Bayesian or Frequentist, Which Are You? By Michael I. Jordan (Part 1 of 2)

Recorded: September 2009 at the Department of Electrical Engineering and Computer Sciences, UC Berkeley. Part 1 of 2. ______________________________________ download the Slides: http://videolectures.net/site/normal_dl/tag=50814/mlss09uk_jordan_bfway.pdf 0:00 Are You a Bayesian or a Frequentist? 1:28 Statistical Inference 6:37 Machine Learning 10:11 Decison-Theoretic Perspective -1 13:01 Decison-Theoretic Perspective -2 18:19 Decison-Theoretic Perspective -3 19:55 Coherence and Calibration 25:23 The Bayesian World 27:04 Subjective Bayes 34:03 Objective Bayes 36:44 Frequentist Perspective 39:21 Frequentist Activities 50:35 Outline -1 50:50 Surrogate Loss Functions 52:02 Motivating example: Decentralized Detection 53:18 Decentralized Detection 54:27 Decentralized Detection (cont.) 56:57 Perspectives -1 1:00:16 f-divergences 1:01:24 Why the f-divergence? 1:04:03 Statistical Machine Learning Perspective 1:04:48 Margin-Based Loss Functions 1:05:40 Estimation Based on a Convex Surrogate Loss 1:07:02 Some Theory for Surrogate Loss Functions 1:08:38 Outline -2 1:09:39 Setup -1 1:11:28 Profiling 1:13:44 Some Examples 1:14:19 Link -1 1:15:00 Conjugate Duality 1:15:49 Link -2 1:17:12 The Easy Direction 1:18:20 The Direction Has a Constructive Consequence -1 1:19:07 Example - Hellinger distance 1:20:45 Example - Variational distance 1:21:24 Example - Kullback-Leibler divergence 1:21:29 Bayes Consistency -1 _____________________ Source: http://videolectures.net/mlss09uk_jordan_bfway/