A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements. - Qinqing Zheng; John D. Lafferty (NIPS, 2015)

Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm. - Qinqing Zheng; Ryota Tomioka (NIPS, 2015)

Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent. - Qinqing Zheng; John D. Lafferty (CoRR, 2016)

Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. - Qinqing Zheng; Jinshuo Dong; Qi Long; Weijie J. Su (ICML, 2020)

ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training. - Qinqing Zheng; Bor-Yiing Su; Jiyan Yang; Alisson G. Azzolini; Qiang Wu; Ou Jin; Shri Karandikar; Hagay Lupesko; Liang Xiong; Eric Zhou (CoRR, 2020)

Federated f-Differential Privacy. - Qinqing Zheng; Shuxiao Chen; Qi Long; Weijie J. Su (AISTATS, 2021)

Near-Optimal Confidence Sequences for Bounded Random Variables. - Arun K. Kuchibhotla; Qinqing Zheng (ICML, 2021)

A Theorem of the Alternative for Personalized Federated Learning. - Shuxiao Chen; Qinqing Zheng; Qi Long; Weijie J. Su (CoRR, 2021)

Online Decision Transformer. - Qinqing Zheng; Amy Zhang 001; Aditya Grover (ICML, 2022)

ConserWeightive Behavioral Cloning for Reliable Offline Reinforcement Learning. - Tung Nguyen; Qinqing Zheng; Aditya Grover (CoRR, 2022)

Latent State Marginalization as a Low-cost Approach for Improving Exploration. - Dinghuai Zhang; Aaron C. Courville; Yoshua Bengio; Qinqing Zheng; Amy Zhang 001; Ricky T. Q. Chen (ICLR, 2023)

Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. - Qinqing Zheng; Mikael Henaff; Brandon Amos; Aditya Grover (ICML, 2023)

Guided Flows for Generative Modeling and Decision Making. - Qinqing Zheng; Matt Le 001; Neta Shaul; Yaron Lipman; Aditya Grover; Ricky T. Q. Chen (CoRR, 2023)

Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? - Shuxiao Chen; Qinqing Zheng; Qi Long; Weijie J. Su (J. Mach. Learn. Res., 2023)

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. - Harshit Sikchi; Qinqing Zheng; Amy Zhang 001; Scott Niekum (ICLR, 2024)

Diffusion World Model. - Zihan Ding; Amy Zhang 001; Yuandong Tian; Qinqing Zheng (CoRR, 2024)

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback. - Qinqing Zheng; Mikael Henaff; Amy Zhang 001; Aditya Grover; Brandon Amos (CoRR, 2024)

Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces. - DiJia Su; Sainbayar Sukhbaatar; Michael Rabbat; Yuandong Tian; Qinqing Zheng (ICLR, 2025)

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning. - DiJia Su; Hanlin Zhu; Yingchen Xu; Jiantao Jiao; Yuandong Tian; Qinqing Zheng (CoRR, 2025)

d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning. - Siyan Zhao; Devaansh Gupta; Qinqing Zheng; Aditya Grover (CoRR, 2025)