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Author search results
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- Pradeep Ravikumar
aka: Pradeep Kumar Ravikumar
University of Texas in Austin, Department of Computer Science, USA
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Publication search results
found 242 matches
- 2024
- Runtian Zhai, Rattana Pukdee, Roger Jin, Maria-Florina Balcan, Pradeep Ravikumar:
Spectrally Transformed Kernel Regression. CoRR abs/2402.00645 (2024) - Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models. CoRR abs/2402.09236 (2024) - Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam, Victor Veitch:
On the Origins of Linear Representations in Large Language Models. CoRR abs/2403.03867 (2024) - 2023
- Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar:
Faith-Shap: The Faithful Shapley Interaction Index. J. Mach. Learn. Res. 24: 94:1-94:42 (2023) - Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar, Hongyang Zhang:
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games. AISTATS 2023: 9607-9636 - Wenbin Zhang, Zichong Wang, Juyong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy C. Weiss:
Individual Fairness Under Uncertainty. ECAI 2023: 3042-3049 - Andrew Bai, Chih-Kuan Yeh, Neil Y. C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh:
Concept Gradient: Concept-based Interpretation Without Linear Assumption. ICLR 2023 - Rattana Pukdee, Dylan Sam, Pradeep Kumar Ravikumar, Nina Balcan:
Label Propagation with Weak Supervision. ICLR 2023 - Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Kumar Ravikumar:
Understanding Why Generalized Reweighting Does Not Improve Over ERM. ICLR 2023 - Chang Deng, Kevin Bello, Bryon Aragam, Pradeep Kumar Ravikumar:
Optimizing NOTEARS Objectives via Topological Swaps. ICML 2023: 7563-7595 - Che-Ping Tsai, Jiong Zhang, Hsiang-Fu Yu, Eli Chien, Cho-Jui Hsieh, Pradeep Kumar Ravikumar:
Representer Point Selection for Explaining Regularized High-dimensional Models. ICML 2023: 34469-34490 - Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. NeurIPS 2023 - Tianyu Chen, Kevin Bello, Bryon Aragam, Pradeep Ravikumar:
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models. NeurIPS 2023 - Chang Deng, Kevin Bello, Pradeep Ravikumar, Bryon Aragam:
Global Optimality in Bivariate Gradient-based DAG Learning. NeurIPS 2023 - Yash Gupta, Runtian Zhai, Arun Sai Suggala, Pradeep Ravikumar:
Responsible AI (RAI) Games and Ensembles. NeurIPS 2023 - Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar:
Learning with Explanation Constraints. NeurIPS 2023 - Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar:
Sample based Explanations via Generalized Representers. NeurIPS 2023 - Bryon Aragam, Pradeep Ravikumar:
Neuro-Causal Models. Compendium of Neurosymbolic Artificial Intelligence 2023: 153-177 - Wenbin Zhang, Juyong Kim, Zichong Wang, Pradeep Ravikumar, Jeremy C. Weiss:
Individual Fairness Guarantee in Learning with Censorship. CoRR abs/2302.08015 (2023) - Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar:
Learning with Explanation Constraints. CoRR abs/2303.14496 (2023) - Chang Deng, Kevin Bello, Bryon Aragam, Pradeep Ravikumar:
Optimizing NOTEARS Objectives via Topological Swaps. CoRR abs/2305.17277 (2023) - Che-Ping Tsai, Jiong Zhang, Eli Chien, Hsiang-Fu Yu, Cho-Jui Hsieh, Pradeep Ravikumar:
Representer Point Selection for Explaining Regularized High-dimensional Models. CoRR abs/2305.20002 (2023) - Runtian Zhai, Bingbin Liu, Andrej Risteski, Zico Kolter, Pradeep Ravikumar:
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation. CoRR abs/2306.00788 (2023) - Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar:
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing. CoRR abs/2306.02235 (2023) - Tianyu Chen, Kevin Bello, Bryon Aragam, Pradeep Ravikumar:
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models. CoRR abs/2306.17361 (2023) - Chang Deng, Kevin Bello, Bryon Aragam, Pradeep Ravikumar:
Global Optimality in Bivariate Gradient-based DAG Learning. CoRR abs/2306.17378 (2023) - Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Ravikumar, Niklas Pfister, Jonas Peters:
Identifying Representations for Intervention Extrapolation. CoRR abs/2310.04295 (2023) - Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar:
Sample based Explanations via Generalized Representers. CoRR abs/2310.18526 (2023) - Yash Gupta, Runtian Zhai, Arun Sai Suggala, Pradeep Ravikumar:
Responsible AI (RAI) Games and Ensembles. CoRR abs/2310.18832 (2023) - Goutham Rajendran, Patrik Reizinger, Wieland Brendel, Pradeep Ravikumar:
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis. CoRR abs/2311.18048 (2023)
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