Janarthanan Rajendran
Janarthanan Rajendran
Assistant Professor, Faculty of Computer Science, Dalhousie University
Verified email at - Homepage
Cited by
Cited by
Meta-learning requires meta-augmentation
J Rajendran, A Irpan, E Jang
Neural Information Processing Systems (NeurIPS), 2020
Discovery of useful questions as auxiliary tasks
V Veeriah, M Hessel, Z Xu, R Lewis, J Rajendran, J Oh, H van Hasselt, ...
Neural Information Processing Systems (NeurIPS), 2019
Attend, adapt and transfer: Attentive deep architecture for adaptive transfer from multiple sources in the same domain
J Rajendran, A Srinivas, MM Khapra, P Prasanna, B Ravindran
International Conference on Learning Representations (ICLR), 2017
Bridge correlational neural networks for multilingual multimodal representation learning
J Rajendran, MM Khapra, S Chandar, B Ravindran
North American Chapter of the Association of Computational Linguistics (NAACL), 2016
Learning end-to-end goal-oriented dialog with multiple answers
J Rajendran, J Ganhotra, S Singh, L Polymenakos
Empirical Methods in Natural Language Processing (EMNLP), 2018
Understanding the impact of COVID-19 on online mental health forums
L Biester, K Matton, J Rajendran, EM Provost, R Mihalcea
ACM Transactions on Management Information Systems (TMIS) 12 (4), 1-28, 2021
Quantifying the effects of COVID-19 on mental health support forums
L Biester, K Matton, J Rajendran, EM Provost, R Mihalcea
Workshop on NLP for COVID-19 at EMNLP, 2020
Learning end-to-end goal-oriented dialog with maximal user task success and minimal human agent use
J Rajendran, J Ganhotra, LC Polymenakos
Transactions of the Association for Computational Linguistics (TACL) 7, 375-386, 2019
A correlational encoder decoder architecture for pivot based sequence generation
A Saha, MM Khapra, S Chandar, J Rajendran, K Cho
International Conference on Computational Linguistics (COLING), 2016
Reinforcement Learning of Implicit and Explicit Control Flow in Instructions
EA Brooks, J Rajendran, RL Lewis, S Singh
International Conference on Machine Learning (ICML), 2021
An introduction to lifelong supervised learning
S Sodhani, M Faramarzi, SV Mehta, P Malviya, M Abdelsalam, ...
arXiv preprint arXiv:2207.04354, 2022
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
Y Wan, A Rahimi-Kalahroudi, J Rajendran, I Momennejad, S Chandar, ...
International Conference on Machine Learning (ICML), 22536-22561, 2022
How Should an Agent Practice?
J Rajendran, R Lewis, V Veeriah, H Lee, S Singh
AAAI Conference on Artificial Intelligence (AAAI) 34 (04), 5454-5461, 2020
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning
H Nekoei, A Badrinaaraayanan, A Sinha, M Amini, J Rajendran, ...
Conference on Lifelong Learning Agents (CoLLAs), 2023
Mastering memory tasks with world models
MR Samsami, A Zholus, J Rajendran, S Chandar
International Conference on Learning Representations (ICLR), 2024
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
X Zhao, Y Pan, C Xiao, S Chandar, J Rajendran
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
NE-Table: A Neural key-value table for Named Entities
J Rajendran, J Ganhotra, X Guo, M Yu, S Singh, L Polymenakos
Recent Advances in Natural Language Processing (RANLP), 2019
How popular are your tweets?
A Saha, J Rajendran, S Shekhar, B Ravindran
Proceedings of the 2014 Recommender Systems Challenge, 66-69, 2014
Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning
A Rahimi-Kalahroudi, J Rajendran, I Momennejad, H van Seijen, ...
Conference on Lifelong Learning Agents, 21-42, 2023
Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games
AV Sudhakar, P Parthasarathi, J Rajendran, S Chandar
arXiv preprint arXiv:2311.07687, 2023
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