Cours magistraux
le (1h3m4s)
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Nombre de programmes trouvés : 9
Cours magistraux
le (1h1m6s)
Bubeck 2/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (1h18s)
Bubeck 3/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (57m29s)
Bubeck 1/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (57m3s)
Bubeck 9/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (56m22s)
Bubeck 7/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (55m13s)
Bubeck 4/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (49m24s)
Bubeck 8/9 - Some geometric aspects of randomized online decision making
... mathematical/algorithmic tools: gradient descent, mirror descent (i.e., Riemannian gradient descent), probabilistic embedding of metric spaces, some basic results in convex geometry, etc.... Voir la vidéo
Cours magistraux
le (48m4s)
