Chenxin Ma - RankMe

21 papers A* 1A 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Solving nonlinear equation systems based on Fitness-Guided clustering with individual evolutionary differential evolution. Expert Syst. Appl. Yangyang Shen, Huali Sun, Chenxin Ma, Minfu Ma, Chang Gao
2024	J	`jnl`	Analysis of procurement strategies in a two-period fresh product supply chain. Kybernetes Guoli Wang, Chenxin Ma
2023	J	`jnl`	A Practical End-to-End Inventory Management Model with Deep Learning. Manag. Sci. Meng Qi, Yuanyuan Shi, Yongzhi Qi, Chenxin Ma, Rong Yuan, Di Wu, Zuo-Jun Max Shen
2022	J	`jnl`	Detecting the Critical States of Type 2 Diabetes Mellitus Based on Degree Matrix Network Entropy by Cross-Tissue Analysis. Entropy Yingke Yang, Zhuanghe Tian, Mengyao Song, Chenxin Ma, Zhenyang Ge, Peiluan Li
2021	J	`jnl`	An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optim. Methods Softw. Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
2021	J	`jnl`	Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences. Comput. Optim. Appl. Majid Jahani, Naga Venkata C. Gudapati, Chenxin Ma, Rachael Tappenden, Martin Takác
2020	A	`conf`	Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy. AISTATS Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takác
2018	J	`jnl`	Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy. CoRR Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takác
2017	J	`jnl`	An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning. CoRR Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
2017	J	`jnl`	CoCoA: A General Framework for Communication-Efficient Distributed Optimization. J. Mach. Learn. Res. Virginia Smith, Simone Forte, Chenxin Ma, Martin Takác, Michael I. Jordan, Martin Jaggi
2017	—	`conf`	Distributed Inexact Damped Newton Method: Data Partitioning and Work-Balancing. AAAI Workshops Chenxin Ma, Martin Takác
2017	J	`jnl`	Distributed optimization with arbitrary local solvers. Optim. Methods Softw. Chenxin Ma, Jakub Konecný, Martin Jaggi, Virginia Smith, Michael I. Jordan, Peter Richtárik, Martin Takác
2017	J	`jnl`	Underestimate Sequences via Quadratic Averaging. CoRR Chenxin Ma, Naga Venkata C. Gudapati, Majid Jahani, Rachael Tappenden, Martin Takác
2016	J	`jnl`	CoCoA: A General Framework for Communication-Efficient Distributed Optimization. CoRR Virginia Smith, Simone Forte, Chenxin Ma, Martin Takác, Michael I. Jordan, Martin Jaggi
2016	J	`jnl`	Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing. CoRR Chenxin Ma, Martin Takác
2016	J	`jnl`	Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption. J. Mach. Learn. Res. Chenxin Ma, Rachael Tappenden, Martin Takác
2015	A*	`conf`	Adding vs. Averaging in Distributed Primal-Dual Optimization. ICML Chenxin Ma, Virginia Smith, Martin Jaggi, Michael I. Jordan, Peter Richtárik, Martin Takác
2015	J	`jnl`	Adding vs. Averaging in Distributed Primal-Dual Optimization. CoRR Chenxin Ma, Virginia Smith, Martin Jaggi, Michael I. Jordan, Peter Richtárik, Martin Takác
2015	J	`jnl`	Distributed Optimization with Arbitrary Local Solvers. CoRR Chenxin Ma, Jakub Konecný, Martin Jaggi, Virginia Smith, Michael I. Jordan, Peter Richtárik, Martin Takác
2015	J	`jnl`	Linear Convergence of the Randomized Feasible Descent Method Under the Weak Strong Convexity Assumption. CoRR Chenxin Ma, Rachael Tappenden, Martin Takác
2015	J	`jnl`	Partitioning Data on Features or Samples in Communication-Efficient Distributed Optimization? CoRR Chenxin Ma, Martin Takác