Ambuj Tewari

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Action Centered Contextual Bandits

Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, 2017, NIPS.

Bounded Parameter Markov Decision Processes with Average Reward Criterion

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2007, COLT.

Generalization Bounds in the Predict-then-Optimize Framework

Ambuj Tewari, Othman El Balghiti, Adam N. Elmachtoub, 2019, NeurIPS.

Online Ranking with Top-1 Feedback pdf

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2014, AISTATS.

On Robust Estimation of High Dimensional Generalized Linear Models

Pradeep Ravikumar, Ambuj Tewari, Eunho Yang, 2013, IJCAI.

Near-optimal Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms for the Non-episodic Setting pdf

Ambuj Tewari, Ziping Xu, Ambuj Tewari, 2020, ArXiv.

Learning To Predict Reaction Conditions: Relationships between Solvent, Molecular Structure, and Catalyst

Ambuj Tewari, Eric Walker, Joshua Andrew Kammeraad, 2019, J. Chem. Inf. Model..

Linear Optimization through the Differential Privacy Lens

Jacob Abernethy, Ambuj Tewari, Jacob D. Abernethy, 2018 .

Thompson Sampling in Non-Episodic Restless Bandits pdf

Ambuj Tewari, Young Hun Jung, Marc Abeille, 2019, ArXiv.

On the Nonasymptotic Convergence of Cyclic Coordinate Descent Methods

Ambuj Tewari, Ankan Saha, Ambuj Tewari, 2013, SIAM J. Optim..

On Lipschitz Continuity and Smoothness of Loss Functions in Learning to Rank pdf

Ambuj Tewari, Sougata Chaudhuri, 2014, ArXiv.

Near-optimal Oracle-efficient Algorithms for Stationary and Non-Stationary Stochastic Linear Bandits pdf

Ambuj Tewari, Baekjin Kim, 2019, ArXiv.

Online Learning via Differential Privacy pdf

Ambuj Tewari, Jacob D. Abernethy, Chansoo Lee, 2017, ArXiv.

Online Learning: Random Averages, Combinatorial Parameters, and Learnability

Ambuj Tewari, Karthik Sridharan, Alexander Rakhlin, 2010, NIPS.

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

Prateek Jain, Ambuj Tewari, Purushottam Kar, 2014, NIPS.

Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret

Ambuj Tewari, Raman Arora, Ofer Dekel, 2012, ICML.

Random ReLU Features: Universality, Approximation, and Composition pdf

Ambuj Tewari, Anna C. Gilbert, Yitong Sun, 2018, ArXiv.

Chapter 14 - Learning Theory

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2014 .

Exploiting longer cycles for link prediction in signed networks

Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari, 2011, CIKM '11.

Illustration of the trainer

Ambuj Tewari, 2013 .

On Applications of Bootstrap in Continuous Space Reinforcement Learning

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Not All are Made Equal: Consistency of Weighted Averaging Estimators Under Active Learning pdf

Ambuj Tewari, Jack Goetz, 2019, ArXiv.

What You See May Not Be What You Get: UCB Bandit Algorithms Robust to ε-Contamination

Ambuj Tewari, Laura Niss, 2020, UAI.

PAC Subset Selection in Stochastic Multi-armed Bandits

Ambuj Tewari, Peter Stone, Peter Auer, 2012, ICML.

A Parallel DFA Minimization Algorithm

Ambuj Tewari, P. Gupta, Utkarsh Srivastava, 2002, HiPC.

Predtron: A Family of Online Algorithms for General Prediction Problems

Nagarajan Natarajan, Prateek Jain, Ambuj Tewari, 2015, NIPS.

Regret Analysis of Bandit Problems with Causal Background Knowledge

Ambuj Tewari, Amirhossein Meisami, Yangyi Lu, 2019, UAI.

On adaptive Linear-Quadratic regulators

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2020, Autom..

Markov Decision Processes with Continuous Side Information

Nan Jiang, Ambuj Tewari, Satinder P. Singh, 2017, ALT.

Online Learning via the Differential Privacy Lens

Jacob Abernethy, Ambuj Tewari, Chansoo Lee, 2019, NeurIPS.

Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems

Ambuj Tewari, Young Hun Jung, 2019, NeurIPS.

Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2007, NIPS.

High-Probability Regret Bounds for Bandit Online Linear Optimization

Thomas P. Hayes, Ambuj Tewari, Peter L. Bartlett, 2008, COLT.

Efficient bandit algorithms for online multiclass prediction

Ambuj Tewari, Sham M. Kakade, Shai Shalev-Shwartz, 2008, ICML '08.

But How Does It Work in Theory? Linear SVM with Random Features

Ambuj Tewari, Anna C. Gilbert, Yitong Sun, 2018, NeurIPS.

On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization

Ambuj Tewari, Sham M. Kakade, Karthik Sridharan, 2008, NIPS.

Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support

Ambuj Tewari, Susan A. Murphy, Inbal Nahum-Shani, 2017, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions pdf

Ambuj Tewari, Susan A. Murphy, Huitian Lei, 2017, ArXiv.

Applications of strong convexity--strong smoothness duality to learning with matrices pdf

Ambuj Tewari, Sham M. Kakade, Shai Shalev-Shwartz, 2009, ArXiv.

Input perturbations for adaptive control and learning

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2018, Autom..

REGAL: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating MDPs

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2009, UAI.

Parallelizing ListNet training using spark

Matthew Lease, Ambuj Tewari, Shilpa Shukla, 2012, SIGIR '12.

Spectral Smoothing via Random Matrix Perturbations pdf

Jacob Abernethy, Ambuj Tewari, Chansoo Lee, 2015, ArXiv.

TorsionNet: A Reinforcement Learning Approach to Sequential Conformer Search pdf

Ambuj Tewari, Joshua Kammeraad, Ziping Xu, 2020, NeurIPS.

Fighting Contextual Bandits with Stochastic Smoothing pdf

Ambuj Tewari, Young Hun Jung, Ambuj Tewari, 2018, ArXiv.

Contextual Markov Decision Processes using Generalized Linear Models pdf

Ambuj Tewari, Aditya Modi, Ambuj Tewari, 2019, ArXiv.

Cost-Sensitive Learning with Noisy Labels

Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon, 2017, J. Mach. Learn. Res..

Online Multiclass Boosting with Bandit Feedback pdf

Ambuj Tewari, Young Hun Jung, Daniel T. Zhang, 2018, AISTATS.

Online Boosting Algorithms for Multi-label Ranking

Ambuj Tewari, Young Hun Jung, Ambuj Tewari, 2017, AISTATS.

Alternating Minimization for Regression Problems with Vector-valued Outputs

Prateek Jain, Ambuj Tewari, 2015, NIPS.

Perceptron like Algorithms for Online Learning to Rank pdf

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2015, ArXiv.

Online learning via sequential complexities

Ambuj Tewari, Karthik Sridharan, Alexander Rakhlin, 2010, J. Mach. Learn. Res..

On the Universality of Online Mirror Descent

Ambuj Tewari, Nathan Srebro, Karthik Sridharan, 2011, NIPS.

Optimal Stragies and Minimax Lower Bounds for Online Convex Games

Ambuj Tewari, Peter L. Bartlett, Jacob D. Abernethy, 2008, COLT.

98 Feasibility and acceptability of using a mobile phone app to assess substance use among adolescents and emerging adults

Ambuj Tewari, Susan A. Murphy, Inbal Nahum-Shani, 2017, Injury Prevention.

Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns pdf

Ambuj Tewari, Ziping Xu, Amir Meisami, 2020, ArXiv.

On the Finite Time Convergence of Cyclic Coordinate Descent Methods pdf

Ambuj Tewari, Ankan Saha, Ambuj Tewari, 2010, ArXiv.

Learning with Noisy Labels

Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon, 2013, NIPS.

Orthogonal Matching Pursuit with Replacement

Inderjit S. Dhillon, Prateek Jain, Ambuj Tewari, 2011, NIPS.

Fighting Bandits with a New Kind of Smoothness

Ambuj Tewari, Jacob D. Abernethy, Chansoo Lee, 2015, NIPS.

On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems

Ambuj Tewari, Baekjin Kim, Ambuj Tewari, 2019, NeurIPS.

Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

Ambuj Tewari, Satinder Singh, Nan Jiang, 2019, AISTATS.

Greedy Algorithms for Structurally Constrained High Dimensional Problems

Pradeep Ravikumar, Inderjit S. Dhillon, Ambuj Tewari, 2011, NIPS.

Generalization error bounds for learning to rank: Does the length of document lists matter?

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2015, ICML.

On Optimality of Adaptive Linear-Quadratic Regulators pdf

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2018, ArXiv.

The Interplay Between Stability and Regret in Online Learning pdf

Prateek Jain, Ambuj Tewari, Ankan Saha, 2012, ArXiv.

Optimizing mHealth Interventions with a Bandit

Ambuj Tewari, Predrag Klasnja, Mashfiqui Rabbi, 2019, Studies in Neuroscience, Psychology and Behavioral Economics.

Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses

Ambuj Tewari, Shivani Agarwal, Harish G. Ramaswamy, 2013, NIPS.

No-regret Exploration in Contextual Reinforcement Learning

Ambuj Tewari, Aditya Modi, Ambuj Tewari, 2019, UAI.

Mixture Proportion Estimation via Kernel Embeddings of Distributions pdf

Ambuj Tewari, Clayton Scott, Harish G. Ramaswamy, 2016, ICML.

Low-Rank Generalized Linear Bandit Problems pdf

Ambuj Tewari, Amirhossein Meisami, Yangyi Lu, 2020, AISTATS.

Online Learning: Stochastic, Constrained, and Smoothed Adversaries

Ambuj Tewari, Karthik Sridharan, Alexander Rakhlin, 2011, NIPS.

Optimism-Based Adaptive Regulation of Linear-Quadratic Systems

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2017, IEEE Transactions on Automatic Control.

Sample Complexity of Policy Search with Known Dynamics

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2006, NIPS.

Finite Time Identification in Unstable Linear Systems pdf

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2017, Autom..

Handling Class Imbalance in Link Prediction Using Learning to Rank Techniques pdf

Ambuj Tewari, Sougata Chaudhuri, Bopeng Li, 2015, AAAI.

Lasso Guarantees for Time Series Estimation Under Subgaussian Tails and $ \beta $-Mixing

Ambuj Tewari, Zifan Li, Kam Chung Wong, 2016 .

On the Generalization Ability of Online Strongly Convex Programming Algorithms

Ambuj Tewari, Sham M. Kakade, S. Kakade, 2008, NIPS.

Finite Time Adaptive Stabilization of LQ Systems

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2018, ArXiv.

From Ads to Interventions: Contextual Bandits in Mobile Health

Ambuj Tewari, Susan A. Murphy, Ambuj Tewari, 2017, Mobile Health - Sensors, Analytic Methods, and Applications.

Finite Time Analysis of Optimal Adaptive Policies for Linear-Quadratic Systems pdf

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2017, ArXiv.

Regret Bounds for Thompson Sampling in Restless Bandit Problems pdf

Ambuj Tewari, Young Hun Jung, 2019, NeurIPS 2019.

Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear Systems

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2019, 2019 IEEE Data Science Workshop (DSW).

Online Learning to Rank with Feedback at the Top

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2016, AISTATS.

Online Learning: Beyond Regret

Ambuj Tewari, Karthik Sridharan, Alexander Rakhlin, 2010, COLT.

Online Learning to Rank with Top-k Feedback

Ambuj Tewari, Sougata Chaudhuri, 2017, J. Mach. Learn. Res..

Input Perturbations for Adaptive Regulation and Learning pdf

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2018, ArXiv.

Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback

Ambuj Tewari, Ankan Saha, Ambuj Tewari, 2011, AISTATS.

Perturbation based Large Margin Approach for Ranking

Pradeep Ravikumar, Ambuj Tewari, Eunho Yang, 2012, AISTATS.

Consistent Algorithms for Multiclass Classification with a Reject Option pdf

Ambuj Tewari, Shivani Agarwal, Harish G. Ramaswamy, 2015, ArXiv.

Active Learning for Non-Parametric Regression Using Purely Random Trees

Ambuj Tewari, Paul Zimmerman, Jack Goetz, 2018, NeurIPS.

Online Linear Optimization via Smoothing pdf

Ambuj Tewari, Abhinav Sinha, Jacob D. Abernethy, 2014, COLT.

Convex Calibrated Surrogates for Hierarchical Classification

Ambuj Tewari, Shivani Agarwal, Harish G. Ramaswamy, 2015, ICML.

Predicting Gene-Disease Associations Using Multiple Species Data

Nagarajan Natarajan, Inderjit S. Dhillon, Ambuj Tewari, 2011 .

Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic Setting

Ambuj Tewari, Ziping Xu, 2020, NeurIPS.

Regret Analysis of Causal Bandit Problems pdf

Ambuj Tewari, Zhenyu Yan, Amirhossein Meisami, 2019, ArXiv.

On the Consistency of Multiclass Classification Methods

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2007, J. Mach. Learn. Res..

Composite objective mirror descent

Ambuj Tewari, Yoram Singer, Shai Shalev-Shwartz, 2010, COLT 2010.

Randomized Exploration for Non-Stationary Stochastic Linear Bandits

Ambuj Tewari, Baekjin Kim, 2020, UAI.

Regularized Estimation in High Dimensional Time Series under Mixing Conditions pdf

Ambuj Tewari, Zifan Li, Kam Chung Wong, 2016, ArXiv.

What Does the Machine Learn? Knowledge Representations of Chemical Reactivity

Ambuj Tewari, Joshua Andrew Kammeraad, Paul M Zimmerman, 2020, J. Chem. Inf. Model..

Partial Hard Thresholding

Inderjit S. Dhillon, Ambuj Tewari, Prateek Jain, 2017, IEEE Transactions on Information Theory.

Smoothness, Low Noise and Fast Rates

Ambuj Tewari, Nathan Srebro, Karthik Sridharan, 2010, NIPS.

Complexity-Based Approach to Calibration with Checking Rules

Ambuj Tewari, Dean P. Foster, Karthik Sridharan, 2011, COLT.

Nearest Neighbor based Greedy Coordinate Descent

Pradeep Ravikumar, Inderjit S. Dhillon, Ambuj Tewari, 2011, NIPS.

Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems

Ambuj Tewari, Mahantesh Halappanavar, Chad Scherrer, 2012, ICML.

On NDCG Consistency of Listwise Ranking Methods

Pradeep Ravikumar, Ambuj Tewari, Eunho Yang, 2011, AISTATS.

On Structural Properties of MDPs that Bound Loss Due to Shallow Planning

Nan Jiang, Ambuj Tewari, Satinder P. Singh, 2016, IJCAI.

Reinforcement learning in large or unknown mdps

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2007 .

On the Approximation Capabilities of ReLU Neural Networks and Random ReLU Features

Ambuj Tewari, Yitong Sun, Anna Gilbert, 2018 .

Optimality of Fast-Matching Algorithms for Random Networks With Applications to Structural Controllability

Ambuj Tewari, George Michailidis, Mohamad Kazem Shirani Faradonbeh, 2015, IEEE Transactions on Control of Network Systems.

Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits pdf

Ambuj Tewari, Zifan Li, 2017, J. Mach. Learn. Res..

Online Learning: Stochastic and Constrained Adversaries pdf

Ambuj Tewari, Karthik Sridharan, Alexander Rakhlin, 2011, ArXiv.

On Learnability under General Stochastic Processes pdf

Ambuj Tewari, A. Philip Dawid, Ambuj Tewari, 2020, ArXiv.

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

Ambuj Tewari, Ohad Shamir, Sham M. Kakade, 2009, AISTATS.

Feature Clustering for Accelerating Parallel Coordinate Descent

Ambuj Tewari, Mahantesh Halappanavar, Chad Scherrer, 2012, NIPS.

Online Boosting for Multilabel Ranking with Top-k Feedback pdf

Ambuj Tewari, Young Hun Jung, Daniel T. Zhang, 2019, ArXiv.

Online multiclass boosting

Ambuj Tewari, Young Hun Jung, Jack Goetz, 2017, NIPS.

Regularization Techniques for Learning with Matrices

Ambuj Tewari, Sham M. Kakade, Shai Shalev-Shwartz, 2009, J. Mach. Learn. Res..

Perceptron-like Algorithms and Generalization Bounds for Learning to Rank pdf

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2014, ArXiv.

Stochastic methods for l1 regularized loss minimization

Ambuj Tewari, Shai Shalev-Shwartz, S. Shalev-Shwartz, 2009, ICML '09.

Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games

Ambuj Tewari, Sougata Chaudhuri, Ambuj Tewari, 2016, NIPS.

Federated Learning via Synthetic Data

Ambuj Tewari, Jack Goetz, Ambuj Tewari, 2020, 2008.04489.

On the Equivalence between Online and Private Learnability beyond Binary Classification pdf

Ambuj Tewari, Young Hun Jung, Baekjin Kim, 2020, NeurIPS.

What You See May Not Be What You Get: UCB Bandit Algorithms Robust to {\epsilon}-Contamination

Ambuj Tewari, Laura Niss, 2019 .

Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results

Ambuj Tewari, Peter L. Bartlett, P. Bartlett, 2007, J. Mach. Learn. Res..

Sample size calculations for micro‐randomized trials in mHealth

Ambuj Tewari, Predrag Klasnja, Susan A Murphy, 2015, Statistics in medicine.

Prediction and clustering in signed networks: a local to global perspective pdf

Nagarajan Natarajan, Inderjit S. Dhillon, Cho-Jui Hsieh, 2013, J. Mach. Learn. Res..

Sampled Fictitious Play is Hannan Consistent

Ambuj Tewari, Zifan Li, Ambuj Tewari, 2016, Games Econ. Behav..

Deterministic MDPs with Adversarial Rewards and Bandit Feedback

Ambuj Tewari, Raman Arora, Ofer Dekel, 2012, UAI.

Online Learning in Adversarial MDPs: Is the Communicating Case Harder than Ergodic? pdf

Ambuj Tewari, Gautam Chandrasekaran, Ambuj Tewari, 2021, ArXiv.

Learning From Others Without Sacrificing Privacy: Simulation Comparing Centralized and Federated Machine Learning on Mobile Health Data

Ambuj Tewari, Jack Goetz, Jessica Chia Liu, 2021, JMIR mHealth and uHealth.

Weighted Gaussian Process Bandits for Non-stationary Environments pdf

Ambuj Tewari, Ness Shroff, Baekjin Kim, 2021, ArXiv.

Thompson sampling for Markov games with piecewise stationary opponent policies

Ambuj Tewari, Anthony DiGiovanni, Ambuj Tewari, 2021, UAI.

Causal Bandits with Unknown Graph Structure pdf

Ambuj Tewari, Amirhossein Meisami, Yangyi Lu, 2021, NeurIPS.

Balancing Adaptability and Non-exploitability in Repeated Games pdf

Ambuj Tewari, Anthony DiGiovanni, 2021, ArXiv.

Joint Learning of Linear Time-Invariant Dynamical Systems pdf

Ambuj Tewari, George Michailidis, Aditya Modi, 2021, ArXiv.

On the Statistical Benefits of Curriculum Learning pdf

Ambuj Tewari, Ziping Xu, 2021, ArXiv.

Causal Markov Decision Processes: Learning Good Interventions Efficiently pdf

Ambuj Tewari, Amirhossein Meisami, Yangyi Lu, 2021, ArXiv.

Bandit Algorithms for Precision Medicine pdf

Ambuj Tewari, Ziping Xu, Yangyi Lu, 2021, ArXiv.

Representation Learning Beyond Linear Prediction Functions pdf

Ambuj Tewari, Ziping Xu, 2021, ArXiv.

High-dimensional variable selection with heterogeneous signals: A precise asymptotic perspective

Ambuj Tewari, Ziwei Zhu, Saptarshi Roy, 2022 .

Exponentiated) Stochastic Gradient Descent for L1 Constrained Problems

Ambuj Tewari, Sham M. Kakade, S. Kakade, 2008 .

No-regret Exploration in Contextual Reinforcement Learning

Ambuj Tewari, Aditya Modi, 2020, UAI.

On the Equivalence between Online and Private Learnability beyond Binary Classification pdf

Ambuj Tewari, Young Hun Jung, Baekjin Kim, 2020, NeurIPS.

On the Approximation Properties of Random ReLU Features

Ambuj Tewari, Anna Gilbert, Yitong Sun, 2018 .