On Addressing Efficiency Concerns in Privacy Preserving Data Mining - Shipra Agrawal 001; Vijay Krishnan; Jayant R. Haritsa (CoRR, 2003)

On Addressing Efficiency Concerns in Privacy-Preserving Mining. - Shipra Agrawal 001; Vijay Krishnan; Jayant R. Haritsa (DASFAA, 2004)

A Framework for High-Accuracy Privacy-Preserving Mining. - Shipra Agrawal 001; Jayant R. Haritsa (ICDE, 2005)

VoIP service quality monitoring using active and passive probes. - Shipra Agrawal 001; P. P. S. Narayan; Jeyashankher Ramamirtham; Rajeev Rastogi; Mark A. Smith; Ken Swanson; Marina Thottan (COMSWARE, 2006)

Efficient Detection of Distributed Constraint Violations. - Shipra Agrawal 001; Supratim Deb; K. V. M. Naidu; Rajeev Rastogi (ICDE, 2007)

Diagnosing Link-Level Anomalies Using Passive Probes. - Shipra Agrawal 001; K. V. M. Naidu; Rajeev Rastogi (INFOCOM, 2007)

Monitoring infrastructure for converged networks and services. - Shipra Agrawal 001; C. N. Kanthi; K. V. M. Naidu; Jeyashankher Ramamirtham; Rajeev Rastogi; Scott Satkin; Anand Srinivasan (Bell Labs Tech. J., 2007)

Parimutuel Betting on Permutations. - Shipra Agrawal 001; Zizhuo Wang 001; Yinyu Ye 001 (WINE, 2008)

Stochastic Combinatorial Optimization under Probabilistic Constraints - Shipra Agrawal 001; Amin Saberi; Yinyu Ye 001 (CoRR, 2008)

A unified framework for dynamic pari-mutuel information market design. - Shipra Agrawal 001; Erick Delage; Mark Peters; Zizhuo Wang 001; Yinyu Ye 001 (EC, 2009)

Distributionally Robust Stochastic Programming with Binary Random Variables - Shipra Agrawal 001; Yichuan Ding; Amin Saberi; Yinyu Ye 001 (CoRR, 2009)

FRAPP: a framework for high-accuracy privacy-preserving mining. - Shipra Agrawal 001; Jayant R. Haritsa; B. Aditya Prakash (Data Min. Knowl. Discov., 2009)

Correlation Robust Stochastic Optimization. - Shipra Agrawal 001; Yichuan Ding; Amin Saberi; Yinyu Ye 001 (SODA, 2010)

A Unified Framework for Dynamic Prediction Market Design. - Shipra Agrawal 001; Erick Delage; Mark Peters; Zizhuo Wang 001; Yinyu Ye 001 (Oper. Res., 2011)

Optimization under uncertainty: bounding the correlation gap. - Shipra Agrawal 001 (2011)

Price of Correlations in Stochastic Optimization. - Shipra Agrawal 001; Yichuan Ding; Amin Saberi; Yinyu Ye 001 (Oper. Res., 2012)

Analysis of Thompson Sampling for the Multi-armed Bandit Problem. - Shipra Agrawal 001; Navin Goyal (COLT, 2012)

Further Optimal Regret Bounds for Thompson Sampling. - Shipra Agrawal 001; Navin Goyal (AISTATS, 2013)

Thompson Sampling for Contextual Bandits with Linear Payoffs. - Shipra Agrawal 001; Navin Goyal (ICML (3), 2013)

Spectral Thompson Sampling. - Tomás Kocák; Michal Valko; Rémi Munos; Shipra Agrawal 001 (AAAI, 2014)

Bandits with concave rewards and convex knapsacks. - Shipra Agrawal 001; Nikhil R. Devanur (EC, 2014)

A Dynamic Near-Optimal Algorithm for Online Linear Programming. - Shipra Agrawal 001; Zizhuo Wang 001; Yinyu Ye 001 (Oper. Res., 2014)

Fast Algorithms for Online Stochastic Convex Programming. - Shipra Agrawal 001; Nikhil R. Devanur (SODA, 2015)

Linear Contextual Bandits with Global Constraints and Objective. - Shipra Agrawal 001; Nikhil R. Devanur (CoRR, 2015)

Contextual Bandits with Global Constraints and Objective. - Shipra Agrawal 001; Nikhil R. Devanur; Lihong Li 001 (CoRR, 2015)

An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives. - Shipra Agrawal 001; Nikhil R. Devanur; Lihong Li 001 (COLT, 2016)

Linear Contextual Bandits with Knapsacks. - Shipra Agrawal 001; Nikhil R. Devanur (NIPS, 2016)

A Near-Optimal Exploration-Exploitation Approach for Assortment Selection. - Shipra Agrawal 001; Vashist Avadhanula; Vineet Goyal; Assaf Zeevi (EC, 2016)

Thompson Sampling for the MNL-Bandit. - Shipra Agrawal 001; Vashist Avadhanula; Vineet Goyal; Assaf Zeevi (COLT, 2017)

Posterior sampling for reinforcement learning: worst-case regret bounds. - Shipra Agrawal 001; Randy Jia (CoRR, 2017)

Bandits with Delayed Anonymous Feedback. - Ciara Pike-Burke; Shipra Agrawal 001; Csaba Szepesvári; Steffen Grünewälder (CoRR, 2017)

Near-Optimal Regret Bounds for Thompson Sampling. - Shipra Agrawal 001; Navin Goyal (J. ACM, 2017)

Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy. - Shipra Agrawal 001; Morteza Zadimoghaddam; Vahab S. Mirrokni (ICML, 2018)

Bandits with Delayed, Aggregated Anonymous Feedback. - Ciara Pike-Burke; Shipra Agrawal 001; Csaba Szepesvári; Steffen Grünewälder (ICML, 2018)

Exploration by Distributional Reinforcement Learning. - Yunhao Tang; Shipra Agrawal 001 (IJCAI, 2018)

Robust Repeated Auctions under Heterogeneous Buyer Behavior. - Shipra Agrawal 001; Constantinos Daskalakis; Vahab S. Mirrokni; Balasubramanian Sivan (EC, 2018)

Implicit Policy for Reinforcement Learning. - Yunhao Tang; Shipra Agrawal 001 (CoRR, 2018)

Boosting Trust Region Policy Optimization by Normalizing Flows Policy. - Yunhao Tang; Shipra Agrawal 001 (CoRR, 2018)

Submodular Secretary Problem with Shortlists. - Shipra Agrawal 001; Mohammad Shadravan; Cliff Stein 001 (ITCS, 2019)

Dynamic First Price Auctions Robust to Heterogeneous Buyers. - Shipra Agrawal 001; Eric Balkanski; Vahab S. Mirrokni; Balasubramanian Sivan (CoRR, 2019)

MNL-Bandit: A Dynamic Learning Approach to Assortment Selection. - Shipra Agrawal 001; Vashist Avadhanula; Vineet Goyal; Assaf Zeevi (Oper. Res., 2019)

Bandits with Global Convex Constraints and Objective. - Shipra Agrawal 001; Nikhil R. Devanur (Oper. Res., 2019)

Discretizing Continuous Action Space for On-Policy Optimization. - Yunhao Tang; Shipra Agrawal 001 (AAAI, 2020)

Reinforcement Learning for Integer Programming: Learning to Cut. - Yunhao Tang; Shipra Agrawal 001; Yuri Faenza (ICML, 2020)

On Optimal Ordering in the Optimal Stopping Problem. - Shipra Agrawal 001; Jay Sethuraman; Xingyu Zhang (EC, 2020)

Robust Repeated First Price Auctions. - Shipra Agrawal 001; Eric Balkanski; Vahab S. Mirrokni; Balasubramanian Sivan (EC, 2021)

Dynamic Pricing and Learning under the Bass Model. - Shipra Agrawal 001; Steven Yin; Assaf Zeevi (EC, 2021)

Scale-Free Adversarial Multi Armed Bandits. - Sudeep Raja Putta; Shipra Agrawal 001 (ALT, 2022)

Online Allocation and Learning in the Presence of Strategic Agents. - Steven Yin; Shipra Agrawal 001; Assaf Zeevi (NeurIPS, 2022)

Learning in Structured MDPs with Convex Cost Functions: Improved Regret Bounds for Inventory Management. - Shipra Agrawal 001; Randy Jia (Oper. Res., 2022)

Dynamic Pricing and Learning with Bayesian Persuasion. - Shipra Agrawal 001; Yiding Feng 001; Wei Tang (NeurIPS, 2023)

Optimistic Posterior Sampling for Reinforcement Learning: Worst-Case Regret Bounds. - Shipra Agrawal 001; Randy Jia (Math. Oper. Res., 2023)

Dynamic Pricing and Learning with Long-term Reference Effects. - Shipra Agrawal 001; Wei Tang (EC, 2024)

Optimistic Q-learning for average reward and episodic reinforcement learning. - Priyank Agrawal; Shipra Agrawal 001 (CoRR, 2024)

Data Dependent Regret Bounds for Online Portfolio Selection with Predicted Returns. - Sudeep Raja Putta; Shipra Agrawal 001 (ALT, 2025)

Optimistic Q-learning for average reward and episodic reinforcement learning extended abstract. - Priyank Agrawal; Shipra Agrawal 001 (COLT, 2025)

Q-learning with Posterior Sampling. - Priyank Agrawal; Shipra Agrawal 001; Azmat Azati (CoRR, 2025)