Causally-Regularized-Learning

This repo contains the core code for method described in Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, and Peixuan Chen. 2018. Causally Regularized Learning with Agnostic Data Selection Bias. In 2018 ACM Mul- timedia Conference (MM ’18)

Here is a simple demo showing how it works in Matlab:

% Generate predictor X and outcome Y (binary)
X = 2*round(rand(1000, 20))-1; % 1000 samples and 20 features
beta_true = ones(20, 1);
Y = double(sigmoid(X*beta_true)>=0.5);
lambda0 = 1; %Logistic loss
lambda1 = 0.1; %Balancing loss
lambda2 = 1; %L_2 norm of sample weight
lambda3 = 0; %L_2 norm of beta
lambda4 = 0.001; %L_1 norm of bata
lambda5 = 1; %Normalization of sample weight
MAXITER = 1000;
ABSTOL = 1e-3;
W_init = rand(1000, 1);
beta_init = 0.5*ones(20, 1);
[W, beta, J_loss] = mainFunc(X, Y, ...
        lambda0, lambda1, lambda2, lambda3, lambda4, lambda5,...
        MAXITER, ABSTOL, W_init, beta_init);