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Khimya Khetarpal
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2020 – today
- 2024
- [i18]Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad:
Toward Human-AI Alignment in Large-Scale Multi-Player Games. CoRR abs/2402.03575 (2024) - [i17]Clare Lyle, Zeyu Zheng, Khimya Khetarpal, Hado van Hasselt, Razvan Pascanu, James Martens, Will Dabney:
Disentangling the Causes of Plasticity Loss in Neural Networks. CoRR abs/2402.18762 (2024) - [i16]Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney:
A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. CoRR abs/2406.02035 (2024) - [i15]Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney:
Normalization and effective learning rates in reinforcement learning. CoRR abs/2407.01800 (2024) - 2023
- [j4]Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy:
POMRL: No-Regret Learning-to-Plan with Increasing Horizons. Trans. Mach. Learn. Res. 2023 (2023) - [c11]Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou:
Discovering Object-Centric Generalized Value Functions From Pixels. ICML 2023: 25755-25768 - [i14]Somjit Nath, Gopeshh Raaj Subbaraj, Khimya Khetarpal, Samira Ebrahimi Kahou:
Discovering Object-Centric Generalized Value Functions From Pixels. CoRR abs/2304.13892 (2023) - [i13]Thomas Jiralerspong, Flemming Kondrup, Doina Precup, Khimya Khetarpal:
Forecaster: Towards Temporally Abstract Tree-Search Planning from Pixels. CoRR abs/2310.09997 (2023) - 2022
- [j3]Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup:
Towards Continual Reinforcement Learning: A Review and Perspectives. J. Artif. Intell. Res. 75: 1401-1476 (2022) - [i12]Andrei Cristian Nica, Khimya Khetarpal, Doina Precup:
The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning. CoRR abs/2201.09653 (2022) - [i11]Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy:
POMRL: No-Regret Learning-to-Plan with Increasing Horizons. CoRR abs/2212.14530 (2022) - 2021
- [j2]Arushi Jain
, Khimya Khetarpal
Safe option-critic: learning safety in the option-critic architecture. Knowl. Eng. Rev. 36: e4 (2021) - [c10]Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup:
Variance Penalized On-Policy and Off-Policy Actor-Critic. AAAI 2021: 7899-7907 - [c9]Haiping Wu, Khimya Khetarpal, Doina Precup:
Self-Supervised Attention-Aware Reinforcement Learning. AAAI 2021: 10311-10319 - [c8]Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau:
Learning Robust State Abstractions for Hidden-Parameter Block MDPs. ICLR 2021 - [c7]Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup:
Temporally Abstract Partial Models. NeurIPS 2021: 1979-1991 - [i10]Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup:
Variance Penalized On-Policy and Off-Policy Actor-Critic. CoRR abs/2102.01985 (2021) - [i9]Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodríguez, Matthew D. Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia:
Sequoia: A Software Framework to Unify Continual Learning Research. CoRR abs/2108.01005 (2021) - [i8]Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup:
Temporally Abstract Partial Models. CoRR abs/2108.03213 (2021) - 2020
- [c6]Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert, Pierre-Luc Bacon, Doina Precup:
Options of Interest: Temporal Abstraction with Interest Functions. AAAI 2020: 4444-4451 - [c5]David Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, Michael L. Littman:
Value Preserving State-Action Abstractions. AISTATS 2020: 1639-1650 - [c4]Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup:
What can I do here? A Theory of Affordances in Reinforcement Learning. ICML 2020: 5243-5253 - [i7]Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert, Pierre-Luc Bacon, Doina Precup:
Options of Interest: Temporal Abstraction with Interest Functions. CoRR abs/2001.00271 (2020) - [i6]Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup:
What can I do here? A Theory of Affordances in Reinforcement Learning. CoRR abs/2006.15085 (2020) - [i5]Amy Zhang
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP. CoRR abs/2007.07206 (2020) - [i4]Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup:
Towards Continual Reinforcement Learning: A Review and Perspectives. CoRR abs/2012.13490 (2020)
2010 – 2019
- 2019
- [c3]Khimya Khetarpal:
Learning Generalized Temporal Abstractions across Both Action and Perception. AAAI 2019: 9890-9891 - [c2]Khimya Khetarpal, Doina Precup:
Learning Options with Interest Functions. AAAI 2019: 9955-9956 - 2018
- [i3]Arushi Jain, Khimya Khetarpal, Doina Precup:
Safe Option-Critic: Learning Safety in the Option-Critic Architecture. CoRR abs/1807.08060 (2018) - [i2]Khimya Khetarpal, Doina Precup:
Attend Before you Act: Leveraging human visual attention for continual learning. CoRR abs/1807.09664 (2018) - [i1]Khimya Khetarpal, Shagun Sodhani, Sarath Chandar, Doina Precup:
Environments for Lifelong Reinforcement Learning. CoRR abs/1811.10732 (2018) - 2017
- [j1]Ishwarya Thirunarayanan
Creating Segments and Effects on Comics by Clustering Gaze Data. ACM Trans. Multim. Comput. Commun. Appl. 13(3): 24:1-24:23 (2017) - 2016
- [c1]Khimya Khetarpal, Eakta Jain:
A preliminary benchmark of four saliency algorithms on comic art. ICME Workshops 2016: 1-6
Coauthor Index
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