NIPS ´08 Workshop: Algebraic and combinatorial methods in machine learning

Adaptive Fourier-Domain Inference on the Symmetric Group

author: Jonathan Huang, Robotics Institute, School of Computer Science, Carnegie Mellon University

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*Slides*
0:00	Adaptive Fourier Domain Inference on the Symmetric group
0:17	Identity Management [Shin et al., '03]
0:50	Identity Management
1:29	Reasoning with Permutations
2:16	Storage Complexity
2:49	First order summaries (1)
3:20	First order summaries (2)
3:46	The problem with 1st order
4:28	Second order summaries (1)
4:51	Second order summaries (2)
5:18	Et cetera
5:47	The Fourier interpretation
6:48	Fourier coefficient matrices
7:50	Hidden Markov Model Inference (1)
8:58	Hidden Markov Model Inference (2)
9:40	Random walk transition model
10:11	Prediction/Rollup
10:40	Fourier Domain Prediction/Rollup
11:36	Conditioning (1)
12:02	Conditioning (2)
12:54	Kronecker Conditioning
13:50	Dealing with bandlimiting errors
14:23	Tracking with a camera network
15:20	Scaling
16:10	Adaptive Identity Management
17:15	Problems
17:54	First-order Independence
18:56	Joining (1)
19:18	Joining (2)
19:55	Problems
20:02	Splitting
20:49	Marginal Preservation
21:32	Detecting Independence
22:35	First-order independence
23:24	Handling Near-Independence
23:53	Experiments - Accuracy
24:48	Experiments – Running time
24:53	- Question
25:20	Experiments – Running time
26:00	Conclusion
26:34	Questions

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