704 citations · 4.8k across the 117 of their papers we have counts for
4 papers · 1 filter
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…
Screening Rules for Convex Problems
Anant Raj, Jakob Olbrich, Bernd Gärtner +2
We propose a new framework for deriving screening rules for convex optimization problems. Our approach covers a large class of constrained and penalized optimization formulations,…
Pursuits in Structured Non-Convex Matrix Factorizations
Rajiv Khanna, Michael Tschannen, Martin Jaggi
Efficiently representing real world data in a succinct and parsimonious manner is of central importance in many fields. We present a generalized greedy pursuit framework, allowing…
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…