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Ambuj Tewari

103 papers · 2006–2026 · 11 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 25 separate collaboration groups - the largest holds only 22% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Ambuj Tewari?

12 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Ziping Xu, Young Hun Jung, Amirhossein Meisami 23 papers · 2014–2025 · NeurIPS, AISTATS, ICML Hide ▲
A Theoretical Framework for Partially-Observed Reward States in RLHF ICLR 2025 Leveraging Offline Data in Linear Latent Contextual Bandits ICML 2025 Offline Policy Evaluation and Optimization Under Confounding AISTATS 2024 Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks ICLR 2024 Learning Mixtures of Markov Chains and MDPs ICML 2023 Adaptive Sampling for Discovery NeurIPS 2022 Efficient Reinforcement Learning with Prior Causal Knowledge CLeaR 2022 On the Statistical Benefits of Curriculum Learning ICML 2022 Causal Bandits with Unknown Graph Structure NeurIPS 2021 Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns AISTATS 2021 Low-Rank Generalized Linear Bandit Problems AISTATS 2021 Representation Learning Beyond Linear Prediction Functions NeurIPS 2021 Regret Analysis of Bandit Problems with Causal Background Knowledge UAI 2020 Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting NeurIPS 2020 TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search NeurIPS 2020 Online Learning via the Differential Privacy Lens NeurIPS 2019 Online Multiclass Boosting with Bandit Feedback AISTATS 2019 Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems NeurIPS 2019 Active Learning for Non-Parametric Regression Using Purely Random Trees NeurIPS 2018 Online Boosting Algorithms for Multi-label Ranking AISTATS 2018 Online multiclass boosting NeurIPS 2017 Fighting Bandits with a New Kind of Smoothness NeurIPS 2015 Online Linear Optimization via Smoothing COLT 2014
13 papers whose co-authors appear nowhere else under this name
A Characterization of List Language Identification in the Limit COLT 2026 Conformal Contextual Robust Optimization AISTATS 2024 Sequence Length Independent Norm-Based Generalization Bounds for Transformers AISTATS 2024 Variational Inference with Coverage Guarantees in Simulation-Based Inference ICML 2024 Learning in online MDPs: is there a price for handling the communicating case? UAI 2023 What You See May Not Be What You Get: UCB Bandit Algorithms Robust to ε-Contamination UAI 2020 Generalization Bounds in the Predict-then-Optimize Framework NeurIPS 2019 Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits JMLR 2018 But How Does It Work in Theory? Linear SVM with Random Features NeurIPS 2018 Action Centered Contextual Bandits NeurIPS 2017 Feature Clustering for Accelerating Parallel Coordinate Descent NeurIPS 2012 Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011 Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010

Venues · all papers under this name

NeurIPS (39) AISTATS (18) ICML (11) JMLR (10) COLT (8) UAI (7) ALT (4) ICLR (2) IJCAI (2) CLeaR (1) L4DC (1)