Chang, Jonathan

11 publications

NeurIPSW 2023 Learning to Generate Better than Your LLM Jonathan Chang, Kianté Brantley, Rajkumar Ramamurthy, Dipendra Misra, Wen Sun

ICML 2022 Learning Bellman Complete Representations for Offline Policy Evaluation Jonathan Chang, Kaiwen Wang, Nathan Kallus, Wen Sun

ICLR 2022 Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh, Albert Webson, Colin Raffel, Stephen Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M Rush

NeurIPS 2021 Mitigating Covariate Shift in Imitation Learning via Offline Data with Partial Coverage Jonathan Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun

NeurIPS 2021 MobILE: Model-Based Imitation Learning from Observation Alone Rahul Kidambi, Jonathan Chang, Wen Sun

JMLR 2017 Joint Label Inference in Networks Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, Sofus A. Macskassy

ICML 2014 Joint Inference of Multiple Label Types in Large Networks Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang, Sofus Macskassy

NeurIPS 2014 Learning a Concept Hierarchy from Multi-Labeled Documents Viet-An Nguyen, Jordan L Ying, Philip Resnik, Jonathan Chang

JMLR 2010 Erratum: SGDQN Is Less Careful than Expected Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang, S. Alex Smith

NeurIPS 2009 Reading Tea Leaves: How Humans Interpret Topic Models Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber, David M. Blei

AISTATS 2009 Relational Topic Models for Document Networks Jonathan Chang, David Blei