Все публикации

Mixture-Models and Expectation

Mixture-Models and Expectation Maximization

K-Means Clustering

K-Means Clustering

Cont. Introduction to

Cont. Introduction to Generalized Linear Models

Introduction to Generalized

Introduction to Generalized Linear Models

Cont. Linear Models

Cont. Linear Models of Classification- Logistic Regression

Cont. Probabilistic Generative

Cont. Probabilistic Generative Models

Linear Models of

Linear Models of Classification

Bayesian Linear Regression

Bayesian Linear Regression

Introduction to Linear

Introduction to Linear Regression

Vasileios Maroulas, University

Vasileios Maroulas, University of Tennessee

Priors and Hierarchical

Priors and Hierarchical Bayesian Modeling

Summarizing Posterior Distributions

Summarizing Posterior Distributions and Bayesian Model Selection

Generative Bayesian Models

Generative Bayesian Models for Discrete Data (continued)

Introduction to Machine

Introduction to Machine Learning

Lecture 43- Nonlinear

Lecture 43- Nonlinear Differential Equations and Stability

Feras Saad MIT

Feras Saad MIT CICS Seminar

Lecture 42- Linear

Lecture 42- Linear ODE Systems and Stability, Non-linear ODE Systems

Lec41 - System

Lec41 - System of ODEs

Lec40 - System

Lec40 - System of ODEs

Lec39 - Singular

Lec39 - Singular Sturm-Liouville Problems

Lecture 38 -

Lecture 38 - Sturm-Liouville Theory

Lec37 - Introduction

Lec37 - Introduction to Sturm-Liouville Theory

Lecture 35- The

Lecture 35- The Fourier Convergence Theorem, Separation of Variables and the Heat Diffusion Equation

Lecture 34 Fourier

Lecture 34 Fourier Series and Partial Differential Equations