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← Authors

Edgar Dobriban

30 papers · 2019–2025 · 10 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (18) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird
πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (142) ⚑ Prolific Year (9) πŸ’Ž Century Club (30) πŸ”₯ Unstoppable (7) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

NIPS (9) ICML (6) JMLR (5) ICLR (4) AAAI (1) COLT (1) CORL (1) EMNLP (1) INTERSPEECH (1) NAACL (1)

Top co-authors

Hamed Hassani (8) Osbert Bastani (7) Insup Lee (7) Xinmeng Huang (5) Sangdon Park (4) Donghwan Lee (4) Behrad Moniri (3) Sifan Liu (3) Shuo Li (2) James Weimer (2)

Research topics

Statistics (1)

Keywords

uncertainty quantification (4) distributed learning (3) ridge regression (3) large language model (3) least square (3) implicit regularization (2) statistical learning (2) deep neural network (2) variance reduction (2) empirical risk minimization (2) mean squared error (2) random projection (2) data augmentation (2) language model (2) learning theory (2) model evaluation (2) group theory (2) random matrix theory (2) model compression (2) domain adaptation (1)

Papers

Evaluating the Performance of Large Language Models via Debates NAACL 2025 JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models NIPS 2024 A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks ICML 2024 PAC Prediction Sets Under Label Shift ICLR 2024 Uncertainty in Language Models: Assessment through Rank-Calibration EMNLP 2024 One-Shot Safety Alignment for Large Language Models via Optimal Dualization NIPS 2024 $\mathrm{SE}(3)$-Equivariant Attention Networks for Shape Reconstruction in Function Space ICLR 2023 Demystifying Disagreement-on-the-Line in High Dimensions ICML 2023 Automatically Predicting Perceived Conversation Quality in a Pediatric Sample Enriched for Autism INTERSPEECH 2023 T-Cal: An Optimal Test for the Calibration of Predictive Models JMLR 2023 Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries JMLR 2023 iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection AAAI 2022 Fair Bayes-Optimal Classifiers Under Predictive Parity NIPS 2022 PAC Prediction Sets Under Covariate Shift ICLR 2022 Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces ICML 2022 PAC Prediction Sets for Meta-Learning NIPS 2022 Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints NIPS 2022 Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates CORL 2022 What Causes the Test Error? Going Beyond Bias-Variance via ANOVA JMLR 2021 Sparse sketches with small inversion bias COLT 2021 Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform NIPS 2020 Implicit Regularization and Convergence for Weight Normalization NIPS 2020 WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions JMLR 2020 Ridge Regression: Structure, Cross-Validation, and Sketching ICLR 2020 A Group-Theoretic Framework for Data Augmentation JMLR 2020 The Implicit Regularization of Stochastic Gradient Flow for Least Squares ICML 2020 DeltaGrad: Rapid retraining of machine learning models ICML 2020 One-shot Distributed Ridge Regression in High Dimensions ICML 2020 A Group-Theoretic Framework for Data Augmentation NIPS 2020 Asymptotics for Sketching in Least Squares Regression NIPS 2019