Publications by Sarath Chandar
Activity
- Principal Investigator: Jan 2020 - now
Preprints
-
An Empirical Investigation of the Role of Pre-training in Lifelong Learning
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, and Emma Strubell
In ArXiv, 2021.
[arxiv] -
Maximum Reward Formulation In Reinforcement Learning
Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E Taylor, and Sarath Chandar
In arXiv, 2020.
[arXiv]
Conference and Journal Papers
2022
-
TAG: Task-based Accumulated Gradients for Lifelong learning
Pranshu Malviya, Balaraman Ravindran, and Sarath Chandar
Conference on Lifelong Learning Agents (CoLLAs), 2022.
[arxiv], [code] -
Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints
Daphné Lafleur, Sarath Chandar, and Gilles Pesant
Principles and Practice of Constraint Programming (CP), 2022.
-
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Yi Wan*, Ali Rahimi-Kalahroudi*, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, and Harm van Seijen
International Conference on Machine Learning (ICML), 2022.
[arXiv], [code] -
Post-hoc Interpretability for Neural NLP: A Survey
Andreas Madsen, Siva Reddy, and Sarath Chandar
ACM Computing Surveys, 2022.
[arXiv] -
Local Structure Matters Most: Perturbation Study in NLU
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, and Sarath Chandar
Findings of ACL, 2022.
[arxiv] -
Memory Augmented Optimizers for Deep Learning
Paul-Aymeric McRae, Prasanna Parthasarathi, Mido Assran, and Sarath Chandar
International Conference on Learning Representations (ICLR), 2022.
[openreview], [code] -
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks
Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, and Sarath Chandar
AAAI Conference on Artificial Intelligence (AAAI), 2022.
[arXiv], [code]
2021
-
MLMLM: Link Prediction with Mean Likelihood Masked Language Model
Louis Clouatre, Philippe Trempe, Amal Zouaq, and Sarath Chandar
Findings of ACL, 2021.
[arXiv] -
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ?
Prasanna Parthasarathi, Sarath Chandar, and Joelle Pineau
Proceedings of the 22nd Annual SIGdial Meeting on Discourse and Dialogue, 2021.
-
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
Prasanna Parthasarathi, Mohamed Abdelsalam, Joelle Pineau, and Sarath Chandar
Proceedings of the 22nd Annual SIGdial Meeting on Discourse and Dialogue, 2021.
-
Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, and Sarath Chandar
International Conference on Machine Learning (ICML), 2021.
[arXiv], [code] -
A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, and Eduard Hovy
Findings of ACL, 2021.
[arXiv] -
Towered Actor Critic for Handling Multiple Action Types in Reinforcement Learning For Drug Discovery
Sai Krishna Gottipati, Yashaswi Pathak, Boris Sattarov, Sahir, Rohan Nuttall, Mohammad Amini, Matthew E. Taylor, and Sarath Chandar
AAAI Conference on Artificial Intelligence, 2021.
-
IIRC: Incremental Implicitly-Refined Classification
Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani, and Sarath Chandar
Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
[arXiv], [code], [website], [PyPI], [docs]
2020
-
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning
Harm van Seijen, Hadi Nekoei, Evan Racah, and Sarath Chandar
Neural Information Processing Systems (NeurIPS), 2020.
[arXiv], [code] -
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Sai Krishna Gottipati*, Boris Sattarov*, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam MJ Thomas, Simon Blackburn, Connor W Coley, Jian Tang, Sarath Chandar, and Yoshua Bengio
International Conference on Machine Learning (ICML), 2020.
[arXiv]