Chenxin Ma

An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning

  • Frank E. Curtis
  • Martin Jaggi
  • Chenxin Ma
  • Nathan Srebro
  • Martin Takac
    • Categories Nonlinear Optimization, Parallel Algorithms

    Distributed optimization algorithms are essential for training machine learning models on very large-scale datasets. However, they often suffer from communication bottlenecks. Confronting this issue, a communication-efficient primal-dual coordinate ascent framework (CoCoA) and its improved variant CoCoA+ have been proposed, achieving a convergence rate of $\mathcal{O}(1/t)$ for solving empirical risk minimization problems with Lipschitz continuous losses. … Read more

    Underestimate Sequences via Quadratic Averaging

  • Naga Venkata Chaitanya Gudapati
  • Rachael Tappenden
  • Majid Jahani
  • Chenxin Ma
  • Martin Takac
    • Categories Nonlinear Optimization, Unconstrained Optimization

    In this work we introduce the concept of an Underestimate Sequence (UES), which is a natural extension of Nesterov’s estimate sequence. Our definition of a UES utilizes three sequences, one of which is a lower bound (or under-estimator) of the objective function. The question of how to construct an appropriate sequence of lower bounds is … Read more