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math.OC2020★ 4 cited
Accelerated Dual-Averaging Primal-Dual Method for Composite Convex Minimization
Conghui Tan, Yuqiu Qian, Shiqian Ma +1
Dual averaging-type methods are widely used in industrial machine learning applications due to their ability to promoting solution structure (e.g., sparsity) efficiently. In this p…
math.OC2018
Stochastic Primal-Dual Method for Empirical Risk Minimization with Per-Iteration Complexity
Conghui Tan, Tong Zhang, Shiqian Ma +1
Regularized empirical risk minimization problem with linear predictor appears frequently in machine learning. In this paper, we propose a new stochastic primal-dual method to solve…
math.OC2016
Barzilai-Borwein Step Size for Stochastic Gradient Descent
Conghui Tan, Shiqian Ma, Yu-Hong Dai +1
One of the major issues in stochastic gradient descent (SGD) methods is how to choose an appropriate step size while running the algorithm. Since the traditional line search techni…