Shipra Agrawal

Affiliations:
  • Columbia University, New York City, NY, USA
  • Microsoft Research India, Bangalore, India (2011 - 2015)
  • Stanford University, CA, USA (PhD 2011)


According to our database1, Shipra Agrawal authored at least 49 papers between 2003 and 2022.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
Learning in Structured MDPs with Convex Cost Functions: Improved Regret Bounds for Inventory Management.
Oper. Res., 2022

Scale-Free Adversarial Multi Armed Bandits.
Proceedings of the International Conference on Algorithmic Learning Theory, 2022

2021
Dynamic Pricing and Learning under the Bass Model.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

Robust Repeated First Price Auctions.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

2020
On Optimal Ordering in the Optimal Stopping Problem.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Reinforcement Learning for Integer Programming: Learning to Cut.
Proceedings of the 37th International Conference on Machine Learning, 2020

Discretizing Continuous Action Space for On-Policy Optimization.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Bandits with Global Convex Constraints and Objective.
Oper. Res., 2019

MNL-Bandit: A Dynamic Learning Approach to Assortment Selection.
Oper. Res., 2019

Dynamic First Price Auctions Robust to Heterogeneous Buyers.
CoRR, 2019

Submodular Secretary Problem with Shortlists.
Proceedings of the 10th Innovations in Theoretical Computer Science Conference, 2019

2018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy.
CoRR, 2018

Implicit Policy for Reinforcement Learning.
CoRR, 2018

Robust Repeated Auctions under Heterogeneous Buyer Behavior.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Exploration by Distributional Reinforcement Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Bandits with Delayed, Aggregated Anonymous Feedback.
Proceedings of the 35th International Conference on Machine Learning, 2018

Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Near-Optimal Regret Bounds for Thompson Sampling.
J. ACM, 2017

Bandits with Delayed Anonymous Feedback.
CoRR, 2017

Posterior sampling for reinforcement learning: worst-case regret bounds.
CoRR, 2017

Optimistic posterior sampling for reinforcement learning: worst-case regret bounds.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Thompson Sampling for the MNL-Bandit.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
A Near-Optimal Exploration-Exploitation Approach for Assortment Selection.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Linear Contextual Bandits with Knapsacks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Contextual Bandits with Global Constraints and Objective.
CoRR, 2015

Linear Contextual Bandits with Global Constraints and Objective.
CoRR, 2015

Fast Algorithms for Online Stochastic Convex Programming.
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

2014
A Dynamic Near-Optimal Algorithm for Online Linear Programming.
Oper. Res., 2014

Bandits with concave rewards and convex knapsacks.
Proceedings of the ACM Conference on Economics and Computation, 2014

Spectral Thompson Sampling.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Thompson Sampling for Contextual Bandits with Linear Payoffs.
Proceedings of the 30th International Conference on Machine Learning, 2013

Further Optimal Regret Bounds for Thompson Sampling.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Analysis of Thompson Sampling for the Multi-armed Bandit Problem.
Proceedings of the COLT 2012, 2012

Price of Correlations in Stochastic Optimization.
Oper. Res., 2012

2011
A Unified Framework for Dynamic Prediction Market Design.
Oper. Res., 2011

2010
Correlation Robust Stochastic Optimization.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

2009
FRAPP: a framework for high-accuracy privacy-preserving mining.
Data Min. Knowl. Discov., 2009

Distributionally Robust Stochastic Programming with Binary Random Variables
CoRR, 2009

A unified framework for dynamic pari-mutuel information market design.
Proceedings of the Proceedings 10th ACM Conference on Electronic Commerce (EC-2009), 2009

2008
Stochastic Combinatorial Optimization under Probabilistic Constraints
CoRR, 2008

Parimutuel Betting on Permutations.
Proceedings of the Internet and Network Economics, 4th International Workshop, 2008

2007
Monitoring infrastructure for converged networks and services.
Bell Labs Tech. J., 2007

Diagnosing Link-Level Anomalies Using Passive Probes.
Proceedings of the INFOCOM 2007. 26th IEEE International Conference on Computer Communications, 2007

Efficient Detection of Distributed Constraint Violations.
Proceedings of the 23rd International Conference on Data Engineering, 2007

2006
VoIP service quality monitoring using active and passive probes.
Proceedings of the First International Conference on COMmunication System softWAre and MiddlewaRE (COMSWARE 2006), 2006

2005
A Framework for High-Accuracy Privacy-Preserving Mining.
Proceedings of the 21st International Conference on Data Engineering, 2005

2004
On Addressing Efficiency Concerns in Privacy-Preserving Mining.
Proceedings of the Database Systems for Advances Applications, 2004

2003
On Addressing Efficiency Concerns in Privacy Preserving Data Mining
CoRR, 2003


  Loading...