Janarthanan Rajendran

According to our database, Janarthanan Rajendran authored at least 31 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Defending against Reverse Preference Attacks is Difficult.

Domenic Rosati, Giles Edkins, Harsh Raj, David Atanasov, Subhabrata Majumdar, Janarthanan Rajendran, Frank Rudzicz, Hassan Sajjad

CoRR, 2024

Fairness Incentives in Response to Unfair Dynamic Pricing.

Jesse Thibodeau, Hadi Nekoei, Afaf Taïk, Janarthanan Rajendran, Golnoosh Farnadi

CoRR, 2024

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale.

Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Toward Debugging Deep Reinforcement Learning Programs with RLExplorer.

Rached Bouchoucha, Ahmed Haj Yahmed, Darshan Patil, Janarthanan Rajendran, Amin Nikanjam, Sarath Chandar, Foutse Khomh

Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2024

Mastering Memory Tasks with World Models.

Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Intelligent Switching for Reset-Free RL.

Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games.

Arjun Vaithilingam Sudhakar, Prasanna Parthasarathi, Janarthanan Rajendran, Sarath Chandar

CoRR, 2023

Replay Buffer With Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning.

Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar

CoRR, 2023

Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning.

Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning.

Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar

Proceedings of the Conference on Lifelong Learning Agents, 2023

Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi.

Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar

Proceedings of the Conference on Lifelong Learning Agents, 2023

Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning.

Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

PatchBlender: A Motion Prior for Video Transformers.

Gabriele Prato, Yale Song, Janarthanan Rajendran, R. Devon Hjelm, Neel Joshi, Sarath Chandar

CoRR, 2022

An Introduction to Lifelong Supervised Learning.

Shagun Sodhani, Mojtaba Faramarzi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed A. Abdelsalam, Janarthanan Rajendran, Sarath Chandar

CoRR, 2022

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods.

Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen

Proceedings of the International Conference on Machine Learning, 2022

2021

On End-to-End Learning of Neural Goal-Oriented Dialog Systems.

Janarthanan Rajendran

PhD thesis, 2021

Understanding the Impact of COVID-19 on Online Mental Health Forums.

Laura Biester, Katie Matton, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea

ACM Trans. Manag. Inf. Syst., 2021

Learning to Learn End-to-End Goal-Oriented Dialog From Related Dialog Tasks.

Janarthanan Rajendran, Jonathan K. Kummerfeld, Satinder Singh

CoRR, 2021

Reinforcement Learning of Implicit and Explicit Control Flow Instructions.

Ethan Brooks, Janarthanan Rajendran, Richard L. Lewis, Satinder Singh

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Meta-Learning Requires Meta-Augmentation.

Janarthanan Rajendran, Alexander Irpan, Eric Jang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Quantifying the Effects of COVID-19 on Mental Health Support Forums.

Laura Biester, Katie Matton, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea

Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020, 2020

How Should an Agent Practice?

Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use.

Janarthanan Rajendran, Jatin Ganhotra, Lazaros C. Polymenakos

Trans. Assoc. Comput. Linguistics, 2019

NE-Table: A Neural key-value table for Named Entities.

Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo, Mo Yu, Satinder Singh, Lazaros Polymenakos

Proceedings of the International Conference on Recent Advances in Natural Language Processing, 2019

Discovery of Useful Questions as Auxiliary Tasks.

Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Named Entities troubling your Neural Methods? Build NE-Table: A neural approach for handling Named Entities.

Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo, Mo Yu, Satinder Singh

CoRR, 2018

Learning End-to-End Goal-Oriented Dialog with Multiple Answers.

Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh, Lazaros Polymenakos

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain.

Janarthanan Rajendran, Aravind S. Lakshminarayanan, Mitesh M. Khapra, P. Prasanna, Balaraman Ravindran

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning.

Janarthanan Rajendran, Mitesh M. Khapra, Sarath Chandar, Balaraman Ravindran

Proceedings of the NAACL HLT 2016, 2016

A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation.

Amrita Saha, Mitesh M. Khapra, Sarath Chandar, Janarthanan Rajendran, Kyunghyun Cho

Proceedings of the COLING 2016, 2016

2015

ADAAPT: A Deep Architecture for Adaptive Policy Transfer from Multiple Sources.

Janarthanan Rajendran, P. Prasanna, Balaraman Ravindran, Mitesh M. Khapra

CoRR, 2015