83 citations · 177 across the 8 of their papers we have counts for
9 papers
Light management in highly-textured perovskite solar cells: From full-device ellipsometry characterization to optical modelling for quantum efficiency optimization
Chenxi Ma, Daming Zheng, Dominique Demaille +4
While perovskite solar cells (PSCs) are now reaching high power conversion efficiencies (PCEs), further performance improvement requires a fine management and an optimization of th…
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy
Majid Jahani, Xi He, Chenxin Ma +4
In this paper, we propose a Distributed Accumulated Newton Conjugate gradiEnt (DANCE) method in which sample size is gradually increasing to quickly obtain a solution whose empiric…
An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning
Chenxin Ma, Martin Jaggi, Frank E. Curtis +2
Distributed optimization algorithms are essential for training machine learning models on very large-scale datasets. However, they often suffer from communication bottlenecks. Conf…
Fast and Safe: Accelerated gradient methods with optimality certificates and underestimate sequences
Majid Jahani, Naga Venkata C. Gudapati, Chenxin Ma +2
In this work we introduce the concept of an Underestimate Sequence (UES), which is motivated by Nesterov's estimate sequence. Our definition of a UES utilizes three sequences, one…
CoCoA: A General Framework for Communication-Efficient Distributed Optimization
Virginia Smith, Simone Forte, Chenxin Ma +3
The scale of modern datasets necessitates the development of efficient distributed optimization methods for machine learning. We present a general-purpose framework for distributed…
Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing
Chenxin Ma, Martin Takáč
In this paper we study inexact dumped Newton method implemented in a distributed environment. We start with an original DiSCO algorithm [Communication-Efficient Distributed Optimiz…