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ORCIDSoham R. Phade
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2020 – today
- 2023
[j4]Soham R. Phade
, Venkat Anantharam:
Learning in Games with Cumulative Prospect Theoretic Preferences. Dyn. Games Appl. 13(1): 265-306 (2023)- [j3]Arundhati Banerjee, Soham R. Phade, Stefano Ermon, Stephan Zheng:
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c5]Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran:
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets. AISTATS 2023: 9773-9806 - [c4]Michael Curry, Alexander Trott, Soham Phade, Yu Bai, Stephan Zheng:
Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning. AAMAS 2023: 2760-2762 - [c3]Yigit Efe Erginbas, Thomas A. Courtade, Kannan Ramchandran, Soham Phade:
Online Pricing for Multi-User Multi-Item Markets. NeurIPS 2023 - [i13]Arundhati Banerjee, Soham Phade, Stefano Ermon, Stephan Zheng:
MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning. CoRR abs/2304.04668 (2023) - [i12]Yoshua Bengio, Prateek Gupta, Lu Li, Soham Phade, Sunil Srinivasa, Andrew Williams, Tianyu Zhang, Yang Zhang, Stephan Zheng:
AI For Global Climate Cooperation 2023 Competition Proceedings. CoRR abs/2307.06951 (2023) - 2022
- [i11]Michael Curry, Alexander Trott, Soham Phade, Yu Bai, Stephan Zheng:
Finding General Equilibria in Many-Agent Economic Simulations Using Deep Reinforcement Learning. CoRR abs/2201.01163 (2022) - [i10]Yigit Efe Erginbas, Soham R. Phade, Kannan Ramchandran:
Interactive Recommendations for Optimal Allocations in Markets with Constraints. CoRR abs/2207.04143 (2022) - [i9]Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng:
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N. CoRR abs/2208.07004 (2022) - [i8]Yigit Efe Erginbas, Soham R. Phade, Kannan Ramchandran:
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets. CoRR abs/2212.06891 (2022) - 2021
- [i7]Soham R. Phade, Venkat Anantharam:
Mechanism Design for Cumulative Prospect Theoretic Agents: A General Framework and the Revelation Principle. CoRR abs/2101.08722 (2021) - 2020
- [i6]Soham R. Phade, Venkat Anantharam:
Black-Box Strategies and Equilibrium for Games with Cumulative Prospect Theoretic Players. CoRR abs/2004.09592 (2020) - [i5]Vipul Gupta, Soham R. Phade, Thomas A. Courtade, Kannan Ramchandran:
Utility-based Resource Allocation and Pricing for Serverless Computing. CoRR abs/2008.07793 (2020) - [i4]Vidya Muthukumar, Soham Phade, Anant Sahai:
On the Impossibility of Convergence of Mixed Strategies with No Regret Learning. CoRR abs/2012.02125 (2020)
2010 – 2019
- 2019
- [j2]Soham R. Phade, Venkat Anantharam:
On the Geometry of Nash and Correlated Equilibria with Cumulative Prospect Theoretic Preferences. Decis. Anal. 16(2): 142-156 (2019) - [c2]Soham R. Phade, Venkat Anantharam:
Optimal Resource Allocation over Networks via Lottery-Based Mechanisms. GAMENETS 2019: 51-70 - 2018
- [i3]Soham R. Phade, Venkat Anantharam:
Learning in Games with Cumulative Prospect Theoretic Preferences. CoRR abs/1804.08005 (2018) - [i2]Soham R. Phade, Venkat Anantharam:
Optimal Resource Allocation over Networks via Lottery-Based Mechanisms. CoRR abs/1812.00501 (2018) - 2017
- [j1]Soham R. Phade, Vivek S. Borkar:
A Distributed Boyle-Dykstra-Han Scheme. SIAM J. Optim. 27(3): 1880-1897 (2017) - [c1]Soham R. Phade, Venkat Anantharam:
On the geometry of nash and correlated equilibria with cumulative prospect theoretic preferences. Allerton 2017: 724-731 - [i1]Soham R. Phade, Venkat Anantharam:
On the Geometry of Nash and Correlated Equilibria with Cumulative Prospect Theoretic Preferences. CoRR abs/1712.00859 (2017)
Coauthor Index
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