Shivaram Kalyanakrishnan

51 papers A* 12A 9B 1C 6Journal 16Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Upper Bounds for All and Max-Gain Policy Iteration Algorithms on Deterministic MDPs. Math. Oper. Res. Ritesh Goenka, Eashan Gupta, Sushil Khyalia, Shivaram Kalyanakrishnan
2025	J	`jnl`	A New Interpretation of the Certainty-Equivalence Approach for PAC Reinforcement Learning with a Generative Model. CoRR Shivaram Kalyanakrishnan, Sheel Shah, Santhosh Kumar Guguloth
2025	A	`conf`	A View of the Certainty-Equivalence Method for PAC RL as an Application of the Trajectory Tree Method. AAMAS Shivaram Kalyanakrishnan, Sheel Shah, Santhosh Kumar Guguloth
2025	A	`conf`	Efficient Computation of Blackwell Optimal Policies Using Rational Functions. ECAI Dibyangshu Mukherjee, Shivaram Kalyanakrishnan
2025	J	`jnl`	Efficient Computation of Blackwell Optimal Policies using Rational Functions. CoRR Dibyangshu Mukherjee, Shivaram Kalyanakrishnan
2025	J	`jnl`	Howard's Policy Iteration is Subexponential for Deterministic Markov Decision Problems with Rewards of Fixed Bit-size and Arbitrary Discount Factor. CoRR Dibyangshu Mukherjee, Shivaram Kalyanakrishnan
2025	J	`jnl`	Hybrids of Reinforcement Learning and Evolutionary Computation in Finance: A Survey. ACM Comput. Surv. Sandarbh Yadav, Vadlamani Ravi, Shivaram Kalyanakrishnan
2025	—	`conf`	On the Efficiency of Algebraic Simplex Algorithms for Solving MDPs. CPAIOR (2) Dibyangshu Mukherjee, Shivaram Kalyanakrishnan
2024	A*	`conf`	Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks. IJCAI Hastyn Doshi, Ayush Tripathi, Keshav Agarwal, Harshad Khadilkar, Shivaram Kalyanakrishnan
2024	B	`conf`	Optimal Stopping Rules for Best Arm Identification in Stochastic Bandits under Uniform Sampling. ISIT Vedang Gupta, Yash Gadhia, Shivaram Kalyanakrishnan, Nikhil Karamchandani
2022	J	`jnl`	Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence. CoRR Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David C. Parkes, William H. Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
2022	A	`conf`	PAC Mode Estimation using PPR Martingale Confidence Sequences. AISTATS Shubham Anand Jain, Rohan Shah, Sanit Gupta, Denil Mehta, Inderjeet J. Nair, Jian Vora, Sushil Khyalia, Sourav Das, Vinay J. Ribeiro, Shivaram Kalyanakrishnan
2022	J	`jnl`	Some Upper Bounds on the Running Time of Policy Iteration on Deterministic MDPs. CoRR Ritesh Goenka, Eashan Gupta, Sushil Khyalia, Pratyush Agarwal, Mulinti Shaik Wajid, Shivaram Kalyanakrishnan
2021	J	`jnl`	An Analysis of Frame-skipping in Reinforcement Learning. CoRR Shivaram Kalyanakrishnan, Siddharth Aravindan, Vishwajeet Bagdawat, Varun Bhatt, Harshith Goka, Archit Gupta, Kalpesh Krishna, Vihari Piratla
2021	A*	`conf`	Intelligent and Learning Agents: Four Investigations. IJCAI Shivaram Kalyanakrishnan
2021	—	`conf`	The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022. NeurIPS (Competition and Demos) Ryan W. Gardner, Gino Perrotta, Anvay Shah, Shivaram Kalyanakrishnan, Kevin A. Wang, Gregory Clark, Timo Bertram, Johannes Fürnkranz, Martin Müller, Brady P. Garrison, Prithviraj Dasgupta, Saeid Rezaei
2021	—	`conf`	The Second NeurIPS Tournament of Reconnaissance Blind Chess. NeurIPS (Competition and Demos) Gino Perrotta, Ryan W. Gardner, Corey Lowman, Mohammad Taufeeque, Nitish Tongia, Shivaram Kalyanakrishnan, Gregory Clark, Kevin Wang, Eitan Rothberg, Brady P. Garrison, Prithviraj Dasgupta, Callum Canavan, Lucas McCabe
2020	—	`conf`	Lower Bounds for Policy Iteration on Multi-action MDPs. CDC Kumar Ashutosh, Sarthak Consul, Bhishma Dedhia, Parthasarathi Khirwadkar, Sahil Shah, Shivaram Kalyanakrishnan
2020	J	`jnl`	Lower Bounds for Policy Iteration on Multi-action MDPs. CoRR Kumar Ashutosh, Sarthak Consul, Bhishma Dedhia, Parthasarathi Khirwadkar, Sahil Shah, Shivaram Kalyanakrishnan
2020	A*	`conf`	Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory. AAAI Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2019	A	`conf`	A Tighter Analysis of Randomised Policy Iteration. UAI Meet Taraviya, Shivaram Kalyanakrishnan
2019	A*	`conf`	PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits. ICML Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2019	J	`jnl`	PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits. CoRR Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2019	J	`jnl`	Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory. CoRR Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2018	C	`conf`	Opportunities and Challenges for Artificial Intelligence in India. AIES Shivaram Kalyanakrishnan, Rahul Alex Panicker, Sarayu Natarajan, Shreya Rao
2018	A	`conf`	Quantile-Regret Minimisation in Infinitely Many-Armed Bandits. UAI Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2017	A*	`conf`	Improved Strong Worst-case Upper Bounds for MDP Planning. IJCAI Anchit Gupta, Shivaram Kalyanakrishnan
2017	A*	`conf`	PAC Identification of a Bandit Arm Relative to a Reward Quantile. AAAI Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
2017	J	`jnl`	RLWS: A Reinforcement Learning based GPU Warp Scheduler. CoRR Jayvant Anantpur, Nagendra Dwarakanath Gulur, Shivaram Kalyanakrishnan, Shalabh Bhatnagar, R. Govindarajan
2016	J	`jnl`	AI's 10 to Watch. IEEE Intell. Syst. Haris Aziz, Elias Bareinboim, Yejin Choi, Daniel J. Hsu, Shivaram Kalyanakrishnan, Reshef Meir, Suchi Saria, Gerardo I. Simari, Lirong Xia, William Yeoh
2016	A*	`conf`	Batch-Switching Policy Iteration. IJCAI Shivaram Kalyanakrishnan, Utkarsh Mall, Ritish Goyal
2016	A*	`conf`	Randomised Procedures for Initialising and Switching Actions in Policy Iteration. AAAI Shivaram Kalyanakrishnan, Neeldhara Misra, Aditya Gopalan
2014	J	`jnl`	Direction-changing fall control of humanoid robots: theory and experiments. Auton. Robots Ambarish Goswami, Seung-kook Yun, Umashankar Nagarajan, Sung-Hee Lee, KangKang Yin, Shivaram Kalyanakrishnan
2014	A*	`conf`	GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare. ICML Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal
2014	A	`conf`	On Building Decision Trees from Large-scale Data in Applications of On-line Advertising. CIKM Shivaram Kalyanakrishnan, Deepthi Singh, Ravi Kant
2013	A*	`conf`	Information Complexity in Bandit Subset Selection. COLT Emilie Kaufmann, Shivaram Kalyanakrishnan
2012	A*	`conf`	PAC Subset Selection in Stochastic Multi-armed Bandits. ICML Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone
2012	A	`conf`	UT Austin Villa 2011: a champion agent in the RoboCup 3D soccer simulation competition. AAMAS Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, Peter Stone
2011	J	`jnl`	Characterizing reinforcement learning methods through parameterized learning problems. Mach. Learn. Shivaram Kalyanakrishnan, Peter Stone
2011	J	`jnl`	Learning to Predict Humanoid Fall. Int. J. Humanoid Robotics Shivaram Kalyanakrishnan, Ambarish Goswami
2011	—	`conf`	On learning with imperfect representations. ADPRL Shivaram Kalyanakrishnan, Peter Stone
2011	A	`conf`	On optimizing interdependent skills: a case study in simulated 3D humanoid robot soccer. AAMAS Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, Peter Stone
2010	A*	`conf`	Efficient Selection of Multiple Bandit Arms: Theory and Practice. ICML Shivaram Kalyanakrishnan, Peter Stone
2010	C	`conf`	Predicting Falls of a Humanoid Robot through Machine Learning. IAAI Shivaram Kalyanakrishnan, Ambarish Goswami
2009	—	`conf`	An empirical analysis of value function-based and policy search reinforcement learning. AAMAS (2) Shivaram Kalyanakrishnan, Peter Stone
2009	C	`conf`	Learning Complementary Multiagent Behaviors: A Case Study. RoboCup Shivaram Kalyanakrishnan, Peter Stone
2009	—	`conf`	Learning complementary multiagent behaviors: a case study. AAMAS (2) Shivaram Kalyanakrishnan, Peter Stone
2009	C	`conf`	Three Humanoid Soccer Platforms: Comparison and Synthesis. RoboCup Shivaram Kalyanakrishnan, Todd Hester, Michael J. Quinlan, Yinon Bentor, Peter Stone
2007	A	`conf`	Batch reinforcement learning in a complex domain. AAMAS Shivaram Kalyanakrishnan, Peter Stone
2007	C	`conf`	Model-Based Reinforcement Learning in a Complex Domain. RoboCup Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
2006	C	`conf`	Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study. RoboCup Shivaram Kalyanakrishnan, Yaxin Liu, Peter Stone