Data, Intelligence and Shortcuts Ensembles for Interactive ... · Machine Learning Applications in...

KeynotesNello Cristianini (University of Bristol) - Data, Intelligence and Shortcuts

Petia Radeva (University of Barcelona) - Uncertainty Modeling and Deep Learning in Food Analysis

Indrė Žliobaitė (University of Helsinki) - Any Hope for Deep Learning in Deep Time?

Courses Ignacio Arganda-Carreras (University of the Basque Country) [introductory/intermediate] Deep Learning for Bioimage Analysis

Thomas G. Dietterich (Oregon State University) [introductory] Machine Learning Methods for Robust Artificial Intelligence

Georgios Giannakis (University of Minnesota) [advanced] Ensembles for Online, Interactive and Deep Learning Machines with

Scalability, and Adaptivity Sergei V. Gleyzer (University of Alabama) [introductory/intermediate] Machine Learning Fundamentals and Their Applications to Very

Large Scientific Data: Rare Signal and Feature Extraction, End-to-end Deep Learning, Uncertainty Estimation and Realtime MachineLearning Applications in Software and Hardware

Çağlar Gülçehre (DeepMind) [intermediate/advanced] Deep Reinforcement Learning

Balázs Kégl (Huawei Technologies) [introductory] Deep Model-based Reinforcement Learning

Ludmila Kuncheva (Bangor University) [intermediate] Classifier Ensembles in the Era of Deep Learning

Vincent Lepetit (ENPC ParisTech) [intermediate] Deep Learning and 3D Geometry

Geert Leus (Delft University of Technology) [introductory/intermediate] Graph Signal Processing: Introduction and Connections to

Distributed Optimization and Deep Learning Andy Liaw (Merck Research Labs) [introductory] Machine Learning and Statistics: Better together

Debora Marks (Harvard Medical School) [intermediate] Protein Design Using Deep Learning

Abdelrahman Mohamed (Facebook AI Research) [introductory/advanced] Recent Advances in Automatic Speech Recognition

Sayan Mukherjee (Duke University) [introductory/intermediate] Integrating Deep Learning with Statistical Modeling

Hermann Ney (RWTH Aachen University) [intermediate/advanced] Speech Recognition and Machine Translation: From Statistical

Decision Theory to Machine Learning and Deep Neural Networks Lyle John Palmer (University of Adelaide) [introductory/advanced] Epidemiology for Machine Learning Investigators

Razvan Pascanu (DeepMind) [intermediate/advanced] Understanding Learning Dynamics in Deep Learning and Deep Reinforcement

Learning Jan Peters (Technical University of Darmstadt) [intermediate] Robot Learning

José C. Príncipe (University of Florida) [intermediate/advanced] Cognitive Architectures for Object Recognition in Video

Björn W. Schuller (Imperial College London) [introductory/intermediate] Deep Signal Processing

Sargur N. Srihari (University at Buffalo) [introductory] Generative Models in Deep Learning

Gaël Varoquaux (INRIA) [intermediate] Representation Learning in Limited Data Settings

René Vidal (Johns Hopkins University) [intermediate/advanced] Mathematics of Deep Learning

Ming-Hsuan Yang (University of California, Merced) [intermediate/advanced] Learning to Track Objects

4th International School on Deep Learning DeepLearn 2021 Winter

Milan, Italy - January 11-15, 2021

Organizers:

Dipartimento di Ingegneria dell'Informazione, Università Politecnicadelle Marche

Institute for Research Development, Training and Advice (IRDTA) –Brussels/London

More info: https://irdta.eu/deeplearn2021w

Data, Intelligence and Shortcuts Ensembles for Interactive ... · Machine Learning Applications in...

Documents

Agente Sonic. Deep reinforcement learning

(Deep) Reinforcement Learning - Computer Vision Lab. …cvlab.postech.ac.kr/.../cse703r_2016s/Deep_Reinforcement_Learning… · (Deep) Reinforcement Learning Kee-Eung Kim School of

Deep Reinforcement Learning that Matters

From Reinforcement Learning to Deep Reinforcement …fagostin/assets/files/...Keywords: Machine learning · Reinforcement learning Deep learning · Deep reinforcement learning 1 Introduction

Deep Reinforcement Learning - Cross Entropy

Deep Learning and Reinforcement Learning Workflows in A.I. · Deep Learning and Reinforcement Learning Workflows in A.I. Jon Cherrie Software Engineering Manager Deep Learning Toolbox

Deep Reinforcement Learning for Crazyhouse · Deep Reinforcement Learning for Crazyhouse MasterthesisbyJohannesCzech Dateofsubmission:December30,2019 1.Review:Prof.Dr.KristianKersting

Deep Reinforcement Learning of Video Games...the eld of machine learning and reinforcement learning, in particular deep reinforcement learning. 1.2.1 Architectural neural network design

Deep Reinforcement Learning An Introduction

Intro to Deep Reinforcement Learning

DEEP FEATURE EXTRACTION FOR SAMPLE-EFFICIENT REINFORCEMENT … · Deep Reinforcement Learning Il deep reinforcement learning (DRL) `e una branca dell’apprendimento per rinforzo

Hierarchical Deep Reinforcement Learning: Integrating ... · Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction ... expected future intrinsic (controller)

Learning about (Deep) Reinforcement Learningsrome.github.io/files/dataphillytalk/data_philly_04022017.pdf · Learning about (Deep) Reinforcement Learning SSccootttt RRoommee romesco

Deep Learning for Reinforcement Learning in · PDF fileDeep Learning for Reinforcement Learning in ... Deep Learning for Reinforcement Learning in Pacman Deep Learning für ... Während

Introduction to Deep Reinforcement Learningwnzhang.net/teaching/cs420/slides/13-deep-rl.pdf · 2020-06-08 · Deep Reinforcement Learning •Deep Reinforcement Learning •leverages

Reinforcement Learning: CNNs and Deep Q Learning

Deep Reinforcement Learning for Robotics

A Deep Reinforcement Learning Chatbot

Reinforcement and deep reinforcement learning for wireless

Tutorial: Deep Reinforcement Learning - Machine Learning ...hunch.net/~beygel/deep_rl_tutorial.pdfTutorial: Deep Reinforcement Learning - Machine Learning