83 citations · 106 across the 3 of their papers we have counts for
3 papers
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…
Primal-Dual Rates and Certificates
Celestine Dünner, Simone Forte, Martin Takáč +1
We propose an algorithm-independent framework to equip existing optimization methods with primal-dual certificates. Such certificates and corresponding rate of convergence guarante…
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework
Virginia Smith, Simone Forte, Michael I. Jordan +1
Despite the importance of sparsity in many large-scale applications, there are few methods for distributed optimization of sparsity-inducing objectives. In this paper, we present a…