification.

[BibT_eX]

[DOI]

Muhammad Bilal Zafar

Isabel Valera

Manuel Gomez-Rodriguez

Krishna P. Gummadi

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

Uprooting and Rerooting Higher-Order Graphical Models.

[BibT_eX]

[DOI]

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

The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings.

[BibT_eX]

[DOI]

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

Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Lost Relatives of the Gumbel Trick.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Conditions beyond treewidth for tightness of higher-order LP relaxations.

[BibT_eX]

[DOI]

Aldo Pacchiano

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Characterizing Tightness of LP Relaxations by Forbidding Signed Minors.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Uprooting and Rerooting Graphical Models.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Train and Test Tightness of LP Relaxations in Structured Prediction.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Tightness of LP Relaxations for Almost Balanced Models.

[BibT_eX]

[DOI]

David A. Sontag

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Clamping Improves TRW and Mean Field Approximations.

[BibT_eX]

[DOI]

Justin Domke

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Bethe and Related Pairwise Entropy Approximations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Revisiting the Limits of MAP Inference by MWSS on Perfect Graphs.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Methods for Inference in Graphical Models.

[BibT_eX]

[DOI]

PhD thesis, 2014

Understanding the Bethe Approximation: When and How can it go Wrong?

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Approximating the Bethe Partition Function.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Clamping Variables and Approximate Inference.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

On MAP Inference by MWSS on Perfect Graphs.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Bethe Bounds and Approximating the Global Optimum.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2009

Structured Prediction Models for Chord Transcription of Music Audio.

[BibT_eX]

[DOI]

Daniel P. W. Ellis