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ORCIDMridul Agarwal
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2020 – today
- 2023
[j11]Mridul Agarwal, Vaneet Aggarwal:
Reinforcement Learning for Joint Optimization of Multiple Rewards. J. Mach. Learn. Res. 24: 49:1-49:41 (2023)- [c19]Subhash Chand Agrawal, Rajesh Kumar Tripathi, Jai Kishan, Mridul Agarwal:
Poze with Vogue. ICCCNT 2023: 1-6 - [c18]Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal:
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization. ICML 2023: 11013-11049 - 2022
- [j10]Mridul Agarwal, Vaneet Aggarwal, Arnob Ghosh, Nilay Tiwari:
Reinforcement Learning for Mean-Field Game. Algorithms 15(3): 73 (2022) - [j9]Yimeng Wang, Mridul Agarwal, Tian Lan, Vaneet Aggarwal:
Learning-Based Online QoE Optimization in Multi-Agent Video Streaming. Algorithms 15(7): 227 (2022) - [j8]Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal:
Joint Optimization of Concave Scalarized Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm. J. Artif. Intell. Res. 74: 1565-1597 (2022) - [j7]Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, Satish V. Ukkusuri:
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC). J. Mach. Learn. Res. 23: 129:1-129:46 (2022) - [j6]Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli:
Multi-Agent Multi-Armed Bandits with Limited Communication. J. Mach. Learn. Res. 23: 212:1-212:24 (2022) - [j5]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Concave Utility Reinforcement Learning with Zero-Constraint Violations. Trans. Mach. Learn. Res. 2022 (2022) - [c17]Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal:
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. AAAI 2022: 3682-3689 - [c16]Mridul Agarwal, Vaneet Aggarwal, Tian Lan:
Multi-Objective Reinforcement Learning with Non-Linear Scalarization. AAMAS 2022: 9-17 - [c15]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Regret guarantees for model-based reinforcement learning with long-term average constraints. UAI 2022: 22-31 - [c14]Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn:
An explore-then-commit algorithm for submodular maximization under full-bandit feedback. UAI 2022: 1541-1551 - [i14]Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal:
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization. CoRR abs/2211.07675 (2022) - 2021
- [j4]Md. Masudur Rahman
, Mythra V. Balakuntala, Glebys T. Gonzalez, Mridul Agarwal, Upinder Kaur, Vishnunandan L. N. Venkatesh, Natalia Sanchez-Tamayo, Yexiang Xue, Richard M. Voyles, Vaneet Aggarwal, Juan P. Wachs:
SARTRES: a semi-autonomous robot teleoperation environment for surgery. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 9(4): 376-383 (2021) - [j3]Mridul Agarwal, Vaneet Aggarwal:
Blind decision making: Reinforcement learning with delayed observations. Pattern Recognit. Lett. 150: 176-182 (2021) - [j2]Mridul Agarwal, Vaneet Aggarwal, Abhishek K. Umrawal, Christopher J. Quinn:
Stochastic Top K-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization. Trans. Data Sci. 2(4): 38:1-38:39 (2021) - [c13]Mridul Agarwal, Vaneet Aggarwal, Abhishek Kumar Umrawal, Christopher J. Quinn:
DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits. AAAI 2021: 6557-6565 - [c12]Mridul Agarwal, Vaneet Aggarwal:
Blind Decision Making: Reinforcement Learning with Delayed Observations. ICAPS 2021: 2-6 - [c11]Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal:
Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback. ALT 2021: 306-339 - [c10]Glebys T. Gonzalez, Mridul Agarwal, Mythra V. Balakuntala, Md. Masudur Rahman, Upinder Kaur, Richard M. Voyles, Vaneet Aggarwal, Yexiang Xue, Juan P. Wachs:
DESERTS: DElay-tolerant SEmi-autonomous Robot Teleoperation for Surgery. ICRA 2021: 12693-12700 - [c9]Mridul Agarwal, Glebys T. Gonzalez, Mythra V. Balakuntala, Md. Masudur Rahman, Vaneet Aggarwal, Richard M. Voyles, Yexiang Xue, Juan P. Wachs:
Dexterous Skill Transfer between Surgical Procedures for Teleoperated Robotic Surgery. RO-MAN 2021: 1236-1242 - [c8]Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal:
Communication efficient parallel reinforcement learning. UAI 2021: 247-256 - [i13]Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli:
Multi-Agent Multi-Armed Bandits with Limited Communication. CoRR abs/2102.08462 (2021) - [i12]Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal:
Communication Efficient Parallel Reinforcement Learning. CoRR abs/2102.10740 (2021) - [i11]Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal:
Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm. CoRR abs/2105.14125 (2021) - [i10]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Markov Decision Processes with Long-Term Average Constraints. CoRR abs/2106.06680 (2021) - [i9]Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, Satish V. Ukkusuri:
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC). CoRR abs/2109.04024 (2021) - [i8]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Concave Utility Reinforcement Learning with Zero-Constraint Violations. CoRR abs/2109.05439 (2021) - [i7]Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal:
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. CoRR abs/2109.06332 (2021) - 2020
- [c7]Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal:
Escaping Saddle Points for Zeroth-order Non-convex Optimization using Estimated Gradient Descent. CISS 2020: 1-6 - [i6]Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal:
DART: aDaptive Accept RejecT for non-linear top-K subset identification. CoRR abs/2011.07687 (2020) - [i5]Mridul Agarwal, Vaneet Aggarwal:
Blind Decision Making: Reinforcement Learning with Delayed Observations. CoRR abs/2011.07715 (2020)
2010 – 2019
- 2019
- [c6]Md. Masudur Rahman, Natalia Sanchez-Tamayo, Glebys T. Gonzalez, Mridul Agarwal, Vaneet Aggarwal, Richard M. Voyles, Yexiang Xue, Juan P. Wachs:
Transferring Dexterous Surgical Skill Knowledge between Robots for Semi-autonomous Teleoperation. RO-MAN 2019: 1-6 - [i4]Mridul Agarwal, Vaneet Aggarwal:
A Reinforcement Learning Based Approach for Joint Multi-Agent Decision Making. CoRR abs/1909.02940 (2019) - [i3]Sathwik Chadaga, Mridul Agarwal, Vaneet Aggarwal:
Encoders and Decoders for Quantum Expander Codes Using Machine Learning. CoRR abs/1909.02945 (2019) - [i2]Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal:
Escaping Saddle Points for Zeroth-order Nonconvex Optimization using Estimated Gradient Descent. CoRR abs/1910.01277 (2019) - 2018
- [i1]Mridul Agarwal, Vaneet Aggarwal:
Regret Bounds for Stochastic Combinatorial Multi-Armed Bandits with Linear Space Complexity. CoRR abs/1811.11925 (2018) - 2012
- [c5]Akshara Rai, Prem Kumar Patchaikani, Mridul Agarwal, Rohit Gupta, Laxmidhar Behera:
Grasping Region Identification in Novel Objects Using Microsoft Kinect. ICONIP (4) 2012: 172-179
2000 – 2009
- 2008
- [c4]Mridul Agarwal, Varsha Balakrishnan, Anshuman Bhuyan, Kyunglok Kim, Bipul C. Paul, Wenping Wang, Bo Yang, Yu Cao, Subhasish Mitra:
Optimized Circuit Failure Prediction for Aging: Practicality and Promise. ITC 2008: 1-10 - 2007
- [c3]Subhasish Mitra, Mridul Agarwal:
Circuit failure prediction to overcome scaled CMOS reliability challenges. ITC 2007: 1-3 - [c2]Mridul Agarwal, Bipul C. Paul, Ming Zhang, Subhasish Mitra:
Circuit Failure Prediction and Its Application to Transistor Aging. VTS 2007: 277-286 - 2006
- [j1]Kanak Agarwal, Mridul Agarwal, Dennis Sylvester, David T. Blaauw:
Statistical interconnect metrics for physical-design optimization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 25(7): 1273-1288 (2006) - 2005
- [c1]Mridul Agarwal, Kanak Agarwal, Dennis Sylvester, David T. Blaauw:
Statistical modeling of cross-coupling effects in VLSI interconnects. ASP-DAC 2005: 503-506
Coauthor Index
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