Sanjay Shakkottai

Towards Performance Robustness for Microservices NSDI 2026 UNUM: A New Framework for Network Control NSDI 2026 Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models ICLR 2025 RB-Modulation: Training-Free Stylization using Reference-Based Modulation ICLR 2025 Semantic Image Inversion and Editing using Rectified Stochastic Differential Equations ICLR 2025 Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion CVPR 2024 In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness NeurIPS 2024 Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks ICML 2024 Beyond Uniform Smoothness: A Stopped Analysis of Adaptive SGD COLT 2023 Collaborative Multi-Agent Heterogeneous Multi-Armed Bandits ICML 2023 InfoNCE Loss Provably Learns Cluster-Preserving Representations COLT 2023 PAC Generalization via Invariant Representations ICML 2023 Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models NeurIPS 2023 Asymptotically-Optimal Gaussian Bandits with Side Observations ICML 2022 FedAvg with Fine Tuning: Local Updates Lead to Representation Learning NeurIPS 2022 Improved Algorithms for Misspecified Linear Markov Decision Processes AISTATS 2022 Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022 MAML and ANIL Provably Learn Representations ICML 2022 Minimax Regret for Cascading Bandits NeurIPS 2022 Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret NeurIPS 2022 Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation ICML 2022 The Power of Adaptivity in SGD: Self-Tuning Step Sizes with Unbounded Gradients and Affine Variance COLT 2022 Combinatorial Blocking Bandits with Stochastic Delays ICML 2021 Contextual Blocking Bandits AISTATS 2021 Exploiting Shared Representations for Personalized Federated Learning ICML 2021 Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NeurIPS 2021 Applications of Common Entropy for Causal Inference NeurIPS 2020 Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes NeurIPS 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NeurIPS 2020 Task-Robust Model-Agnostic Meta-Learning NeurIPS 2020 The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits AISTATS 2020 Blocking Bandits NeurIPS 2019 Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach AISTATS 2019 Pareto Optimal Streaming Unsupervised Classification ICML 2019 Contextual Bandits with Stochastic Experts AISTATS 2018 Multi-Fidelity Black-Box Optimization with Hierarchical Partitions ICML 2018 The Search Problem in Mixture Models JMLR 2018 Contextual Bandits with Latent Confounders: An NMF Approach AISTATS 2017 Identifying Best Interventions through Online Importance Sampling ICML 2017 Model-Powered Conditional Independence Test NeurIPS 2017 Regret of Queueing Bandits NeurIPS 2016