Lectures related to Latent Tree Learning

Building Robust Ensembles via Margin Boosting

Delves into building robust ensembles through margin boosting for improved adversarial defense in machine learning models.

Dynamic Programming: Bellman-Ford and Dijkstra

Explores dynamic programming with Bellman-Ford, Dijkstra, greedy strategies, and activity scheduling problems.

PCA: Derivation and Optimization

Covers the derivation of PCA projection, error minimization, and eigenvector optimization.

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LU Decomposition Algorithm

Covers the LU decomposition algorithm, transforming a matrix into L and U.

Dynamic Programming: Financial Adviser's Prediction

Covers a dynamic programming algorithm for a financial adviser to maximize the probability of impressing her clients.

Branch and Bound: Formal Description

Covers the Branch and Bound algorithm, focusing on formal description and implementation steps to find optimal integer solutions.

Machine Learning: Fundamentals and Applications

Introduces machine learning basics, covering data segmentation, clustering, classification, and practical applications like image classification and face similarity.