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Mathematics
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Mathematics
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336
Nicol Schraudolph
Gradient methods locally optimize an unknown differentiable function, and thus provide the engines that drive much machine learning. Here we'll take a look under the hood, beginning with brief ...
3h 59m 4s |
4 years ago
Videolectures.net
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Operations research
Machine learning
Mathematical optimization
Function (mathematics)
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1126
Jure Leskovec
3h 52m 53s |
4 years ago
Videolectures.net
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Graph theory
Graph (mathematics)
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1180
Lieven Vandenberghe
The lectures will provide an introduction to the theory and applications of convex optimization.
2h 22m 16s |
4 years ago
Videolectures.net
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890
Arnaud Doucet
Parts 4 and 5 of this lecture are presented in
2h 16m 28s |
4 years ago
Videolectures.net
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Monte Carlo method
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1824
Les molécules chimiques présentes dans l'alimentation depuis une cinquantaine d'années pourraient être responsables de l'augmentation de certaines maladies.Plus de 100 000 molécules chimiques ...
1h 52m 39s |
2 years ago
ina fr
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USS Christopher (DE-100)
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584
Nicol Schraudolph
The incorporation of online learning capabilities into real-time computing systems has been hampered by a lack of efficient, scalable optimization algorithms for this purpose: second-order methods ...
1h 51m 44s |
4 years ago
Videolectures.net
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Gradient descent
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Conjugate transpose
Nonlinear system
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1018
Adam Kalai
We consider online learning and its relationship to game theory. In an online decision-making problem, as in Singer's lecture, one typically makes a sequence of decisions and receives feedback ...
1h 37m 46s |
4 years ago
Videolectures.net
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799
Sanjoy Dasgupta
This tutorial will focus on entropy, exponential families, and information projection. We'll start by seeing the sense in which entropy is the only reasonable definition of randomness. We will then ...
1h 35m 21s |
4 years ago
Videolectures.net
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Information theory
Exponential family
Information geometry
Projection (linear algebra)
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343
Dana Scott
1h 26m 21s |
4 years ago
Videolectures.net
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Philosophy of mathematics
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