1. Preface

   • Tian-De Guo

   EditorialNotes 13 February 2023 Pages: 243 - 244

2. An Overview of Stochastic Quasi-Newton Methods for Large-Scale Machine Learning

   • Tian-De Guo
   • Yan Liu
   • Cong-Ying Han

   ReviewPaper Open access 25 February 2023 Pages: 245 - 275

   

3. A Mini-Batch Proximal Stochastic Recursive Gradient Algorithm with Diagonal Barzilai–Borwein Stepsize

   • Teng-Teng Yu
   • Xin-Wei Liu
   • Jie Sun

   OriginalPaper 21 October 2022 Pages: 277 - 307

   

4. An Automatic Fuzzy Clustering Algorithm for Discrete Elements

   • Tai Vovan
   • Yen Nguyenhoang
   • Sang Danh

   OriginalPaper 27 January 2022 Pages: 309 - 325

   

5. Randomized Algorithms for Orthogonal Nonnegative Matrix Factorization

   • Yong-Yong Chen
   • Fang-Fang Xu

   OriginalPaper 10 November 2020 Pages: 327 - 345

   

6. A Framework of Convergence Analysis of Mini-batch Stochastic Projected Gradient Methods

   • Jian Gu
   • Xian-Tao Xiao

   OriginalPaper 20 November 2019 Pages: 347 - 369

   

7. A Gradient Descent Method for Estimating the Markov Chain Choice Model

   • Lei Fu
   • Dong-Dong Ge

   OriginalPaper 24 September 2021 Pages: 371 - 381

   

8. Approximate Customized Proximal Point Algorithms for Separable Convex Optimization

   • Hong-Mei Chen
   • Xing-Ju Cai
   • Ling-Ling Xu

   OriginalPaper 27 May 2022 Pages: 383 - 408