Arun Verma

Supervised Regression: Least Square Regression, Maximum Likelihood Least Square Regression, Bayesian Linear Regression, Ridge Regression, LASSO, Support Vector Regression, K-Nearest Neighbors Regression, Locally Linear Regression.
Supervised Classification: Perceptron, Logistic Regression, K-Nearest Neighbors Classification, Support Vector Machines, Neural Networks, Decision Trees, Bagging, Boosting.
Unsupervised Classification: Clustering, Expectation Maximization, K-means Algorithm
Dimensionality Reduction: Principal Component Analysis, Linear Discriminant Analysis

Batch Learning: Training and Testing, Evaluation Measures, Overfitting, Regularization, Theory of Generalization, PAC Learnability, A-PAC Learnability, Bias-Variance Tradeoff, VC Dimension.
Online Learning: Adversarial and Stochastic Settings, Online Learning with Expert Feedback(Weighted Majority), Online Convex Optimization (Follow the Regualized Leader).
Multi-Armed Bandits: Algorithms for Simple and Cumulative Regret (UCB, KL-UCB, KL-LUCB, lil’UCB, EXP3, EXP3.P, EXP3-IX), Multi-armed Bandits with Side Observations (EXP3.G), Multi-armed Bandits with Side Information (LinUCB).