Raman Arora

Backdoor Attacks in Token Selection of Attention Mechanism ICML 2025 Policy-Regret Minimization in Markov Games with Function Approximation ICML 2025 Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates ALT 2024 On The Statistical Complexity of Offline Decision-Making ICML 2024 Adversarially Robust Multi-task Representation Learning NIPS 2024 On the Stability and Generalization of Meta-Learning NIPS 2024 Adversarially Robust Hypothesis Transfer Learning ICML 2024 Offline Multitask Representation Learning for Reinforcement Learning NIPS 2024 Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms NIPS 2024 Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation NIPS 2024 Public-data Assisted Private Stochastic Optimization: Power and Limitations NIPS 2024 Benign Overfitting in Adversarial Training of Neural Networks ICML 2024 On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond NIPS 2023 VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation ICLR 2023 Optimistic Rates for Multi-Task Representation Learning NIPS 2023 Robustness Guarantees for Adversarially Trained Neural Networks NIPS 2023 Multi-Agent Learning with Heterogeneous Linear Contextual Bandits NIPS 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation AAAI 2023 A Risk-Sensitive Approach to Policy Optimization AAAI 2023 From Adaptive Query Release to Machine Unlearning ICML 2023 Faster Rates of Convergence to Stationary Points in Differentially Private Optimization ICML 2023 Adversarial Robustness is at Odds with Lazy Training NIPS 2022 Differentially Private Generalized Linear Models Revisited NIPS 2022 Machine Unlearning via Algorithmic Stability COLT 2021 Corralling Stochastic Bandit Algorithms AISTATS 2021 Differentially Private Analysis on Graph Streams AISTATS 2021 Dropout: Explicit Forms and Capacity Control ICML 2021 Robust Learning for Data Poisoning Attacks ICML 2021 FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020 On Convergence and Generalization of Dropout Training NIPS 2020 Adversarial Robustness of Supervised Sparse Coding NIPS 2020 On Differentially Private Graph Sparsification and Applications NIPS 2019 On Dropout and Nuclear Norm Regularization ICML 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019 Communication-efficient Distributed SGD with Sketching NIPS 2019 Bandits with Feedback Graphs and Switching Costs NIPS 2019 Efficient Convex Relaxations for Streaming PCA NIPS 2019 Deep Generalized Canonical Correlation Analysis ACL 2019 Differentially Private Robust Low-Rank Approximation NIPS 2018 The Physical Systems Behind Optimization Algorithms NIPS 2018 Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features NIPS 2018 Policy Regret in Repeated Games NIPS 2018 Understanding Deep Neural Networks with Rectified Linear Units ICLR 2018 Streaming Principal Component Analysis in Noisy Setting ICML 2018 Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization ICML 2018 On the Implicit Bias of Dropout ICML 2018 On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization JMLR 2018 Stochastic Approximation for Canonical Correlation Analysis NIPS 2017 A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion INTERSPEECH 2017 Embedding Lexical Features via Low-Rank Tensors NAACL 2016 An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization AISTATS 2016 Learning Multiview Embeddings of Twitter Users ACL 2016 Disease Trajectory Maps NIPS 2016 Stochastic Optimization for Multiview Representation Learning using Partial Least Squares ICML 2016 Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning ICML 2016 On Deep Multi-View Representation Learning ICML 2015 Multiview LSA: Representation Learning via Generalized CCA NAACL 2015 Accelerated Mini-batch Randomized Block Coordinate Descent Method NIPS 2014 Robust Stochastic Principal Component Analysis AISTATS 2014 Deep Canonical Correlation Analysis ICML 2013 Stochastic Optimization of PCA with Capped MSG NIPS 2013 Similarity-based Clustering by Left-Stochastic Matrix Factorization JMLR 2013 Consensus Ranking with Signed Permutations AISTATS 2013 On Learning Rotations NIPS 2009