Deep Learning: Theory, Algorithms, and Applications

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NII Shonan Meeting Seminar 040

Schedule

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Daily Meal Schedule:

. Breakfast: 7:30-9:00
. Lunch: 11:30-13:30
. Dinner: 18:00-19:30

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Welcome, Introduction, Overview, History:

(Pierre Baldi, Tomaso Poggio, and Kenji Fukumizu)

1)????? THEORY (Monday Morning) Chair: Kenji Fukumizu

Talks:

Basic principles of Self-Organization and Supervised L earning (Shun-ichi Amari)

Autoencoders for Structured Data (Alessandro Sperduti)

Deep Targets and Dropout (Pierre Baldi)

Spotlights:

Non Linear Dynamics of Learning in Deep Linear Networks (Surya Ganguli)

Deep Sequential Decision Making? (Takayuki Osogami)

Black Box and Representation Aspects of Neural Networks (Klaus-Robert Muller)

Panel: ?Chair and Speakers

2)????? NEUROBIOLOGY (Monday Afternoon) Chair: Hiroyuki Nakahara

Talks:

Stochasticity of Biological Synapses (Erik De Schutter)

A Mathematical Theory of Semantic Cognition ?(Surya Ganguli)

Learning, Decision-Making, and Neural Coding ?(Hiroyuki? Nakahara)

Spotlights:

Circuits and Large Scale Architecture of the Brain (Shimon Edelman)

?Towards Modelling Cortical Response Properties Using Multilayer Models of Natural Images

(Aapo Hyvärinen)

Artificial Neural Networks versus Biological Neural Networks (Pierre Baldi)

Brain Machine Interfaces (Klaus-Robert Muller)

?Panel :? Chair and Speakers

3)????? ALGORITHMS (Tuesday Morning) Chair: Klaus-Robert Muller

Talks:

What is the Information Content of an Algorithm? (Joachim Buhmann)

M-Theory (Tomaso Poggio)

Generative vs Discriminative Scaling to Big Data (Klaus-Robert Muller)

Spotlights:

Going from Text Analysis to Structural Analysis ?(Michal Rosen Zvi)

Dropout (Sepp Hochreiter)

Long-Short Term Memory Units (Sepp Hochreiter)

Evolutionary/Developmental Neural Networks, Because That’s What Worked For Us (Eric Mjoslness)

Panel:? Chair and Speakers

4)????? SYMBOLIC/SEMANTIC VS STATISTICS/CONNECTIONIST (Tuesday Afternoon) Chair: Paolo Frasconi

Talks:

Languages for Machine Learning: What Role for Neural Networks?? (Paolo Frasconi)

Cognitive Architectures, Expressible as or Hybridized With Neural Networks? and/or Graphical Models

(Eric Mjolsness)

A Design for a Brain?? (Shimon Edelman)

SPECIAL SESSION ON OPEN PROBLEMS (Paolo Frasconi, Shimon Edelman, Eric Mjolsness)

5)????? APPLICATIONS (Wednesday Morning)? Chair: Pierre Baldi

Talks:

Applications in Physics, Chemoinformatics, and? Bioinformatics (Pierre Baldi)

Applications in Genetics and Quantum Chemistry (Klaus-Robert Muller)

Big Data in Neuroscience (Joachim Buhmann)

?Spotlights:

Deep Density-Ratio Estimation (Masashi Sugiyama)

Bayesian Optimization in Materials Informatics (Koji Tsuda)

Decoding EEG, MEG, and EMG Data: Three-way Analysis and Deep Learning (Aapo Hyvärinen)

Large Scale Identification of Brain Cells (Paolo Frasconi)

Panel:? Chair and Speakers

6)??????????? EXCURSION ??(Wednesday Afternoon)? ?and OPEN PROBLEMS

7)??????????? APPLICATIONS? (Thursday Morning)? Chair: Takio Kurita

Talks:

What is Learned by Convolutional Networks for Image Recognition Tasks?? (Takayuki Okatani)

Recent developments of Deep Learning in Natural Language Processing (Kevin Duh)

Limitation of Neural Network Approach in Natural Language Processing (Kunihiko Sadamasa)

Spotlights:

Applications to Health Care (Michal Rosen Zvi)

Expected Applications of Deep Learning (Hideki Asoh)

Wasserstein Means: Efficient Detection of Invariances with Optimal Transport (Marco Cuturi)

Panel: ?Chair and Speakers

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