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Arnab Maiti
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2020 – today
- 2025
[j4]Arindam Khan
, Aditya Lonkar
, Arnab Maiti
, Amatya Sharma
, Andreas Wiese
:
Tight Approximation Algorithms for 2D Guillotine Strip Packing. ACM Trans. Algorithms 21(3): 28:1-28:30 (2025)
[j3]Arnab Maiti
, Ross Boczar
, Kevin G. Jamieson
, Lillian J. Ratliff
:
Query-Efficient Algorithm to Find all Nash Equilibria in a Two-Player Zero-Sum Matrix Game. ACM Trans. Economics and Comput. 13(3): 15:1-15:18 (2025)
[c16]Arnab Maiti, Zhiyuan Fan, Kevin G. Jamieson, Lillian J. Ratliff, Gabriele Farina:
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries. COLT 2025: 3881-3932
[c15]Arnab Maiti:
Open Problem: Optimal Instance-Dependent Sample Complexity for finding Nash Equilibrium in Two Player Zero-Sum Matrix games. COLT 2025: 6230-6234
[c14]Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin Jamieson, Lillian J. Ratliff:
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. ICML 2025
[c13]Arnab Maiti
, Kevin G. Jamieson
, Lillian J. Ratliff
:
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games Under Noisy Feedback. SAGT 2025: 3-20
[i17]Arnab Maiti, Zhiyuan Fan, Kevin G. Jamieson, Lillian J. Ratliff, Gabriele Farina:
Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries. CoRR abs/2504.00461 (2025)
[i16]Junyan Liu, Arnab Maiti, Artin Tajdini, Kevin G. Jamieson, Lillian J. Ratliff:
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals. CoRR abs/2505.23124 (2025)
[i15]Zhiyuan Fan, Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff, Gabriele Farina:
On the Universal Near Optimality of Hedge in Combinatorial Settings. CoRR abs/2510.17099 (2025)
[i14]Shinji Ito, Kevin G. Jamieson, Haipeng Luo, Arnab Maiti, Taira Tsuchiya:
Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback. CoRR abs/2510.17103 (2025)- 2024
[j2]Arnab Maiti, Palash Dey
:
On Parameterized Complexity of Binary Networked Public Goods Game. Algorithmica 86(1): 307-333 (2024)
[j1]Arnab Maiti, Palash Dey
:
Query complexity of tournament solutions. Theor. Comput. Sci. 991: 114422 (2024)
[c12]Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff:
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. AISTATS 2024: 2602-2610
[c11]Arnab Maiti
, Palash Dey
:
On Binary Networked Public Goods Game with Altruism. LATIN (2) 2024: 289-303- 2023
[c10]Siddharth Barman, Arindam Khan, Arnab Maiti, Ayush Sawarni:
Fairness and Welfare Quantification for Regret in Multi-Armed Bandits. AAAI 2023: 6762-6769
[c9]Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff:
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. AISTATS 2023: 9429-9469
[i13]Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff:
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games. CoRR abs/2303.10565 (2023)
[i12]Arnab Maiti, Kevin G. Jamieson, Lillian J. Ratliff:
Logarithmic Regret for Matrix Games against an Adversary with Noisy Bandit Feedback. CoRR abs/2306.13233 (2023)
[i11]Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff:
Query-Efficient Algorithms to Find the Unique Nash Equilibrium in a Two-Player Zero-Sum Matrix Game. CoRR abs/2310.16236 (2023)
[i10]Arnab Maiti, Ross Boczar, Kevin G. Jamieson, Lillian J. Ratliff:
Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits. CoRR abs/2310.16252 (2023)- 2022
[c8]Siddharth Barman, Arindam Khan, Arnab Maiti:
Universal and Tight Online Algorithms for Generalized-Mean Welfare. AAAI 2022: 4793-4800
[c7]Arnab Maiti, Palash Dey:
On Parameterized Complexity of Binary Networked Public Goods Game. AAMAS 2022: 871-879
[c6]Arnab Maiti, Palash Dey:
Parameterized Algorithms for Kidney Exchange. AAMAS 2022: 1693-1695
[c5]Arindam Khan, Aditya Lonkar, Arnab Maiti, Amatya Sharma
, Andreas Wiese:
Tight Approximation Algorithms for Two-Dimensional Guillotine Strip Packing. ICALP 2022: 80:1-80:20
[c4]Arnab Maiti, Palash Dey:
Parameterized Algorithms for Kidney Exchange. IJCAI 2022: 405-411
[i9]Arindam Khan, Aditya Lonkar, Arnab Maiti, Amatya Sharma, Andreas Wiese:
Tight Approximation Algorithms for Two Dimensional Guillotine Strip Packing. CoRR abs/2202.05989 (2022)
[i8]Arnab Maiti, Palash Dey:
On Binary Networked Public Goods Game with Altruism. CoRR abs/2205.00442 (2022)
[i7]Siddharth Barman, Arindam Khan, Arnab Maiti, Ayush Sawarni:
Fairness and Welfare Quantification for Regret in Multi-Armed Bandits. CoRR abs/2205.13930 (2022)- 2021
[c3]Palash Dey, Arnab Maiti, Amatya Sharma
:
On Parameterized Complexity of Liquid Democracy. CALDAM 2021: 83-94
[c2]Arindam Khan, Arnab Maiti, Amatya Sharma, Andreas Wiese
:
On Guillotine Separable Packings for the Two-Dimensional Geometric Knapsack Problem. SoCG 2021: 48:1-48:17
[c1]Arnab Maiti, Vishakha Patil, Arindam Khan:
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization. NeurIPS 2021: 19553-19565
[i6]Arindam Khan, Arnab Maiti, Amatya Sharma
, Andreas Wiese:
On Guillotine Separable Packings for the Two-dimensional Geometric Knapsack Problem. CoRR abs/2103.09735 (2021)
[i5]Siddharth Barman, Arindam Khan, Arnab Maiti:
Universal and Tight Online Algorithms for Generalized-Mean Welfare. CoRR abs/2109.00874 (2021)
[i4]Arnab Maiti, Palash Dey:
Parameterized Algorithms for Kidney Exchange. CoRR abs/2112.10250 (2021)- 2020
[i3]Palash Dey, Arnab Maiti, Amatya Sharma:
On Parameterized Complexity of Liquid Democracy. CoRR abs/2011.14192 (2020)
[i2]Arnab Maiti, Palash Dey:
On Parameterized Complexity of Binary Networked Public Goods Game. CoRR abs/2012.01880 (2020)
[i1]Arnab Maiti, Vishakha Patil, Arindam Khan:
Streaming Algorithms for Stochastic Multi-armed Bandits. CoRR abs/2012.05142 (2020)
Coauthor Index

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last updated on 2026-02-05 23:44 CET by the dblp team
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