Get our free extension to see links to code for papers anywhere online!

Add to Chrome

Add to Firefox

Picture for Shuang Qiu

Shuang Qiu

Stochastic Gradient Descent without Full Data Shuffle

Jun 12, 2022
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

Figure 1 for Stochastic Gradient Descent without Full Data Shuffle

Figure 2 for Stochastic Gradient Descent without Full Data Shuffle

Figure 3 for Stochastic Gradient Descent without Full Data Shuffle

Figure 4 for Stochastic Gradient Descent without Full Data Shuffle

* This technical report is an extension of our SIGMOD 2022 paper titled "In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle". https://doi.org/10.1145/3514221.3526150

Access Paper or Ask Questions

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

Feb 25, 2022
Boxiang Lyu, Qinglin Meng, Shuang Qiu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan

Figure 1 for Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

Figure 2 for Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

* The first three authors contribute equally and are listed in alphabetical order

Access Paper or Ask Questions

Safe Screening for Sparse Conditional Random Fields

Nov 27, 2021
Weizhong Zhang, Shuang Qiu

Figure 1 for Safe Screening for Sparse Conditional Random Fields

Figure 2 for Safe Screening for Sparse Conditional Random Fields

Figure 3 for Safe Screening for Sparse Conditional Random Fields

Figure 4 for Safe Screening for Sparse Conditional Random Fields

Access Paper or Ask Questions

On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game

Oct 19, 2021
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang

* ICML 2021

Access Paper or Ask Questions