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Audiovisual Mathematics Library

Audiovisual Mathematics Library

Documents 68Q32 3 results

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Model-free control and deep learning - Bellemare, Marc (Author of the conference) | CIRM H

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In this talk I will present some recent developments in model-free reinforcement learning applied to large state spaces, with an emphasis on deep learning and its role in estimating action-value functions. The talk will cover a variety of model-free algorithms, including variations on Q-Learning, and some of the main techniques that make the approach practical. I will illustrate the usefulness of these methods with examples drawn from the Arcade Learning Environment, the popular set of Atari 2600 benchmark domains.[-]
In this talk I will present some recent developments in model-free reinforcement learning applied to large state spaces, with an emphasis on deep learning and its role in estimating action-value functions. The talk will cover a variety of model-free algorithms, including variations on Q-Learning, and some of the main techniques that make the approach practical. I will illustrate the usefulness of these methods with examples drawn from the Arcade ...[+]

68Q32 ; 91A25 ; 68T05

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Multi-armed bandits and beyond - Agrawal, Shipra (Author of the conference) | CIRM H

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In this tutorial I will discuss recent advances in theory of multi-armed bandits and reinforcement learning, in particular the upper confidence bound (UCB) and Thompson Sampling (TS) techniques for algorithm design and analysis.

60J20 ; 68Q32 ; 68T05

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Optimal transport for graphs: definitions, applications to graph-signal processing - Courty, Nicolas (Author of the conference) | CIRM H

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In this talk I will discuss how a variant of the classical optimal transport problem, known as the Gromov-Wasserstein distance, can help in designing learning tasks over graphs, and allow to transpose classical signal processing or data analysis tools such as dictionary learning or online change detection, for learning over those types of structured objects. Both theoretical and practical aspects will be discussed.

68Q32 ; 68T05

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