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bcd-for-dnns-pytorch

Code for Global Convergence of Block Coordinate Descent in Deep Learning (ICML 2019)

convex_optimization

This is a homework of convex_optimization which implements almost all solutions of LASSO and some solutions of LP, such as cvxpy, gurobi, mosek, gradient descent, proximal primal problem, smoothed primal problem, FISTA, Nesterov second, ADMM and so on. Currently I completed the Chinese 'README', but in the near future, I will try to write an English version.

cubic_reg

Implementation of Nesterov and Polyak's (2006) cubic regularization algorithm and Cartis et al's (2011) adaptive cubic regularization algorithm

cvi_ctm

Conjugate Computation Variational Inference for Correlated Topic Models

drlr_nips2019_exp

The MATLAB source code

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

gerrili1996.github.io

incremental_drsvm

The source code for our NeurIPS (2020) paper "Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine"

jdot

Joint distribution optimal transportation for domain adaptation

lasso_using_pgd

A demo showing how proximal gradient descent and accelerated proximal gradient descent can solve LASSO formulation

libadmm

A Library of ADMM for Sparse and Low-rank Optimization

old_homepage

homepage

overleaf

Sumarising IEEE Document on JPEG standard

subsampled_cubic_regularization

Source code for "Sub-sampled Cubic Regularization for Non-convex Optimization", JM Kohler, A Lucchi, https://arxiv.org/abs/1705.05933

variational-inference

Summary in the Monte Carlo Variational Inference