Chaoqi Wang

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Roger GrosseAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Guodong ZhangxAIVerified email at x.ai
SHENGYANG SUNApplied Scientist, NVIDIAVerified email at nvidia.com
Yuxin ChenUniversity of Chicago, Assistant Professor of Computer ScienceVerified email at uchicago.edu
Sanja FidlerUniversity of Toronto, NVIDIAVerified email at cs.toronto.edu
Jiaman LiStanford UniversityVerified email at stanford.edu
Wenyuan ZengUniversity of TorontoVerified email at cs.toronto.edu
Adish SinglaTenure-track Faculty, Max Planck Institute for Software Systems (MPI-SWS), GermanyVerified email at mpi-sws.org
Deng CaiProfessor of Computer Science, Zhejiang UniversityVerified email at cad.zju.edu.cn
Xiuye GuGoogleVerified email at google.com
Yibo JiangPhD, University of ChicagoVerified email at uchicago.edu
Zhe FengGoogle ResearchVerified email at google.com
Ashwinkumar BadanidiyuruGoogle Research Mountain ViewVerified email at google.com
Haifeng XuUniversity of ChicagoVerified email at uchicago.edu
Kevin MurphyResearch Scientist, GoogleVerified email at google.com

Chaoqi Wang

Ph.D. student at University of Chicago

Verified email at uchicago.edu - Homepage

Large language models Machine learning Reinforcement learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Picking Winning Tickets Before Training by Preserving Gradient Flow C Wang, G Zhang, R Grosse International Conference on Learning Representations, 2020	546	2020
Three Mechanisms of Weight Decay Regularization G Zhang, C Wang, B Xu, R Grosse International Conference on Learning Representations, 2018	261	2018
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis C Wang, R Grosse, S Fidler, G Zhang International Conference on Machine Learning, 2019	101	2019
Differentiable Compositional Kernel Learning for Gaussian Processes S Sun, G Zhang, C Wang, W Zeng, J Li, R Grosse International Conference on Machine Learning, 2018	86	2018
A Revisit on Deep Hashings for Large-scale Content-based Image Retrieval D Cai, X Gu, C Wang arXiv preprint arXiv:1711.06016, 2017	16	2017
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations? C Wang, S Sun, R Grosse International Conference on Artificial Intelligence and Statistics, 2020	15	2020
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints C Wang, Y Jiang, C Yang, H Liu, Y Chen International Conference on Learning Representations, 2023	11	2023
Teaching an Active Learner with Contrastive Examples C Wang, A Singla, Y Chen Advances in Neural Information Processing Systems, 2021	7	2021
Active Policy Improvement from Multiple Black-box Oracles X Liu, T Yoneda, C Wang*, M Walter, Y Chen International Conference on Machine Learning, 2023	2	2023
Model-based Policy Optimization under Approximate Bayesian Inference C Wang, Y Chen, K Murphy International Conference on Artificial Intelligence and Statistics, 2023		2023
Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts C Wang, Z Ye, Z Feng, A Badanidiyuru, H Xu Advances in Neural Information Processing Systems, 2023		2023
Iterative Machine Teaching for Black-box Markov Learners C Wang, S Zilles, A Singla, Y Chen International Conference on Machine Learning, Workshop on Theory-of-Mind, 2023		2023

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