Experimental Design for Nonstationary Optimization
,
Pranshu Malviya,
Maryam Hashemzadeh,
and Sarath Chandar
[paper]
Interpolate: How Resetting Active Neurons can also improve Generalizability in Online Learning
Pranshu Malviya,
,
Maryam Hashemzadeh,
Quentin Fournier,
and Sarath Chandar
[paper]
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer
Rached Bouchoucha,
Ahmed Haj Yahmed,
,
Janarthanan Rajendran,
Amin Nikanjam,
Sarath Chandar,
and Foutse Khomh
International Conference on Software Maintenance and Evolution (ICSME), 2024.
[paper]
Exploring the Plasticity of Neural Network for NLP Tasks in Continual Learning
Maryam Hashemzadeh,
Pranshu Malviya*,
,
and Sarath Chandar
Conference on Lifelong Learning Agents (CoLLAs) Workshop Track, 2024.
Intelligent Switching for Reset-Free RL
,
Janarthanan Rajendran,
Glen Berseth,
and Sarath Chandar
International Conference on Learning Representations (ICLR), 2024.
[paper],
[code]
An Empirical Investigation of the Role of Pre-training in Lifelong Learning
Sanket Vaibhav Mehta,
,
Sarath Chandar,
and Emma Strubell
Journal of Machine Learning Research, 2023.
Theory of Continual Learning Workshop, ICML, 2021
(Spotlight)
[paper],
[code]
Disentangling 3D Prototypical Networks for Few-Shot Concept Learning
Mihir Prabhudesai*,
Shamit Lal*,
,
Hsiao-Yu Tung,
Adam W Harley,
and Katerina Fragkiadaki
International Conference on Learning Representations 2021, 2021.
Object Representations for Learning and Reasoning Workshop. Neurips, 2020
(Spotlight)
[paper],
[code],
[project page]