Schedule

           

 

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Rooms: (P1) = Poludniowa 1, (P2) = Poludniowa 2, (W) = Wschodnia

  22 23 24 25 26
           
08:00-08:45 Reception Open session I - W Industrial session I - W Open session II - W Industrial session II - W
08:45-09:00 Welcome - P1 (08:00-08:45) (08:00-08:45) (08:00-08:45) (08:00-08:45)
           
09:00-10:30 Mikolov -P1 Courville - P1 Ney - W Varoquaux - P2 Kwok - W
  Schuller - P2 El Naqa - W Roli - P2 Vidal - P1 Principe - P2
  Gleyzer - P2 Suykens - P1 Wang - W Srihari - P1
           
11:00-12:30 Smola - P1 Mikolov -P1 Ji - P2 Ney - W Varoquaux - P2
  Suganthan - P2 Schuller - P2 Zhang - P1 Roli - P2 Vidal - P1
  Thirion - W   Suykens - P1 Wang - W
           
  Lunch Lunch Lunch Lunch Lunch
           
13:30-15:00 Courville - P1 Smola - P1 Ney - W Kwok - W Honavar - W
  El Naqa - W Suganthan - P2 Roli - P2 Principe - P2 Xu - P1
  Gleyzer - P2 Thirion - W Suykens - P1 Srihari - P1 Yang - P2
           
15:30-17:00 Mikolov -P1 Courville - P1 Ji - P2 Varoquaux - P2 Kwok - W
  Schuller - P2 El Naqa - W Zhang - P1 Vidal - P1 Principe - P2
    Gleyzer - P2   Wang - W Srihari - P1
           
17:30-19:00 Smola - P1 Ji - P2 Employer session Honavar - W Honavar - W
  Suganthan - P2 Zhang - P1   Xu - P1 Xu - P1
  Thirion - W   Yang - P2 Yang - P2
           
19:15-20:15   Keynote Balcan - P1 Keynote Gales - P1 Keynote van der Schaar - P1  
           
    Dinner with strangers Dinner with strangers Dinner with strangers  


Monday, 22


08:00-08:45

Reception

08:45-09:00

Location: P1 → Welcome

09:00-10:30

Location: P1, Tomas Mikolov - Facebook ⊳ “Using Neural Networks for Modeling and Representing Natural Languages (with Piotr Bojanowski and Armand Joulin)”     introductory

Location: P2, Björn Schuller - Imperial College London ⊳ “Deep Learning for Intelligent Signal Processing”     introductory/intermediate

11:00-12:30

Location: P1, Alex Smola - Amazon ⊳ “Dive into Deep Learning”     introductory

Location: P2, Ponnuthurai N Suganthan - Nanyang Technological University ⊳ “Learning Algorithms for Classification, Forecasting and Visual Tracking”     introductory/intermediate

Location: W, Bertrand Thirion - INRIA ⊳ “Understanding the Brain with Machine Learning”     introductory

12:30-13:30

Lunch

13:30-15:00

Location: P1, Aaron Courville - University of Montréal ⊳ “Deep Generative Models”     introductory/intermediate

Location: W, Issam El Naqa - University of Michigan ⊳ “Deep Learning for Biomedicine”     introductory/intermediate

Location: P2, Sergei V. Gleyzer - University of Florida ⊳ “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”     introductory/intermediate

15:30-17:00

Location: P1, Tomas Mikolov - Facebook ⊳ “Using Neural Networks for Modeling and Representing Natural Languages (with Piotr Bojanowski and Armand Joulin)”     introductory

Location: P2, Björn Schuller - Imperial College London ⊳ “Deep Learning for Intelligent Signal Processing”     introductory/intermediate

17:30-19:00

Location: P1, Alex Smola - Amazon ⊳ “Dive into Deep Learning”     introductory

Location: P2, Ponnuthurai N Suganthan - Nanyang Technological University ⊳ “Learning Algorithms for Classification, Forecasting and Visual Tracking”     introductory/intermediate

Location: W, Bertrand Thirion - INRIA ⊳ “Understanding the Brain with Machine Learning”     introductory



Tuesday, 23


08:00-08:45

Location: W → Open session I

09:00-10:30

Location: P1, Aaron Courville - University of Montréal ⊳ “Deep Generative Models”     introductory/intermediate

Location: W, Issam El Naqa - University of Michigan ⊳ “Deep Learning for Biomedicine”     introductory/intermediate

Location: P2, Sergei V. Gleyzer - University of Florida ⊳ “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”     introductory/intermediate

11:00-12:30

Location: P1, Tomas Mikolov - Facebook ⊳ “Using Neural Networks for Modeling and Representing Natural Languages (with Piotr Bojanowski and Armand Joulin)”     introductory

Location: P2, Björn Schuller - Imperial College London ⊳ “Deep Learning for Intelligent Signal Processing”     introductory/intermediate

12:30-13:30

Lunch

13:30-15:00

Location: P1, Alex Smola - Amazon ⊳ “Dive into Deep Learning”     introductory

Location: P2, Ponnuthurai N Suganthan - Nanyang Technological University ⊳ “Learning Algorithms for Classification, Forecasting and Visual Tracking”     introductory/intermediate

Location: W, Bertrand Thirion - INRIA ⊳ “Understanding the Brain with Machine Learning”     introductory

15:30-17:00

Location: P1, Aaron Courville - University of Montréal ⊳ “Deep Generative Models”     introductory/intermediate

Location: W, Issam El Naqa - University of Michigan ⊳ “Deep Learning for Biomedicine”     introductory/intermediate

Location: P2, Sergei V. Gleyzer - University of Florida ⊳ “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”     introductory/intermediate

17:30-19:00

Location: P2, Qiang Ji - Rensselaer Polytechnic Institute ⊳ “Probabilistic Deep Learning for Computer Vision”     introductory/intermediate

Location: P1, Zhongfei Zhang - Binghamton University ⊳ “Knowledge Discovery from Complex Data with Deep Learning”     introductory/advanced

19:15-20:15

Location: P1 → Keynote Balcan

20:30 - ...

Dinner with strangers


Wednesday, 24


08:00-08:45

Location: W → Industrial session I

09:00-10:30

Location: W, Hermann Ney - RWTH Aachen University ⊳ “Speech Recognition and Machine Translation: From Statistical Decision Theory to Machine Learning and Deep Neural Networks”     intermediate/advanced

Location: P2, Fabio Roli - University of Cagliari ⊳ “Adversarial Machine Learning”     introductory/intermediate

Location: P1, Johan Suykens - KU Leuven ⊳ “Deep Learning, Neural Networks and Kernel Machines”     introductory/intermediate

11:00-12:30

Location: P2, Qiang Ji - Rensselaer Polytechnic Institute ⊳ “Probabilistic Deep Learning for Computer Vision”     introductory/intermediate

Location: P1, Zhongfei Zhang - Binghamton University ⊳ “Knowledge Discovery from Complex Data with Deep Learning”     introductory/advanced

12:30-13:30

Lunch

13:30-15:00

Location: W, Hermann Ney - RWTH Aachen University ⊳ “Speech Recognition and Machine Translation: From Statistical Decision Theory to Machine Learning and Deep Neural Networks”     intermediate/advanced

Location: P2, Fabio Roli - University of Cagliari ⊳ “Adversarial Machine Learning”     introductory/intermediate

Location: P1, Johan Suykens - KU Leuven ⊳ “Deep Learning, Neural Networks and Kernel Machines”     introductory/intermediate

15:30-17:00

Location: P2, Qiang Ji - Rensselaer Polytechnic Institute ⊳ “Probabilistic Deep Learning for Computer Vision”     introductory/intermediate

Location: P1, Zhongfei Zhang - Binghamton University ⊳ “Knowledge Discovery from Complex Data with Deep Learning”     introductory/advanced

17:30-19:00

Employer session

19:15-20:15

Location: P1 → Keynote Gales

20:30 - ...

Dinner with strangers


Thursday, 25


08:00-08:45

Location: W → Open session II

09:00-10:30

Location: P2, Gaël Varoquaux - INRIA ⊳ “Representation Learning in Limited Data Settings”     intermediate

Location: P1, René Vidal - Johns Hopkins University ⊳ “Mathematics of Deep Learning”     intermediate/advanced

Location: W, Haixun Wang - WeWork ⊳ “Abstractions, Concepts, and Machine Learning”     intermediate

11:00-12:30

Location: W, Hermann Ney - RWTH Aachen University ⊳ “Speech Recognition and Machine Translation: From Statistical Decision Theory to Machine Learning and Deep Neural Networks”     intermediate/advanced

Location: P2, Fabio Roli - University of Cagliari ⊳ “Adversarial Machine Learning”     introductory/intermediate

Location: P1, Johan Suykens - KU Leuven ⊳ “Deep Learning, Neural Networks and Kernel Machines”     introductory/intermediate

12:30-13:30

Lunch

13:30-15:00

Location: W, James Kwok - Hong Kong University of Science and Technology ⊳ “Compressing Neural Networks”     introductory/intermediate

Location: P2, Jose C. Principe - University of Florida ⊳ “Cognitive Architectures for Object Recognition in Video”     intermediate/advanced

Location: P1, Sargur Srihari - University at Buffalo ⊳ “Explainable Artificial Intelligence”     intermediate/advanced

15:30-17:00

Location: P2, Gaël Varoquaux - INRIA ⊳ “Representation Learning in Limited Data Settings”     intermediate

Location: P1, René Vidal - Johns Hopkins University ⊳ “Mathematics of Deep Learning”     intermediate/advanced

Location: W, Haixun Wang - WeWork ⊳ “Abstractions, Concepts, and Machine Learning”     intermediate

17:30-19:00

Location: W, Vasant Honavar - Pennsylvania State University ⊳ “Causal Models for Making Sense of Data”     introductory/intermediate

Location: P1, Xiaowei Xu - University of Arkansas, Little Rock ⊳ “Multi-resolution Models for Learning Multilevel Abstract Representations of Text”     introductory/advanced

Location: P2, Ming-Hsuan Yang - University of California, Merced ⊳ “Learning to Track Objects”     intermediate/advanced

19:15-20:15

Location: P1 → Keynote van der Schaar

20:30 - ...

Dinner with strangers


Friday, 26


08:00-08:45

Location: W → Industrial session II

09:00-10:30

Location: W, James Kwok - Hong Kong University of Science and Technology ⊳ “Compressing Neural Networks”     introductory/intermediate

Location: P2, Jose C. Principe - University of Florida ⊳ “Cognitive Architectures for Object Recognition in Video”     intermediate/advanced

Location: P1, Sargur Srihari - University at Buffalo ⊳ “Explainable Artificial Intelligence”     intermediate/advanced

11:00-12:30

Location: P2, Gaël Varoquaux - INRIA ⊳ “Representation Learning in Limited Data Settings”     intermediate

Location: P1, René Vidal - Johns Hopkins University ⊳ “Mathematics of Deep Learning”     intermediate/advanced

Location: W, Haixun Wang - WeWork ⊳ “Abstractions, Concepts, and Machine Learning”     intermediate

12:30-13:30

Lunch

13:30-15:00

Location: W, Vasant Honavar - Pennsylvania State University ⊳ “Causal Models for Making Sense of Data”     introductory/intermediate

Location: P1, Xiaowei Xu - University of Arkansas, Little Rock ⊳ “Multi-resolution Models for Learning Multilevel Abstract Representations of Text”     introductory/advanced

Location: P2, Ming-Hsuan Yang - University of California, Merced ⊳ “Learning to Track Objects”     intermediate/advanced

15:30-17:00

Location: W, James Kwok - Hong Kong University of Science and Technology ⊳ “Compressing Neural Networks”     introductory/intermediate

Location: P2, Jose C. Principe - University of Florida ⊳ “Cognitive Architectures for Object Recognition in Video”     intermediate/advanced

Location: P1, Sargur Srihari - University at Buffalo ⊳ “Explainable Artificial Intelligence”     intermediate/advanced

17:30-19:00

Location: W, Vasant Honavar - Pennsylvania State University ⊳ “Causal Models for Making Sense of Data”     introductory/intermediate

Location: P1, Xiaowei Xu - University of Arkansas, Little Rock ⊳ “Multi-resolution Models for Learning Multilevel Abstract Representations of Text”     introductory/advanced

Location: P2, Ming-Hsuan Yang - University of California, Merced ⊳ “Learning to Track Objects”     intermediate/advanced