Janarthanan Rajendran
Janarthanan Rajendran
Postdoctoral Fellow at Mila - Quebec Artificial Intelligence Institute and University of Montreal
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Zitiert von
Zitiert von
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
Meta-learning requires meta-augmentation
J Rajendran, A Irpan, E Jang
Neural Information Processing Systems (NeurIPS), 2020
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
Quantifying the effects of COVID-19 on mental health support forums
L Biester, K Matton, J Rajendran, EM Provost, R Mihalcea
NLP COVID-19 Workshop, Empirical Methods in Natural Language Processing (EMNLP), 2020
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
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
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
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
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
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
Stability and bifurcation analysis of a pupillary light reflex model
J Rajendran, SS Arutprakasam, AM Warrier
The 27th Chinese Control and Decision Conference (CCDC), 1765-1771, 2015
How popular are your tweets?
A Saha, J Rajendran, S Shekhar, B Ravindran
Proceedings of the 2014 Recommender Systems Challenge, 66-69, 2014
PatchBlender: A Motion Prior for Video Transformers
G Prato, Y Song, J Rajendran, RD Hjelm, N Joshi, S Chandar
arXiv preprint arXiv:2211.14449, 2022
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, 22536-22561, 2022
Staged independent learning: Towards decentralized cooperative multi-agent Reinforcement Learning
H Nekoei, A Badrinaaraayanan, A Sinha, M Amini, J Rajendran, ...
ICLR 2022 Workshop on Gamification and Multiagent Solutions, 2022
Learning to Learn End-to-End Goal-Oriented Dialog From Related Dialog Tasks
J Rajendran, JK Kummerfeld, S Singh
arXiv preprint arXiv:2110.15724, 2021
On End-to-End Learning of Neural Goal-Oriented Dialog Systems
J Rajendran
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