Machine Learning Summer School (MLSS), Cambridge 2009

Bayesian or Frequentist, Which Are You?

author: Michael I. Jordan, Department of Electrical Engineering and Computer Sciences, UC Berkeley
published: Nov. 2, 2009, recorded: September 2009, views: 12592

Slides

Slides
0:00	Are You a Bayesian or a Frequentist?
1:28	Statistical Inference
6:36	Machine Learning
10:11	Decison-Theoretic Perspective -1
13:01	Decison-Theoretic Perspective -2
18:18	Decison-Theoretic Perspective -3
19:55	Coherence and Calibration
25:23	The Bayesian World
27:03	Subjective Bayes
34:03	Objective Bayes
36:44	Frequentist Perspective
39:20	Frequentist Activities
50:35	Outline -1
50:50	Surrogate Loss Functions
52:02	Motivating example: Decentralized Detection
53:18	Decentralized Detection
54:26	Decentralized Detection (cont.)
56:57	Perspectives -1
60:16	f-divergences
61:23	Why the f-divergence?
64:02	Statistical Machine Learning Perspective
64:48	Margin-Based Loss Functions
65:40	Estimation Based on a Convex Surrogate Loss
67:02	Some Theory for Surrogate Loss Functions
68:37	Outline -2
69:38	Setup -1
71:28	Profiling
73:43	Some Examples
74:18	Link -1
75:00	Conjugate Duality
75:49	Link -2
77:12	The Easy Direction
78:20	The Direction Has a Constructive Consequence -1
79:07	Example - Hellinger distance
80:45	Example - Variational distance
81:24	Example - Kullback-Leibler divergence
81:29	Bayes Consistency -1

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