← Authors

Pradeep Ravikumar

68 papers · 2010–2024 · 12 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (12) πŸƒ Academic Marathon (14) πŸ—ΊοΈ Taxonomy Completionist (30) 🐝 Cross-Pollinator (7) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (26) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (13) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (102) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner πŸ’Ž Century Club (68) πŸ”₯ Unstoppable (15)

Conferences

ICML (26) AISTATS (18) JMLR (6) NIPS (5) AAAI (2) COLT (2) EMNLP (2) ICLR (2) UAI (2) ACL (1) IJCAI (1) IJCNLP (1)

Top co-authors

Ian En-Hsu Yen (8) Inderjit Dhillon (8) Eunho Yang (8) Bryon Aragam (7) Arun Sai Suggala (7) Adarsh Prasad (6) Chen Dan (6) David Inouye (4) Ambuj Tewari (4) Justin Khim (3)

Keywords

graphical model (8) convex optimization (8) markov random field (5) high-dimensional statistics (4) structure learning (4) exponential family (4) adversarial robustness (4) heavy-tailed distribution (3) empirical risk minimization (3) statistical guarantee (3) covariance estimation (2) causal discovery (2) feature importance (2) feature attribution (2) causal inference (2) primal-dual optimization (2) logistic regression (2) parameter estimation (2) binary classification (2) domain generalization (2)

Papers

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