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Data science and the curse of phase transitions
Published on 2016-11-282354 Views
Extracting information, and more generally extracting knowledge from large datasets is arguably one of the main frontiers of modern science, common to a broad variety of disciplines. Bayesian approach
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Presentation
Data science and the curse of phase transitions00:00
Information Theory00:19
More is different01:32
Ferromagnetism03:00
Emergence = collective behavior - 104:22
Emergence = collective behavior - 205:15
Phase transition with many states: spin glases - 105:27
Phase transition with many states: spin glases - 207:52
Phase transition with many states: spin glases - 308:13
Phase transition with many states: spin glases - 408:29
The spin glass cornucopia09:15
Why? - 110:06
Why? - 210:40
Phase Transitions in Information Theory10:48
Information transfer - 111:18
Information transfer - 211:50
Error correction12:15
Shannon's phase transition - 115:03
Shannon's phase transition - 216:57
Shannon's phase transition - 317:36
Shannon's phase transition - 418:44
Efficient codes21:34
Error decoding: inference problem - 122:36
Error decoding: inference problem - 225:11
More Phase Transitions in Error correcting codes25:58
Phase Transitions in Information theory27:23
Compressed sensing27:31
Compressed sensing motivation29:27
Tomography29:53
An example: tomography of binary mixtures - 130:26
An example: tomography of binary mixtures - 230:44
An example: tomography of binary mixtures - 332:15
An example: tomography of binary mixtures - 433:01
An example: tomography of binary mixtures - 533:14
An example: tomography of binary mixtures - 633:52
Compressed sensing as an optimization problem35:01
phase diagram - phase transitions35:34
Alternative approach36:25
Bayesian approach36:50
Analysis of random instances - 137:22
Analysis of random instances - 237:25
Seeding the crystal37:49
Nucleation and seeding - 137:51
Nucleation and seeding - 238:13
Nucleation and seeding - 338:24
Nucleation and seeding - 438:34