Geoff Gordon

10-607 lecture on multivariate modeling

Geoff Gordon

a ^ b implies b ^ a

Geoff Gordon

10-600 prop logic 2

Geoff Gordon

10-600 prop logic 1

Geoff Gordon

10-701 Machine Learning Fall 2013 Lecture 23

Geoff Gordon

10-701 Machine Learning Fall 2013 Lecture 22

Geoff Gordon

10-701 Machine Learning Fall 2013 Lecture 20

Geoff Gordon

10-701 Machine Learning Fall 2013 lecture 19

Geoff Gordon

10-701 Machine Learning Recitation -- Information Theory

Geoff Gordon

10-701 Machine Learning fall 2013 Lecture 18

Geoff Gordon

Machine Learning 10-701 fall 2013 lecture 17

Geoff Gordon

10-701 fall 2013 midterm review session

Geoff Gordon

10-701 Machine Learning Fall 2013 Lecture 10

Geoff Gordon

10-701 Machine Learning Lecture 09

Geoff Gordon

Machine Learning 10-701 Recitation 01

Geoff Gordon

10-701 fall 2013 lecture 04

Geoff Gordon

Lecture 27 Dual Averaging

Geoff Gordon

Lecture 26 Path Algorithms

Geoff Gordon

Lecture 25 Coordinate descent

Geoff Gordon

Lecture 24 Interior point methods

Geoff Gordon

Lecture 23 Interior point methods

Geoff Gordon

Lecture 22 SVM duality, interior point

Geoff Gordon

Lecture 21 QP and cone program duality; support vector machines

Geoff Gordon

Lecture 20 Quadratic programs, cone programs

Geoff Gordon

Lecture 7 Subgradient method continued

Geoff Gordon

Lecture 6 Subgradient method

Geoff Gordon

Lecture 5 Gradient descent revisited

Geoff Gordon

Lecture 9 Acceleration

Geoff Gordon

Lecture 19 ADMM, mirror descent

Geoff Gordon

Lecture 10 Matrix differentials

Geoff Gordon