Search Results for author:
Found 8 papers, 4 papers with code
Meta Distribution Alignment for Generalizable Person Re-Identification
Domain Generalizable (DG) person ReID is a challenging task which trains a model on source domains yet generalizes well on target domains.
Domain Generalization
Generalizable Person Re-identification
+1
A New Accelerated Stochastic Gradient Method with Momentum
In this paper, we propose a novel accelerated stochastic gradient method with momentum, which momentum is the weighted average of previous gradients.
Asymptotic proximal point methods: finding the global minima with linear convergence for a class of multiple minima problems
We propose and analyze asymptotic proximal point (APP) methods to find the global minimizer for a class of nonconvex, nonsmooth, or even discontinuous multiple minima functions.
Optimization and Control Numerical Analysis Numerical Analysis 65K05, 68Q25, 90C26, 90C56
Can speed up the convergence rate of stochastic gradient methods to $\mathcal{O}(1/k^2)$ by a gradient averaging strategy?
In this paper we consider the question of whether it is possible to apply a gradient averaging strategy to improve on the sublinear convergence rates without any increase in storage.
Stochastic gradient-free descents
In this paper we propose stochastic gradient-free methods and accelerated methods with momentum for solving stochastic optimization problems.
Contraction methods for continuous optimization
Motivated by the grid search method and Bayesian optimization, we introduce the concept of contractibility and its applications in model-based optimization.
Optimization and Control Computational Complexity Numerical Analysis Numerical Analysis 65K05, 68Q15, 90C26, 90C56
Sparse residual tree and forest
The hierarchical parallel SRT algorithm is based on both tree decomposition and adaptive radial basis function (RBF) explorations, whereby for each child a sparse and proper RBF refinement is added to the approximation by minimizing the norm of the residual inherited from its parent.
Minima distribution for global optimization
This paper establishes a strict mathematical relationship between an arbitrary continuous function on a compact set and its global minima, like the well-known first order optimality condition for convex and differentiable functions.
