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ORCIDDebmalya Mandal
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2020 – today
- 2024
[c23]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. AISTATS 2024: 1243-1251- [c22]Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences. ICML 2024 - [c21]Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic:
Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs. ICML 2024 - [i25]Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic:
Corruption Robust Offline Reinforcement Learning with Human Feedback. CoRR abs/2402.06734 (2024) - [i24]Nam Phuong Tran, The-Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, Long Tran-Thanh:
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games. CoRR abs/2402.07067 (2024) - [i23]Ben Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic:
Performative Reinforcement Learning in Gradually Shifting Environments. CoRR abs/2402.09838 (2024) - [i22]Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences. CoRR abs/2403.01857 (2024) - [i21]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. CoRR abs/2403.07933 (2024) - [i20]Nam Phuong Tran, The-Anh Ta, Debmalya Mandal, Long Tran-Thanh:
Symmetric Linear Bandits with Hidden Symmetry. CoRR abs/2405.13899 (2024) - [i19]Hadi Hosseini, Debmalya Mandal, Amrit Puhan:
The Surprising Effectiveness of SP Voting with Partial Preferences. CoRR abs/2406.00870 (2024) - 2023
- [c20]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. AAAI 2023: 9064-9071 - [c19]Jiarui Gan, Annika Hennes, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Markov Decision Processes with Time-Varying Geometric Discounting. AAAI 2023: 11980-11988 - [c18]Mohammad Mohammadi, Jonathan Nöther, Debmalya Mandal, Adish Singla, Goran Radanovic:
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks. AAMAS 2023: 1835-1844 - [c17]Debajyoti Kar, Mert Kosan, Debmalya Mandal, Sourav Medya, Arlei Silva, Palash Dey, Swagato Sanyal:
Feature-based Individual Fairness in k-clustering. AAMAS 2023: 2772-2774 - [c16]Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic:
Performative Reinforcement Learning. ICML 2023: 23642-23680 - [i18]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. CoRR abs/2302.03608 (2023) - [i17]Mohammad Mohammadi, Jonathan Nöther, Debmalya Mandal, Adish Singla, Goran Radanovic:
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks. CoRR abs/2302.13851 (2023) - [i16]Jiarui Gan, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Sequential Principal-Agent Problems with Communication: Efficient Computation and Learning. CoRR abs/2306.03832 (2023) - [i15]Jiarui Gan, Annika Hennes, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Markov Decision Processes with Time-Varying Geometric Discounting. CoRR abs/2307.10491 (2023) - [i14]Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic:
Agent-Specific Effects. CoRR abs/2310.11334 (2023) - 2022
- [c15]Nicholas Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Sequential Blocked Matching. AAAI 2022: 4834-4842 - [c14]Samuel Deng, Yilin Guo, Daniel Hsu, Debmalya Mandal:
Learning Tensor Representations for Meta-Learning. AISTATS 2022: 11550-11580 - [i13]Samuel Deng, Yilin Guo, Daniel Hsu, Debmalya Mandal:
Learning Tensor Representations for Meta-Learning. CoRR abs/2201.07348 (2022) - [i12]Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic:
Performative Reinforcement Learning. CoRR abs/2207.00046 (2022) - [i11]Debmalya Mandal, Jiarui Gan:
Socially Fair Reinforcement Learning. CoRR abs/2208.12584 (2022) - 2021
- [j2]Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal:
MetaLearning with Graph Neural Networks: Methods and Applications. SIGKDD Explor. 23(2): 13-22 (2021) - [c13]Hadi Hosseini, Debmalya Mandal, Nisarg Shah, Kevin Shi:
Surprisingly Popular Voting Recovers Rankings, Surprisingly! IJCAI 2021: 245-251 - [i10]Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal:
Meta-Learning with Graph Neural Networks: Methods and Applications. CoRR abs/2103.00137 (2021) - [i9]Hadi Hosseini, Debmalya Mandal, Nisarg Shah, Kevin Shi:
Surprisingly Popular Voting Recovers Rankings, Surprisingly! CoRR abs/2105.09386 (2021) - [i8]Nicholas Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Sequential Blocked Matching. CoRR abs/2108.00073 (2021) - [i7]Debajyoti Kar, Sourav Medya, Debmalya Mandal, Arlei Silva, Palash Dey, Swagato Sanyal:
Feature-based Individual Fairness in k-Clustering. CoRR abs/2109.04554 (2021) - [i6]Rohith Dwarakanath Vallam, Priyanka Bhatt, Debmalya Mandal, Y. Narahari:
Improving Teacher-Student Interactions in Online Educational Forums using a Markov Chain based Stackelberg Game Model. CoRR abs/2112.01239 (2021) - 2020
- [j1]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. ACM Trans. Economics and Comput. 8(1): 2:1-2:34 (2020) - [c12]Debmalya Mandal, Goran Radanovic, David C. Parkes:
The Effectiveness of Peer Prediction in Long-Term Forecasting. AAAI 2020: 2160-2167 - [c11]Nick Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh:
Adversarial Blocking Bandits. NeurIPS 2020 - [c10]Debmalya Mandal, Samuel Deng, Suman Jana, Jeannette M. Wing, Daniel J. Hsu:
Ensuring Fairness Beyond the Training Data. NeurIPS 2020 - [c9]Debmalya Mandal, Nisarg Shah, David P. Woodruff:
Optimal Communication-Distortion Tradeoff in Voting. EC 2020: 795-813 - [i5]Debmalya Mandal, Samuel Deng, Suman Jana, Jeannette M. Wing, Daniel Hsu:
Ensuring Fairness Beyond the Training Data. CoRR abs/2007.06029 (2020)
2010 – 2019
- 2019
- [c8]Debmalya Mandal, Ariel D. Procaccia, Nisarg Shah, David P. Woodruff:
Efficient and Thrifty Voting by Any Means Necessary. NeurIPS 2019: 7178-7189 - [i4]Debmalya Mandal, David C. Parkes:
Weighted Tensor Completion for Time-Series Causal Inference. CoRR abs/1902.04646 (2019) - 2017
- [c7]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. EC 2017: 81-98 - [i3]Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes:
Calibrated Fairness in Bandits. CoRR abs/1707.01875 (2017) - 2016
- [c6]Debmalya Mandal, David C. Parkes:
Correlated Voting. IJCAI 2016: 366-372 - [i2]Debmalya Mandal, Matthew Leifer, David C. Parkes, Galen Pickard, Victor Shnayder:
Peer Prediction with Heterogeneous Tasks. CoRR abs/1612.00928 (2016) - 2015
- [c5]Rohith Dwarakanath Vallam, Priyanka Bhatt, Debmalya Mandal, Y. Narahari:
A Stackelberg Game Approach for Incentivizing Participation in Online Educational Forums with Heterogeneous Student Population. AAAI 2015: 1043-1049 - [c4]Praphul Chandra, Yadati Narahari, Debmalya Mandal, Prasenjit Dey:
Novel Mechanisms for Online Crowdsourcing with Unreliable, Strategic Agents. AAAI 2015: 1256-1262 - [c3]Arpita Biswas, Shweta Jain, Debmalya Mandal, Y. Narahari:
A Truthful Budget Feasible Multi-Armed Bandit Mechanism for Crowdsourcing Time Critical Tasks. AAMAS 2015: 1101-1109 - [c2]Arupratan Ray, Debmalya Mandal, Yadati Narahari:
Profit Maximizing Prior-free Multi-unit Procurement Auctions with Capacitated Sellers. AAMAS 2015: 1753-1754 - [i1]Arupratan Ray, Debmalya Mandal, Y. Narahari:
Profit Maximizing Prior-free Multi-unit Procurement Auctions with Capacitated Sellers. CoRR abs/1504.01020 (2015) - 2014
- [c1]Debmalya Mandal, Yadati Narahari:
A novel ex-post truthful mechanism for multi-slot sponsored search auctions. AAMAS 2014: 1555-1556
Coauthor Index
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last updated on 2024-09-04 00:27 CEST by the dblp team
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