Ravikumar, Pradeep

72 publications

NeurIPS 2024 Do LLMs Dream of Elephants (when Told Not to)? Latent Concept Association and Associative Memory in Transformers Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

NeurIPS 2024 From Causal to Concept-Based Representation Learning Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

NeurIPS 2024 Identifying General Mechanism Shifts in Linear Causal Representations Tianyu Chen, Kevin Bello, Francesco Locatello, Bryon Aragam, Pradeep Ravikumar

NeurIPS 2024 LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation Bowen Li, Zhaoyu Li, Qiwei Du, Jinqi Luo, Wenshan Wang, Yaqi Xie, Simon Stepputtis, Chen Wang, Katia Sycara, Pradeep Ravikumar, Alexander Gray, Xujie Si, Sebastian Scherer

NeurIPS 2024 Markov Equivalence and Consistency in Differentiable Structure Learning Chang Deng, Kevin Bello, Pradeep Ravikumar, Bryon Aragam

JMLR 2023 Faith-Shap: The Faithful Shapley Interaction Index Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar

AISTATS 2023 Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang

AISTATS 2022 An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski

AISTATS 2022 Heavy-Tailed Streaming Statistical Estimation Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

AISTATS 2022 Iterative Alignment Flows Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar, David I. Inouye

AISTATS 2022 Threading the Needle of on and Off-Manifold Value Functions for Shapley Explanations Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar

ICML 2022 Building Robust Ensembles via Margin Boosting Dinghuai Zhang, Hongyang Zhang, Aaron Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala

CHIL 2022 Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence Juyong Kim, Jeremy C Weiss, Pradeep Ravikumar

JMLR 2022 Fundamental Limits and Tradeoffs in Invariant Representation Learning Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar

AISTATS 2021 Contrastive Learning of Strong-Mixing Continuous-Time Stochastic Processes Bingbin Liu, Pradeep Ravikumar, Andrej Risteski

ICML 2021 DORO: Distributional and Outlier Robust Optimization Runtian Zhai, Chen Dan, Zico Kolter, Pradeep Ravikumar

COLT 2021 Efficient Bandit Convex Optimization: Beyond Linear Losses Arun Sai Suggala, Pradeep Ravikumar, Praneeth Netrapalli

ICML 2021 On Proximal Policy Optimization’s Heavy-Tailed Gradients Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

AAAI 2021 Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee

UAI 2021 Subseasonal Climate Prediction in the Western US Using Bayesian Spatial Models Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar

AISTATS 2020 A Robust Univariate Mean Estimator Is All You Need Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

UAI 2020 Automated Dependence Plots David Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar

ICML 2020 Certified Robustness to Label-Flipping Attacks via Randomized Smoothing Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter

ICML 2020 Class-Weighted Classification: Trade-Offs and Robust Approaches Ziyu Xu, Chen Dan, Justin Khim, Pradeep Ravikumar

AISTATS 2020 Learning Sparse Nonparametric DAGs Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric Xing

ICLR 2020 MACER: Attack-Free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

ICLR 2020 Minimizing FLOPs to Learn Efficient Sparse Representations Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos

ICML 2020 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification Chen Dan, Yuting Wei, Pradeep Ravikumar

ICML 2020 Uniform Convergence of Rank-Weighted Learning Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

COLT 2019 Adaptive Hard Thresholding for Near-Optimal Consistent Robust Regression Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain

AAAI 2019 Building Human-Machine Trust via Interpretability Umang Bhatt, Pradeep Ravikumar, José M. F. Moura

AISTATS 2019 Revisiting Adversarial Risk Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar

AAAI 2018 A Voting-Based System for Ethical Decision Making Ritesh Noothigattu, Snehalkumar (Neil) S. Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, Ariel D. Procaccia

ICML 2018 Binary Classification with Karmic, Threshold-Quasi-Concave Metrics Bowei Yan, Sanmi Koyejo, Kai Zhong, Pradeep Ravikumar

ICML 2018 Deep Density Destructors David Inouye, Pradeep Ravikumar

ICML 2018 Loss Decomposition for Fast Learning in Large Output Spaces Ian En-Hsu Yen, Satyen Kale, Felix Yu, Daniel Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar

ICML 2017 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar

AISTATS 2017 Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain Xiangru Huang, Ian En-Hsu Yen, Ruohan Zhang, Qixing Huang, Pradeep Ravikumar, Inderjit S. Dhillon

ICML 2017 Latent Feature Lasso Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar

AISTATS 2017 Minimax Gaussian Classification & Clustering Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar

ICML 2017 Ordinal Graphical Models: A Tale of Two Approaches Arun Sai Suggala, Eunho Yang, Pradeep Ravikumar

AISTATS 2017 Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition Jiong Zhang, Ian En-Hsu Yen, Pradeep Ravikumar, Inderjit S. Dhillon

ICML 2016 A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery Ian En-Hsu Yen, Xin Lin, Jiong Zhang, Pradeep Ravikumar, Inderjit Dhillon

ICML 2016 Optimal Classification with Multivariate Losses Nagarajan Natarajan, Oluwasanmi Koyejo, Pradeep Ravikumar, Inderjit Dhillon

ICML 2016 PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification Ian En-Hsu Yen, Xiangru Huang, Pradeep Ravikumar, Kai Zhong, Inderjit Dhillon

ICML 2016 Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families That Permit Positive Dependencies David Inouye, Pradeep Ravikumar, Inderjit Dhillon

ICML 2015 A Convex Exemplar-Based Approach to MAD-Bayes Dirichlet Process Mixture Models En-Hsu Yen, Xin Lin, Kai Zhong, Pradeep Ravikumar, Inderjit Dhillon

ICML 2015 Distributional Rank Aggregation, and an Axiomatic Analysis Adarsh Prasad, Harsh Pareek, Pradeep Ravikumar

JMLR 2015 Graphical Models via Univariate Exponential Family Distributions Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

AISTATS 2015 Sparsistency of 1-Regularized M-Estimators Yen-Huan Li, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher

UAI 2015 Tracking with Ranked Signals Tianyang Li, Harsh H. Pareek, Pradeep Ravikumar, Dhruv Balwada, Kevin Speer

ICML 2015 Vector-Space Markov Random Fields via Exponential Families Wesley Tansey, Oscar Hernan Madrid Padilla, Arun Sai Suggala, Pradeep Ravikumar

ICML 2014 Admixture of Poisson MRFs: A Topic Model with Word Dependencies David Inouye, Pradeep Ravikumar, Inderjit Dhillon

ICML 2014 Elementary Estimators for High-Dimensional Linear Regression Eunho Yang, Aurelie Lozano, Pradeep Ravikumar

ICML 2014 Elementary Estimators for Sparse Covariance Matrices and Other Structured Moments Eunho Yang, Aurelie Lozano, Pradeep Ravikumar

ICML 2014 Exponential Family Matrix Completion Under Structural Constraints Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh

ICML 2014 Learning Graphs with a Few Hubs Rashish Tandon, Pradeep Ravikumar

AISTATS 2014 Mixed Graphical Models via Exponential Families Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu

JMLR 2014 QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar

ICML 2013 Human Boosting Harsh Pareek, Pradeep Ravikumar

IJCAI 2013 On Robust Estimation of High Dimensional Generalized Linear Models Eunho Yang, Ambuj Tewari, Pradeep Ravikumar

AISTATS 2012 High-Dimensional Sparse Inverse Covariance Estimation Using Greedy Methods Christopher Johnson, Ali Jalali, Pradeep Ravikumar

AISTATS 2012 Perturbation Based Large Margin Approach for Ranking Eunho Yang, Ambuj Tewari, Pradeep Ravikumar

AISTATS 2011 On Learning Discrete Graphical Models Using Group-Sparse Regularization Ali Jalali, Pradeep Ravikumar, Vishvas Vasuki, Sujay Sanghavi

AISTATS 2011 On NDCG Consistency of Listwise Ranking Methods Pradeep Ravikumar, Ambuj Tewari, Eunho Yang

ICML 2011 On the Use of Variational Inference for Learning Discrete Graphical Model Eunho Yang, Pradeep Ravikumar

JMLR 2010 Message-Passing for Graph-Structured Linear Programs: Proximal Methods and Rounding Schemes Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright

ALT 2009 Error-Correcting Tournaments Alina Beygelzimer, John Langford, Pradeep Ravikumar

ICML 2008 Message-Passing for Graph-Structured Linear Programs: Proximal Projections, Convergence and Rounding Schemes Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright

ICML 2006 Quadratic Programming Relaxations for Metric Labeling and Markov Random Field MAP Estimation Pradeep Ravikumar, John D. Lafferty

UAI 2004 A Hierarchical Graphical Model for Record Linkage Pradeep Ravikumar, William W. Cohen

UAI 2004 Variational Chernoff Bounds for Graphical Models Pradeep Ravikumar, John D. Lafferty