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2020 – today
- 2024
[c9]Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum:
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. ICLR 2024- [i14]Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng:
Diffusion World Model. CoRR abs/2402.03570 (2024) - 2023
- [j1]Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su:
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? J. Mach. Learn. Res. 24: 262:1-262:59 (2023) - [c8]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. ICLR 2023 - [c7]Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover:
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. ICML 2023: 42339-42362 - [i13]Qinqing Zheng, Matt Le, Neta Shaul, Yaron Lipman, Aditya Grover, Ricky T. Q. Chen:
Guided Flows for Generative Modeling and Decision Making. CoRR abs/2311.13443 (2023) - 2022
- [c6]Qinqing Zheng, Amy Zhang, Aditya Grover:
Online Decision Transformer. ICML 2022: 27042-27059 - [i12]Qinqing Zheng, Amy Zhang, Aditya Grover:
Online Decision Transformer. CoRR abs/2202.05607 (2022) - [i11]Dinghuai Zhang, Aaron C. Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen:
Latent State Marginalization as a Low-cost Approach for Improving Exploration. CoRR abs/2210.00999 (2022) - [i10]Tung Nguyen, Qinqing Zheng, Aditya Grover:
ConserWeightive Behavioral Cloning for Reliable Offline Reinforcement Learning. CoRR abs/2210.05158 (2022) - [i9]Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover:
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. CoRR abs/2210.06518 (2022) - 2021
- [c5]Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie J. Su:
Federated f-Differential Privacy. AISTATS 2021: 2251-2259 - [c4]Arun K. Kuchibhotla, Qinqing Zheng:
Near-Optimal Confidence Sequences for Bounded Random Variables. ICML 2021: 5827-5837 - [i8]Qinqing Zheng, Shuxiao Chen
, Qi Long, Weijie J. Su:
Federated $f$-Differential Privacy. CoRR abs/2102.11158 (2021) - [i7]Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su:
A Theorem of the Alternative for Personalized Federated Learning. CoRR abs/2103.01901 (2021) - 2020
- [c3]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. ICML 2020: 11420-11435 - [i6]Qinqing Zheng, Bor-Yiing Su, Jiyan Yang, Alisson G. Azzolini, Qiang Wu, Ou Jin, Shri Karandikar, Hagay Lupesko, Liang Xiong, Eric Zhou:
ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training. CoRR abs/2003.03477 (2020) - [i5]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. CoRR abs/2003.04493 (2020) - [i4]Arun Kumar Kuchibhotla, Qinqing Zheng:
Near-Optimal Confidence Sequences for Bounded Random Variables. CoRR abs/2006.05022 (2020)
2010 – 2019
- 2016
- [i3]Qinqing Zheng, John D. Lafferty:
Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent. CoRR abs/1605.07051 (2016) - 2015
- [c2]Qinqing Zheng, John D. Lafferty:
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements. NIPS 2015: 109-117 - [c1]Qinqing Zheng, Ryota Tomioka:
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. NIPS 2015: 3106-3113 - [i2]Qinqing Zheng, Ryota Tomioka:
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. CoRR abs/1503.05479 (2015) - [i1]Qinqing Zheng, John D. Lafferty:
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements. CoRR abs/1506.06081 (2015)
Coauthor Index
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last updated on 2024-09-14 01:10 CEST by the dblp team
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