Learning Using Local Membership Queries thumbnail
Pause
Mute
Subtitles
Playback speed
0.25
0.5
0.75
1
1.25
1.5
1.75
2
Full screen

Learning Using Local Membership Queries

Published on Aug 09, 20133558 Views

We introduce a new model of membership query (MQ) learning, where the learning algorithm is restricted to query points that are close to random examples drawn from the underlying distribution. The lea

Related categories

Chapter list

Learning using Local Membership Queries00:00
PAC + MQ Learning [Angluin ‘87] - 100:07
PAC + MQ Learning - 101:12
PAC + MQ Learning [Angluin ‘87] - 201:54
PAC + MQ Learning - 202:34
Our Model02:57
PAC + local-MQ Learning03:30
Warmup: 1-local MQs04:23
Our Results(1)05:36
Our Results(2)06:10
Our Results(3)06:30
Learning sparse polynomials - 106:51
Learning sparse polynomials - 206:58
Learning sparse polynomials - 308:01
Learning sparse polynomials - 408:33
Learning sparse polynomials - 509:13
Low degree approximation09:16
Learning sparse polynomials - 610:03
Kushilevitz-Mansour Algorithm - 110:12
Kushilevitz-Mansour Algorithm - 210:38
Kushilevitz-Mansour Algorithm - 311:26
Kushilevitz-Mansour Algorithm - 411:37
Kushilevitz-Mansour Algorithm - 511:59
Our Algorithm - 112:38
Our Algorithm - 213:32
Our Algorithm - 313:38
Our Algorithm - 413:46
Our Algorithm - 514:52
Non-zero-test (x1) - 115:26
Non-zero-test (x1) - 215:48
Non-zero-test (S)16:23
Our Algorithm - 616:35
Our Algorithm - 717:11
Our Algorithm - 817:30
Conclusions17:34
Open Problems18:00
Thank You18:48