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Relational Learning with One Network: An Asymptotic Analysis

Published on May 06, 20113971 Views

Rongjing Xiang

Theoretical analysis of structured learning methods has focused primarily on domains where the data consist of {\em independent} (albeit structured) examples. Although the statistical relational learn

AISTATS 2011 - Ft. Lauderdale

Related categories

Machine LearningNetwork Analysis

Chapter list

Relational Learning with One Network: An Asymptotic Analysis00:00
Overview - 100:14
Overview - 200:22
Overview - 300:47
Overview - 401:29
IID vs. Relational Settings - 101:50
IID vs. Relational Settings - 201:57
IID vs. Relational Settings - 302:11
IID vs. Relational Settings - 402:16
IID vs. Relational Settings - 502:39
IID vs. Relational Settings - 602:50
Relational Learning for Single Network Domains - 103:11
Relational Learning for Single Network Domains - 203:21
Relational Learning for Single Network Domains - 303:30
Relational Learning for Single Network Domains - 403:34
Relational Learning for Single Network Domains - 503:34
Relational Learning for Single Network Domains - 603:36
Relational Learning for Single Network Domains - 703:38
Relational Learning for Single Network Domains - 803:40
Learning Markovian Relational Models - 103:49
Learning Markovian Relational Models - 204:05
Learning Markovian Relational Models - 304:07
Learning Markovian Relational Models - 404:35
Learning Markovian Relational Models - 504:45
Learning Markovian Relational Models - 604:47
Learning Markovian Relational Models - 704:51
Learning Markovian Relational Models - 804:58
Learning Markovian Relational Models - 905:05
Learning Markovian Relational Models - 1005:10
Learning Markovian Relational Models - 1105:13
Learning Markovian Relational Models - 1205:16
Learning Markovian Relational Models - 1305:18
Learning Markovian Relational Models - 1405:29
Learning Markovian Relational Models - 1505:33
Learning Markovian Relational Models - 1605:42
Learning Markovian Relational Models - 1705:47
Learning Markovian Relational Models - 1805:50
Learning Markovian Relational Models - 1905:52
Learning Markovian Relational Models - 2006:13
Learning Markovian Relational Models - 2106:22
Learning Markovian Relational Models - 2206:26
Learning Markovian Relational Models - 2306:54
Learning Markovian Relational Models - 2407:02
Learning Markovian Relational Models - 2507:10
Learning Markovian Relational Models - 2607:18
Learning Markovian Relational Models - 2707:28
Learning Markovian Relational Models - 2807:33
Learning Markovian Relational Models - 2907:34
Learning Markovian Relational Models - 3007:36
Learning Markovian Relational Models - 3107:57
Learning Markovian Relational Models - 3208:25
Overview - 508:29
Overview - 608:35
Overview - 709:02
Overview - 809:17
Asymptotic Analysis: Assumptions - 109:27
Asymptotic Analysis: Assumptions - 209:28
Asymptotic Analysis: Assumptions - 309:54
Asymptotic Analysis: Assumptions - 410:06
Asymptotic Analysis: Assumptions - 510:27
Asymptotic Analysis: Assumptions - 610:38
Asymptotic Analysis: Assumptions - 710:48
Consequence of Weak Dependence - 111:12
Consequence of Weak Dependence - 211:20
Consequence of Weak Dependence - 311:30
Consequence of Weak Dependence - 411:32
Consequence of Weak Dependence - 511:40
Consequence of Weak Dependence - 612:08
Consequence of Weak Dependence - 712:17
Consequence of Weak Dependence - 812:27
Consequence of Weak Dependence - 912:35
Consequence of Weak Dependence - 1012:40
Consequence of Weak Dependence - 1112:44
Consequence of Weak Dependence - 1212:56
Consequence of Weak Dependence - 1313:11
Asymptotic Consistency - 113:14
Asymptotic Consistency - 213:32
Asymptotic Consistency - 313:40
Asymptotic Consistency - 413:51
Asymptotic Consistency - 514:09
Asymptotic Consistency - 614:30
Asymptotic Consistency - 715:01
Asymptotic Consistency - 815:24
Asymptotic Consistency - 915:46
Asymptotic Efficiency - 115:52
Asymptotic Efficiency - 215:53
Asymptotic Efficiency - 316:28
Asymptotic Efficiency - 416:33
Asymptotic Efficiency - 516:36
Asymptotic Efficiency - 616:38
Asymptotic Efficiency - 716:40
Asymptotic Efficiency - 816:48
Asymptotic Efficiency - 916:49
Asymptotic Efficiency - 1017:07
Asymptotic Efficiency - 1117:13
Overview - 917:28
Overview - 1017:32
Overview - 1117:50
Overview - 1217:53
Overview - 1317:57
Overview - 1418:28
Constructing PL Components - 118:44
Constructing PL Components - 218:46
Constructing PL Components - 318:51
Constructing PL Components - 418:59
Constructing PL Components - 519:08
Constructing PL Components - 619:29
Mean squared error - 119:50
Mean squared error - 220:03
Mean squared error - 320:06
Mean squared error - 420:23
Mean squared error - 520:28
Mean squared error - 620:31
Mean squared error - 720:38
Facebook Data20:45
Facebook classification results - 121:05
Facebook classification results - 221:15
Facebook classification results - 321:24
Facebook classification results - 421:39
Facebook classification results - 521:49
Conclusions - 121:59
Conclusions - 222:01
Conclusions - 322:12
Conclusions - 422:24
Conclusions - 522:49
Conclusions - 623:12
Thank you23:22