1 code implementation • 7 Sep 2020 • Yuqiu Qian, Conghui Tan, Danhao Ding, Hui Li, Nikos Mamoulis
Nonnegative matrix factorization (NMF) has been successfully applied in several data mining tasks.
no code implementations • 15 Jan 2020 • Conghui Tan, Yuqiu Qian, Shiqian Ma, Tong Zhang
Dual averaging-type methods are widely used in industrial machine learning applications due to their ability to promoting solution structure (e. g., sparsity) efficiently.
1 code implementation • 11 Oct 2019 • Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu
However, in many social network scenarios, centralized federated learning is not applicable (e. g., a central agent or server connecting all users may not exist, or the communication cost to the central server is not affordable).
no code implementations • NeurIPS 2018 • Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu
Regularized empirical risk minimization problem with linear predictor appears frequently in machine learning.
no code implementations • NeurIPS 2018 • Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu
Regularized empirical risk minimization problem with linear predictor appears frequently in machine learning.
no code implementations • NeurIPS 2016 • Conghui Tan, Shiqian Ma, Yu-Hong Dai, Yuqiu Qian
One of the major issues in stochastic gradient descent (SGD) methods is how to choose an appropriate step size while running the algorithm.