Course Description

KeyNote and Courses

Keynotes

to be announced

Courses (to be completed)



  • Christopher Bishop
    (Microsoft Research Cambridge) [introductory]
    Introduction to the Key Concepts and Techniques of Machine Learning


    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


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


    Tomas Mikolov
    (Facebook) [introductory]
    Using Neural Networks for Modeling and Representing Natural Languages (with 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


    Navraj Pannu
    (GoDaddy) [introductory/intermediate]
    Deep Learning and Maximum Likelihood in Structural Biology


    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) []
    tba


    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


    Alexey Svyatkovskiy
    (Princeton University) [introductory/intermediate]
    From Natural Language Processing to Machine Learning on Source Code


    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