KEYNOTE SPEAKERS:

Maria-Florina Balcan (Carnegie Mellon University), Data Driven Clustering

Mark Gales (University of Cambridge), Use of Deep Learning in Non-native Spoken English Assessment

Mihaela van der Schaar (University of Cambridge), Learning Engines for Healthcare: Using Machine Learning to Transform Clinical Practice and Discovery

PROFESSORS AND COURSES:

Aaron Courville (University of Montréal), [introductory/intermediate] Deep Generative Models

Issam El Naqa (University of Michigan), [introductory/intermediate] Deep Learning for Biomedicine

Sergei V. Gleyzer (University of Florida), [introductory/intermediate] Feature Extraction, End-end Deep Learning and Applications to Very Large Scientific Data: Rare Signal Extraction, Uncertainty Estimation and Realtime Machine Learning Applications in Software and Hardware

Vasant Honavar (Pennsylvania State University), [introductory/intermediate] Causal Models for Making Sense of Data

Qiang Ji (Rensselaer Polytechnic Institute), [introductory/intermediate] Probabilistic Deep Learning for Computer Vision

James Kwok (Hong Kong University of Science and Technology), [introductory/intermediate] Compressing Neural Networks

Tomas Mikolov (Facebook), [introductory] Using Neural Networks for Modeling and Representing Natural Languages (with Piotr Bojanowski and Armand Joulin)

Hermann Ney (RWTH Aachen University), [intermediate/advanced] Speech Recognition and Machine Translation: From Statistical Decision Theory to Machine Learning and Deep Neural Networks

Jose C. Principe (University of Florida), [intermediate/advanced] Cognitive Architectures for Object Recognition in Video

Fabio Roli (University of Cagliari), [introductory/intermediate] Adversarial Machine Learning

Björn Schuller (Imperial College London), [introductory/intermediate] Deep Learning for Intelligent Signal Processing

Alex Smola (Amazon), [introductory] Dive into Deep Learning

Sargur Srihari (University at Buffalo), [intermediate/advanced] Explainable Artificial Intelligence

Ponnuthurai N Suganthan (Nanyang Technological University), [introductory/intermediate] Learning Algorithms for Classification, Forecasting and Visual Tracking

Johan Suykens (KU Leuven), [introductory/intermediate] Deep Learning, Neural Networks and Kernel Machines

Bertrand Thirion (INRIA), [introductory] Understanding the Brain with Machine Learning

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

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

Haixun Wang (WeWork), [intermediate] Abstractions, Concepts, and Machine Learning

Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced] Multi-resolution Models for Learning Multilevel Abstract Representations of Text

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

Zhongfei Zhang (Binghamton University), [introductory/advanced] Knowledge Discovery from Complex Data with Deep Learning

OPEN SESSION:

An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to david@irdta.eu by July 14, 2019.