Pradeep Ravikumar

Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers NeurIPS 2024 From Causal to Concept-Based Representation Learning NeurIPS 2024 Identifying General Mechanism Shifts in Linear Causal Representations NeurIPS 2024 LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation NeurIPS 2024 Markov Equivalence and Consistency in Differentiable Structure Learning NeurIPS 2024 Faith-Shap: The Faithful Shapley Interaction Index JMLR 2023 Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games AISTATS 2023 AnEMIC: A Framework for Benchmarking ICD Coding Models EMNLP 2022 An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization AISTATS 2022 Building Robust Ensembles via Margin Boosting ICML 2022 Fundamental Limits and Tradeoffs in Invariant Representation Learning JMLR 2022 Heavy-tailed Streaming Statistical Estimation AISTATS 2022 Iterative Alignment Flows AISTATS 2022 Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations AISTATS 2022 Contrastive learning of strong-mixing continuous-time stochastic processes AISTATS 2021 DORO: Distributional and Outlier Robust Optimization ICML 2021 Efficient Bandit Convex Optimization: Beyond Linear Losses COLT 2021 Improving Compositional Generalization in Classification Tasks via Structure Annotations ACL 2021 On Proximal Policy Optimization’s Heavy-tailed Gradients ICML 2021 Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances AAAI 2021 Subseasonal climate prediction in the western US using Bayesian spatial models UAI 2021 A Robust Univariate Mean Estimator is All You Need AISTATS 2020 Automated Dependence Plots UAI 2020 Certified Robustness to Label-Flipping Attacks via Randomized Smoothing ICML 2020 Class-Weighted Classification: Trade-offs and Robust Approaches ICML 2020 Learning Sparse Nonparametric DAGs AISTATS 2020 MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius ICLR 2020 Minimizing FLOPs to Learn Efficient Sparse Representations ICLR 2020 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification ICML 2020 Uniform Convergence of Rank-weighted Learning ICML 2020 Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression COLT 2019 Building Human-Machine Trust via Interpretability AAAI 2019 Revisiting Adversarial Risk AISTATS 2019 Binary Classification with Karmic, Threshold-Quasi-Concave Metrics ICML 2018 Cost-Sensitive Learning with Noisy Labels JMLR 2018 Deep Density Destructors ICML 2018 Loss Decomposition for Fast Learning in Large Output Spaces ICML 2018 Word Mover’s Embedding: From Word2Vec to Document Embedding EMNLP 2018 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization ICML 2017 Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain AISTATS 2017 Latent Feature Lasso ICML 2017 Minimax Gaussian Classification & Clustering AISTATS 2017 Ordinal Graphical Models: A Tale of Two Approaches ICML 2017 Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition AISTATS 2017 A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery ICML 2016 Optimal Classification with Multivariate Losses ICML 2016 PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification ICML 2016 Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies ICML 2016 A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models ICML 2015 Distributional Rank Aggregation, and an Axiomatic Analysis ICML 2015 Graphical Models via Univariate Exponential Family Distributions JMLR 2015 Sparsistency of \ell_1-Regularized M-Estimators AISTATS 2015 Vector-Space Markov Random Fields via Exponential Families ICML 2015 Admixture of Poisson MRFs: A Topic Model with Word Dependencies ICML 2014 Elementary Estimators for High-Dimensional Linear Regression ICML 2014 Elementary Estimators for Sparse Covariance Matrices and other Structured Moments ICML 2014 Exponential Family Matrix Completion under Structural Constraints ICML 2014 Learning Graphs with a Few Hubs ICML 2014 Mixed Graphical Models via Exponential Families AISTATS 2014 QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation JMLR 2014 Human Boosting ICML 2013 On Robust Estimation of High Dimensional Generalized Linear Models IJCAI 2013 High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods AISTATS 2012 Perturbation based Large Margin Approach for Ranking AISTATS 2012 On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011 On NDCG Consistency of Listwise Ranking Methods AISTATS 2011 Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes JMLR 2010