virtual MLSS 2020 (Opening Remarks)

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0:00:00 [Opening remark- Virtual MLSS 2020]
0:00:21 Machine Learning Summer School
0:03:24 History
0:04:45 Sponsors
0:05:58 Platinum sponsors' events
0:06:31 Application Statistics
0:08:25 Taken time zones into account,
0:09:02 Structure of virtual MLSS2020
0:09:10 Lectures
0:12:04 Roundtables
0:13:20 Speed-dates
0:14:41 Poster Q&A
0:16:13 Social events
0:17:52 Chartroom & Social media
0:19:18 Social media
0:19:42 virtual MLSS webpage
0:19:58 Virtual MLSS 2020 at Tubingen
0:22:04 Contributors
0:22:14 The MLSS2020 organisation team
0:23:04 The MLSS2020 volunteers
0:23:53 Enjoy our Virtual MLSS2020!
0:26:16 Sponsors
0:27:33 Symbolic, Statistical, Causal AI
0:28:22 Videos
0:30:38 Books of The Times
0:31:49 Cybernetics - 1940s/50s
0:36:17 Figure 2 - Perceptron
0:37:13 Minsky & Papert, 1969
0:37:37 A particular task that could not be learn (Hawkins, 1961)
0:38:03 Perception limitations recognized by Rosenbla
0:38:41 Percepton Convergence Theorem (Novikoff, 1962)
0:39:39 Symbolic Al
0:40:53 Minsky & Papert recall (1988/89)
0:42:14 The "XOR Affair"
0:43:03 Technical content of Perceptions
0:44:01 Is parity important?
0:44:31 Reception of "Perceptrons"
0:45:05 The end of perceptions (cf. Olazaran, 1996)
0:46:43 Predictions of symbolic Al
0:48:42 The Return of Neural Nets
0:49:30 The Return of Neural Nets, II
0:50:52 Machine Learning
0:54:09 Classic AI (rules shaped by humans)
0:54:41 MIT Technology Review
0:55:18 Big Data
0:57:33 Letter - Human-level control through deep reinforcement learning
0:58:20 News & Views - Learning to see and act
0:58:54 Human-level object recognition?
0:59:27 Machine learning uses correlations rather than causality
1:00:14 Adversarial Vulnerability
1:01:16 The New England Journal of Medicine
1:04:02 Dependence vs. Causation
1:05:13 Reichenbach's Common Cause Principle
1:15:09 Summary

Видео virtual MLSS 2020 (Opening Remarks) канала virtual mlss2020