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Characterizing the Gap Between Actor-Critic and Policy Gradient

Jun 13, 2021
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans

* ICML 2021 

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3D-NVS: A 3D Supervision Approach for Next View Selection

Dec 03, 2020
Kumar Ashutosh, Saurabh Kumar, Subhasis Chaudhuri

* Submitted to CVPR-21 

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One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL

Oct 27, 2020
Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn

* Accepted at NeurIPS 2020 

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Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification

Oct 25, 2020
Ayush Bhardwaj, Sakshee Pimpale, Saurabh Kumar, Biplab Banerjee

* Preprint. Under consideration at Pattern Recognition Letters 

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Supervised Learning Using a Dressed Quantum Network with "Super Compressed Encoding": Algorithm and Quantum-Hardware-Based Implementation

Jul 20, 2020
Saurabh Kumar, Siddharth Dangwal, Debanjan Bhowmik

* 17 pages, 5 figures, 4 tables 

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Distilling Spikes: Knowledge Distillation in Spiking Neural Networks

May 01, 2020
Ravi Kumar Kushawaha, Saurabh Kumar, Biplab Banerjee, Rajbabu Velmurugan

* Preprint: Manuscript under review 

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Gradient Surgery for Multi-Task Learning

Jan 19, 2020
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn

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Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification

Aug 28, 2019
Saurabh Kumar, Biplab Banerjee, Subhasis Chaudhuri

* Preprint: Manuscript under revision 

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DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Jun 06, 2019
Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare

* 13 pages main text, 16 pages appendix. ICML 2019 

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Statistics and Samples in Distributional Reinforcement Learning

Feb 21, 2019
Mark Rowland, Robert Dadashi, Saurabh Kumar, Rémi Munos, Marc G. Bellemare, Will Dabney

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Dopamine: A Research Framework for Deep Reinforcement Learning

Dec 14, 2018
Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare

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Federated Control with Hierarchical Multi-Agent Deep Reinforcement Learning

Dec 22, 2017
Saurabh Kumar, Pararth Shah, Dilek Hakkani-Tur, Larry Heck

* Hierarchical Reinforcement Learning Workshop at the 31st Conference on Neural Information Processing Systems 

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Learning to Compose Skills

Nov 30, 2017
Himanshu Sahni, Saurabh Kumar, Farhan Tejani, Charles Isbell

* Presented at NIPS 2017 Deep RL Symposium 

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State Space Decomposition and Subgoal Creation for Transfer in Deep Reinforcement Learning

May 24, 2017
Himanshu Sahni, Saurabh Kumar, Farhan Tejani, Yannick Schroecker, Charles Isbell

* 5 pages, 6 figures; 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2017), Ann Arbor, Michigan 

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