Ambuj Tewari

Orcid: 0000-0001-6969-7844

According to our database1, Ambuj Tewari authored at least 167 papers between 2002 and 2024.

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Bibliography

2024
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks.
CoRR, 2024

Optimal Thresholding Linear Bandit.
CoRR, 2024

The Complexity of Sequential Prediction in Dynamical Systems.
CoRR, 2024

A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Low-Rank MDPs.
CoRR, 2024

A Framework for Partially Observed Reward-States in RLHF.
CoRR, 2024

2023
Effectiveness of gamified team competition as mHealth intervention for medical interns: a cluster micro-randomized trial.
npj Digit. Medicine, 2023

Revisiting the Learnability of Apple Tasting.
CoRR, 2023

Sequence Length Independent Norm-Based Generalization Bounds for Transformers.
CoRR, 2023

Conformal Contextual Robust Optimization.
CoRR, 2023

On the Computational Complexity of Private High-dimensional Model Selection via the Exponential Mechanism.
CoRR, 2023

Online Infinite-Dimensional Regression: Learning Linear Operators.
CoRR, 2023

On the Minimax Regret in Online Ranking with Top-k Feedback.
CoRR, 2023

Multiclass Online Learnability under Bandit Feedback.
CoRR, 2023

A Combinatorial Characterization of Online Learning Games with Bounded Losses.
CoRR, 2023

A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning.
CoRR, 2023

Online Learning with Set-Valued Feedback.
CoRR, 2023

Variational Inference with Coverage Guarantees.
CoRR, 2023

A Characterization of Online Multiclass Learnability.
CoRR, 2023

Quantum Learning Theory Beyond Batch Binary Classification.
CoRR, 2023

An Asymptotically Optimal Algorithm for the One-Dimensional Convex Hull Feasibility Problem.
CoRR, 2023

A Characterization of Multilabel Learnability.
CoRR, 2023

Learning in online MDPs: is there a price for handling the communicating case?
Proceedings of the Uncertainty in Artificial Intelligence, 2023

On Proper Learnability between Average- and Worst-case Robustness.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Learnability of Multilabel Ranking.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Mixtures of Markov Chains and MDPs.
Proceedings of the International Conference on Machine Learning, 2023

Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits.
Proceedings of the International Conference on Machine Learning, 2023

Multiclass Online Learning and Uniform Convergence.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Conformer-RL: A deep reinforcement learning library for conformer generation.
J. Comput. Chem., 2022

Offline Policy Evaluation and Optimization under Confounding.
CoRR, 2022

Probabilistically Robust PAC Learning.
CoRR, 2022

Adaptive Learning for Discovery.
CoRR, 2022

Achieving Representative Data via Convex Hull Feasibility Sampling Algorithms.
CoRR, 2022

Balancing adaptability and non-exploitability in repeated games.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Adaptive Sampling for Discovery.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Agnostic Multiclass Boosting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Statistical Benefits of Curriculum Learning.
Proceedings of the International Conference on Machine Learning, 2022

Efficient Reinforcement Learning with Prior Causal Knowledge.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Weighted Gaussian Process Bandits for Non-stationary Environments.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Optimism-Based Adaptive Regulation of Linear-Quadratic Systems.
IEEE Trans. Autom. Control., 2021

Joint Learning of Linear Time-Invariant Dynamical Systems.
CoRR, 2021

Online Learning in Adversarial MDPs: Is the Communicating Case Harder than Ergodic?
CoRR, 2021

Bandit Algorithms for Precision Medicine.
CoRR, 2021

Causal Markov Decision Processes: Learning Good Interventions Efficiently.
CoRR, 2021

Thompson sampling for Markov games with piecewise stationary opponent policies.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Representation Learning Beyond Linear Prediction Functions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Causal Bandits with Unknown Graph Structure.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Low-Rank Generalized Linear Bandit Problems.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
What Does the Machine Learn? Knowledge Representations of Chemical Reactivity.
J. Chem. Inf. Model., 2020

Federated Learning via Synthetic Data.
CoRR, 2020

On Learnability under General Stochastic Processes.
CoRR, 2020

Near-optimal Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms for the Non-episodic Setting.
CoRR, 2020

On adaptive Linear-Quadratic regulators.
Autom., 2020

Input perturbations for adaptive control and learning.
Autom., 2020

What You See May Not Be What You Get: UCB Bandit Algorithms Robust to ε-Contamination.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Regret Analysis of Bandit Problems with Causal Background Knowledge.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Randomized Exploration for Non-Stationary Stochastic Linear Bandits.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

No-regret Exploration in Contextual Reinforcement Learning.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Equivalence between Online and Private Learnability beyond Binary Classification.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Finite-Time Adaptive Stabilization of Linear Systems.
IEEE Trans. Autom. Control., 2019

Learning To Predict Reaction Conditions: Relationships between Solvent, Molecular Structure, and Catalyst.
J. Chem. Inf. Model., 2019

Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits.
CoRR, 2019

Online Boosting for Multilabel Ranking with Top-k Feedback.
CoRR, 2019

Thompson Sampling in Non-Episodic Restless Bandits.
CoRR, 2019

Not All are Made Equal: Consistency of Weighted Averaging Estimators Under Active Learning.
CoRR, 2019

Regret Analysis of Causal Bandit Problems.
CoRR, 2019

Regret Bounds for Thompson Sampling in Restless Bandit Problems.
CoRR, 2019

Contextual Markov Decision Processes using Generalized Linear Models.
CoRR, 2019

On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generalization Bounds in the Predict-then-Optimize Framework.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Learning via the Differential Privacy Lens.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems.
Proceedings of the IEEE Data Science Workshop, 2019

On Applications of Bootstrap in Continuous Space Reinforcement Learning.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Online Multiclass Boosting with Bandit Feedback.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Sampled fictitious play is Hannan consistent.
Games Econ. Behav., 2018

Input Perturbations for Adaptive Regulation and Learning.
CoRR, 2018

Random ReLU Features: Universality, Approximation, and Composition.
CoRR, 2018

Finite Time Adaptive Stabilization of LQ Systems.
CoRR, 2018

On Optimality of Adaptive Linear-Quadratic Regulators.
CoRR, 2018

Finite time identification in unstable linear systems.
Autom., 2018

But How Does It Work in Theory? Linear SVM with Random Features.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Active Learning for Non-Parametric Regression Using Purely Random Trees.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Markov Decision Processes with Continuous Side Information.
Proceedings of the Algorithmic Learning Theory, 2018

Online Boosting Algorithms for Multi-label Ranking.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Partial Hard Thresholding.
IEEE Trans. Inf. Theory, 2017

Optimality of Fast-Matching Algorithms for Random Networks With Applications to Structural Controllability.
IEEE Trans. Control. Netw. Syst., 2017

Cost-Sensitive Learning with Noisy Labels.
J. Mach. Learn. Res., 2017

Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits.
J. Mach. Learn. Res., 2017

Online Learning to Rank with Top-k Feedback.
J. Mach. Learn. Res., 2017

Online Learning via Differential Privacy.
CoRR, 2017

Finite Time Analysis of Optimal Adaptive Policies for Linear-Quadratic Systems.
CoRR, 2017

An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions.
CoRR, 2017

Online Multiclass Boosting.
CoRR, 2017

Online multiclass boosting.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Action Centered Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

From Ads to Interventions: Contextual Bandits in Mobile Health.
Proceedings of the Mobile Health - Sensors, Analytic Methods, and Applications, 2017

2016
Regularized Estimation in High Dimensional Time Series under Mixing Conditions.
CoRR, 2016

Mixture Proportion Estimation via Kernel Embedding of Distributions.
CoRR, 2016

Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

On Structural Properties of MDPs that Bound Loss Due to Shallow Planning.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Mixture Proportion Estimation via Kernel Embeddings of Distributions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Online Learning to Rank with Feedback at the Top.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Handling Class Imbalance in Link Prediction Using Learning to Rank Techniques.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Online learning via sequential complexities.
J. Mach. Learn. Res., 2015

Consistent Algorithms for Multiclass Classification with a Reject Option.
CoRR, 2015

Perceptron like Algorithms for Online Learning to Rank.
CoRR, 2015

Alternating Minimization for Regression Problems with Vector-valued Outputs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Predtron: A Family of Online Algorithms for General Prediction Problems.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fighting Bandits with a New Kind of Smoothness.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Generalization error bounds for learning to rank: Does the length of document lists matter?
Proceedings of the 32nd International Conference on Machine Learning, 2015

Convex Calibrated Surrogates for Hierarchical Classification.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Online Ranking with Top-1 Feedback.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Prediction and clustering in signed networks: a local to global perspective.
J. Mach. Learn. Res., 2014

Perceptron-like Algorithms and Generalization Bounds for Learning to Rank.
CoRR, 2014

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Online Linear Optimization via Smoothing.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
On the Nonasymptotic Convergence of Cyclic Coordinate Descent Methods.
SIAM J. Optim., 2013

Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Learning with Noisy Labels.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On Robust Estimation of High Dimensional Generalized Linear Models.
Proceedings of the IJCAI 2013, 2013

2012
Perturbation based Large Margin Approach for Ranking.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Regularization Techniques for Learning with Matrices.
J. Mach. Learn. Res., 2012

The Interplay Between Stability and Regret in Online Learning
CoRR, 2012

Deterministic MDPs with Adversarial Rewards and Bandit Feedback.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Parallelizing ListNet training using spark.
Proceedings of the 35th International ACM SIGIR conference on research and development in Information Retrieval, 2012

Feature Clustering for Accelerating Parallel Coordinate Descent.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Scaling Up Coordinate Descent Algorithms for Large <i>ℓ<sub>1</sub></i> Regularization Problems.
Proceedings of the 29th International Conference on Machine Learning, 2012

PAC Subset Selection in Stochastic Multi-armed Bandits.
Proceedings of the 29th International Conference on Machine Learning, 2012

Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Stochastic Methods for <i>l</i><sub>1</sub>-regularized Loss Minimization.
J. Mach. Learn. Res., 2011

Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

On NDCG Consistency of Listwise Ranking Methods.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Online Learning: Beyond Regret.
Proceedings of the COLT 2011, 2011

Complexity-Based Approach to Calibration with Checking Rules.
Proceedings of the COLT 2011, 2011

Online Learning: Stochastic and Constrained Adversaries
CoRR, 2011

Greedy Algorithms for Structurally Constrained High Dimensional Problems.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

On the Universality of Online Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Online Learning: Stochastic, Constrained, and Smoothed Adversaries.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Orthogonal Matching Pursuit with Replacement.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Nearest Neighbor based Greedy Coordinate Descent.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Exploiting longer cycles for link prediction in signed networks.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

On the Finite Time Convergence of Cyclic Coordinate Descent Methods
CoRR, 2010

Smoothness, Low Noise and Fast Rates.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Online Learning: Random Averages, Combinatorial Parameters, and Learnability.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Convex Games in Banach Spaces.
Proceedings of the COLT 2010, 2010

Composite Objective Mirror Descent.
Proceedings of the COLT 2010, 2010

2009
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity
CoRR, 2009

Applications of strong convexity--strong smoothness duality to learning with matrices
CoRR, 2009

REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs.
Proceedings of the UAI 2009, 2009

2008
On the Generalization Ability of Online Strongly Convex Programming Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Efficient bandit algorithms for online multiclass prediction.
Proceedings of the Machine Learning, 2008

High-Probability Regret Bounds for Bandit Online Linear Optimization.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Optimal Stragies and Minimax Lower Bounds for Online Convex Games.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

2007
On the Consistency of Multiclass Classification Methods.
J. Mach. Learn. Res., 2007

Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results.
J. Mach. Learn. Res., 2007

Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Bounded Parameter Markov Decision Processes with Average Reward Criterion.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Sample Complexity of Policy Search with Known Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2004
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2002
A Parallel DFA Minimization Algorithm.
Proceedings of the High Performance Computing, 2002


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