Topics in Optimization, Spring 2018

Course Outline

Time and location

Time: Tuesday, Friday 12:00 - 1:50pm

Location: DARRIN 236

Instructor

Yangyang Xu

Office: Amos Eaton 310

Office hour: TF 10:30am - 11:30am or by appointment

Email: xuy21@rpi.edu

Programming assignments

Reading materials

  • A fast iterative shrinkage-thresholding algorithm for linear inverse problems, Beck and Teboulle, 2009.

  • Gradient methods for minimizing composite functions, Nesterov, 2012.

  • Convergence rates of inexact proximal-gradient methods for convex optimization, Schmidt, Roux, and Bach, 2011.

  • Proximal Newton-type methods for convex optimization, Lee, Sun, and Saunders, 2012.

  • Robust stochastic approximation approach to stochastic programming, Nemirovski, Juditsky, Lan, and Shapiro, 2009.

  • Stochastic first and zeroth-order methods for nonconvex stochastic programming, Ghadimi and Lan, 2013.

  • Accelerating stochastic gradient descent using predictive variance reduction, Johnson and Zhang, 2013.

  • SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives, Defazio, Bach, and Lacoste-Julien, 2014.

  • Minimizing finite sums with the stochastic average gradient, Schmidt, Roux, and Bach, 2017.

  • Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization, Tseng, 2001.

  • A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion, Xu and Yin, 2013.

  • Efficiency of coordinate descent methods on huge-scale optimization problems, Nesterov, 2012.

  • A unified convergence analysis of block successive minimization methods for nonsmooth optimization, Razaviyayn, Hong, and Luo, 2013.

  • Calculus of the exponent of Kurdyka-Lojasiewicz inequality and its applications to linear convergence of first-order methods, Li and Pong, 2017.

  • Worst-case Complexity of Cyclic Coordinate Descent: O(n^2) Gap with Randomized Version, Sun and Ye, 2016.

  • Analyzing Random Permutations for Cyclic Coordinate Descent, Wright and Lee, 2017.

  • A Primer on Coordinate Descent Algorithms, She, Tu, Xu, and Yin, 2016.