sebastien guglietta

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Tuning Recurrent Neural Networks with Reinforcement Learning

We are excited to announce our new RL Tuner algorithm, a method for enchancing the performance of an LSTM trained on data using Reinforcement …

Guest Post (Part I): Demystifying Deep Reinforcement Learning - Intel AI

Two years ago, a small company in London called DeepMind uploaded their pioneering paper “Playing Atari with Deep Reinforcement Learning” to Arxiv. …

Neural Networks, Manifolds, and Topology

Posted on April 6, 2014<p>topology, neural networks, deep learning, manifold hypothesis<p>Recently, there’s been a great deal of excitement and interest in …

Attention and Augmented Recurrent Neural Networks

A visual overview of neural attention, and the powerful extensions of neural networks being built on top of it.

Contents — DeepLearning 0.1 documentation

Andrej Karpathy blog

• Jan 20, 2018 (started posting on Medium instead)<br>Yes I'm still around but, I've started posting on Medium instead of here.<br>• Sep 7, 2016 A Survival Guide …

Deep Learning

Home - colah's blog

YouTube

Teaching

UK Universities

Reinforcement Learning

Intersect 2018 Conference: Early Bird tickets now available! Amazing speakers, world-class hiring partners, and more!<p>Free Course<p>by<p>Offered at Georgia …

Deep Learning

Lecture popularity: You need to login to cast your vote.<p>Watch videos: <i>(click on thumbnail to launch)</i><p>Part 1 1:20:02<p>!NOW PLAYING<p>Part 2 1:11:03<p>!NOW …

Machine Learning

Basics of Computational Reinforcement Learning

Lecture popularity: You need to login to cast your vote.<p>Watch videos: <i>(click on thumbnail to launch)</i><p>Part 1 1:24:36<p>!NOW PLAYING<p>Part 2 1:24:13<p>!NOW …

Deep Reinforcement Learning

Lecture popularity: You need to login to cast your vote.<p>Description<p>In this tutorial I will discuss how reinforcement learning (RL) can be combined …

Shape Modeling and Generative Modeling for Learning Dynamics - Hamid Krim Technion lecture

Empirical Intrinsic Geometry for Nonlinear Signal Analysis - Ronen Talmon Technion

Modeling Data Streams Using Sparse Distributed Representations

Blind source separation by sparse decomposition

Signal and Image Classification - Stephane Mallat Technion lecture

Maximum likelihood blind source separation (ICA)

Causal Directions in Noisy Environment

author: Guido Nolte, Fraunhofer Institute for Intelligent Analysis and Information Systems <br>presenter: Andreas Ziehe, Fraunhofer Institute for …

Granger Causality and Dynamic Structural Systems

Lecture popularity: You need to login to cast your vote.<p>Description<p>Using a generally applicable dynamic structural system of equations, we give …

Deep Generative Models

author: Yoshua Bengio, Department of Computer Science and Operations Research, University of Montreal<br>Watch: Deep Generative Models