NIPS 2014 - highlights

This year, NIPS is in my home town Montréal!
Here is the highlights https://nips.cc/Conferences/2014/Program/

Most interesting invited talks:

John Carlos Baez

University of California, Riverside

Networks in Climate Science

Cynthia Dwork

Microsoft Research

Privacy in the Land of Plenty

Arunava Majumdar

Google Inc. & Stanford University

Role of Coupled Networks in 21st Century Energy Infrastructure

Yurii Nesterov

Catholic University of Louvain (UCL)

Subgradient Methods for Huge-Scale Optimization Problems

Posner Lectures

Michael Kearns

University of Pennsylvania

Games, Networks, and People

John J. Hopfield

Princeton University

Using the Emergent Dynamics of Attractor Networks for Computation

Friday Dec 12 highlights workshops

• Personalization: Methods and Applications
• Deep Learning and Representation Learning
• Modern Machine Learning and Natural Language Processing
• Learning Semantics

Saturday Dec 13 Workshop

1. Human Propelled Machine Learning
2. Advances in Variational Inference
3. 4th Workshop on Automated Knowledge Base Construction (AKBC)

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more details:

Workshop Friday 12 dec : 8:30am – 6:30pm Friday, December 12, 2014

8:30am – 6:30pm	Yoshua Bengio, Adam Coates, Roland Memisevic, Andrew Y Ng Deep Learning and Representation Learning
8:30am – 6:30pm	Reza Bosagh Zadeh, Ion Stoica, Ameet S Talwalkar Distributed Machine Learning and Matrix Computations

8:30am – 6:30pm

Cedric Archambeau, Antoine Bordes, Leon Bottou, Chris J Burges, David Grangier Learning Semantics

8:30am – 6:30pm

Ankur P Parikh, Avneesh Saluja, Chris Dyer, Eric P Xing Modern Machine Learning and Natural Language Processing

8:30am – 6:30pm

Khalid El-Arini, Yisong Yue, Dilan Gorur Personalization: Methods and Applications

 Workshop Saturday 13 dec : 8:30am – 6:30pm Friday, December 12, 2014

8:30am – 6:30pm	Shakir Mohamed, Tamara Broderick, Charles Blundell, Matthew D Hoffman,David Blei, Michael I Jordan Advances in Variational Inference
8:30am – 6:30pm	Shivani Agarwal, Hossein Azari Soufiani, Guy Bresler, Sewoong Oh, David C Parkes, Arun Rajkumar, Devavrat Shah Analysis of Rank Data: Confluence of Social Choice, Operations Research, and Machine Learning
8:30am – 6:30pm	Richard Baraniuk, Michael C Mozer, Divyanshu Vats, Christoph Studer, Andrew E Waters, Andrew Lan Human Propelled Machine Learning
8:30am – 6:30pm	David S Choi, Aaron Clauset, Edo M Airoldi, Leto Peel, Johan Ugander Networks: From Graphs to Rich Data

Conference other interesting talks:

Tuesday Dec 9th

4:15 – 5:40pm	Oral Session 4Session Chair: Ranzato Marc'Aurelio
	·         Y. Tang, N. Srivastava, R. Salakhutdinov Learning Generative Models with Visual Attention ·           o    J. Yosinski, J. Clune, Y. Bengio, H. Lipson How transferable are features in deep neural networks?

Wednesday Dec 10th

2:00 – 3:30pm	Oral Session 7Session Chair: Geoffrey J Gordon
	·         Posner LectureJohn J. Hopfield Using the Emergent Dynamics of Attractor Networks for Computation