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Papers
Towards Provably Unlearnable Examples via Bayes Error Optimization
AAAI 2026
Human and AI Perceptual Differences in Image Classification Errors
AAAI 2025
Validate Your Authority: Benchmarking LLMs on Multi-Label Precedent Treatment Classification
EMNLP 2025
Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization
NeurIPS 2024
Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random
NeurIPS 2024
Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
NeurIPS 2024
A Case of Exponential Convergence Rates for SVM
AISTATS 2023
A General Theory of Correct, Incorrect, and Extrinsic Equivariance
NeurIPS 2023
An Active Learning Pipeline for NLU Error Detection in Conversational Agents
ACL 2023
Demystifying Disagreement-on-the-Line in High Dimensions
ICML 2023
ODS: Test-Time Adaptation in the Presence of Open-World Data Shift
ICML 2023
Generalized Resubstitution for Classification Error Estimation
JMLR 2022
Label-Descriptive Patterns and Their Application to Characterizing Classification Errors
ICML 2022
Rethinking Fano’s Inequality in Ensemble Learning
ICML 2022
The Implicit Bias of Benign Overfitting
COLT 2022
Training OOD Detectors in their Natural Habitats
ICML 2022
Accountable Error Characterization
NAACL 2021
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
ICML 2021
Out of a Hundred Trials, How Many Errors Does Your Speaker Verifier Make?
Interspeech 2021
Why Do Document-Level Polarity Classifiers Fail?
NAACL 2021
Identifying Mislabeled Data using the Area Under the Margin Ranking
NeurIPS 2020
Neural Speed Reading Audited
EMNLP 2020
Nonzero-sum Adversarial Hypothesis Testing Games
NeurIPS 2019
On The Classification-Distortion-Perception Tradeoff
NeurIPS 2019
Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors
AISTATS 2019