logistic regression
Logistic regression is a statistical method used for binary classification tasks that models the probability of a categorical outcome based on one or more predictor variables. It is a fundamental algorithm in supervised learning.
- Among Us: A Sandbox for Measuring and Detecting Agentic Deception
- Any-stepsize Gradient Descent for Separable Data under Fenchel–Young Losses
- Ascent Fails to Forget
- Compact Memory for Continual Logistic Regression
- Error Feedback under $(L_0,L_1)$-Smoothness: Normalization and Momentum
- Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
- Rescaled Influence Functions: Accurate Data Attribution in High Dimension