| 2025 | CPAIOR | On the Efficiency of Algebraic Simplex Algorithms for Solving MDPs. | Dibyangshu Mukherjee, Shivaram Kalyanakrishnan |
| 2025 | ECAI | Efficient Computation of Blackwell Optimal Policies Using Rational Functions. | Dibyangshu Mukherjee, Shivaram Kalyanakrishnan |
| 2025 | ICAPS | An Improved Lower Bound on the Length of Locally-Improving Policy Sequences in MDPs with Large Action Sets. | Pratyush Agarwal, Mulinti Shaik Wajid, Shivaram Kalyanakrishnan |
| 2025 | ICAPS | Howard's Policy Iteration is Subexponential for Deterministic Markov Decision Problems with Rewards of Fixed Bit-size and Arbitrary Discount Factor. | Dibyangshu Mukherjee, Shivaram Kalyanakrishnan |
| 2024 | IJCAI | Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks. | Hastyn Doshi, Ayush Tripathi, Keshav Agarwal, Harshad Khadilkar, Shivaram Kalyanakrishnan |
| 2024 | ISIT | Optimal Stopping Rules for Best Arm Identification in Stochastic Bandits under Uniform Sampling. | Vedang Gupta, Yash Gadhia, Shivaram Kalyanakrishnan, Nikhil Karamchandani |
| 2022 | AISTATS | PAC Mode Estimation using PPR Martingale Confidence Sequences. | Shubham Anand Jain, Rohan Shah, Sanit Gupta, Denil Mehta, Inderjeet J. Nair, Jian Vora, Sushil Khyalia, Sourav Das, Vinay J. Ribeiro, Shivaram Kalyanakrishnan |
| 2021 | IJCAI | Intelligent and Learning Agents: Four Investigations. | Shivaram Kalyanakrishnan |
| 2020 | AAAI | Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory. | Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan |
| 2019 | ICML | PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits. | Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan |
| 2019 | UAI | A Tighter Analysis of Randomised Policy Iteration. | Meet Taraviya, Shivaram Kalyanakrishnan |
| 2018 | AIES | Opportunities and Challenges for Artificial Intelligence in India. | Shivaram Kalyanakrishnan, Rahul Alex Panicker, Sarayu Natarajan, Shreya Rao |
| 2018 | UAI | Quantile-Regret Minimisation in Infinitely Many-Armed Bandits. | Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan |
| 2017 | AAAI | PAC Identification of a Bandit Arm Relative to a Reward Quantile. | Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan |
| 2017 | IJCAI | Improved Strong Worst-case Upper Bounds for MDP Planning. | Anchit Gupta, Shivaram Kalyanakrishnan |
| 2016 | AAAI | Randomised Procedures for Initialising and Switching Actions in Policy Iteration. | Shivaram Kalyanakrishnan, Neeldhara Misra, Aditya Gopalan |
| 2016 | IJCAI | Batch-Switching Policy Iteration. | Shivaram Kalyanakrishnan, Utkarsh Mall, Ritish Goyal |
| 2014 | CIKM | On Building Decision Trees from Large-scale Data in Applications of On-line Advertising. | Shivaram Kalyanakrishnan, Deepthi Singh, Ravi Kant |
| 2014 | ICML | GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare. | Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal |
| 2013 | COLT | Information Complexity in Bandit Subset Selection. | Emilie Kaufmann, Shivaram Kalyanakrishnan |
| 2012 | AAMAS | UT Austin Villa 2011: a champion agent in the RoboCup 3D soccer simulation competition. | Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, Peter Stone |
| 2012 | ICML | PAC Subset Selection in Stochastic Multi-armed Bandits. | Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone |
| 2010 | IAAI | Predicting Falls of a Humanoid Robot through Machine Learning. | Shivaram Kalyanakrishnan, Ambarish Goswami |
| 2010 | ICML | Efficient Selection of Multiple Bandit Arms: Theory and Practice. | Shivaram Kalyanakrishnan, Peter Stone |
| 2009 | RoboCup | Three Humanoid Soccer Platforms: Comparison and Synthesis. | Shivaram Kalyanakrishnan, Todd Hester, Michael J. Quinlan, Yinon Bentor, Peter Stone |
| 2009 | RoboCup | Learning Complementary Multiagent Behaviors: A Case Study. | Shivaram Kalyanakrishnan, Peter Stone |
| 2007 | RoboCup | Model-Based Reinforcement Learning in a Complex Domain. | Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu |
| 2006 | RoboCup | Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study. | Shivaram Kalyanakrishnan, Yaxin Liu, Peter Stone |