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Workshop date

Schedule

Saturday 17 December, 2011
*) The Powerpoint presentation of Geoff's talk is now available here.

Morning session [Hierarchical Models and Transfer Learning]: 7.30 - 10.30am


7.30 - 8.00 Introduction, Opening remarks by organizers 
8.00 - 8.20 Josh Tenenbaum (MIT) - Hierarchical learning in human and machines 
8.20 - 8.50 Ruslan Salakhutdinov (University of Toronto) - Learning Hierarchical-Deep Models
8.50 - 9.20 Coffee Break
9.20 - 9.50 Dilan Gorur (UCI) - Scalable nonparametric Bayesian hierarchical Representations
9.50 - 10.10 Spotlights
10.10 - 10.30 Open discussion (afterwards, poster cont'd)

Afternoon session [Deep Learning and Optimization]: 4.00 - 7.30pm

16.00 - 16.10 Summary of Transfer Learning and Optimization Challenges
16.10 - 16.35 [Winner of TL challenge] Ian Goodfellow (University of Montreal) - Spike and Slab Sparse Coding for Unsupervised Feature Discovery
16.35 - 17.00 
[Winner of optimization challenge] Sixin Zhang (NYU) - Averaged Stochastic Gradient Descent for Autoencoders
17.00 - 17.40 Goeff Hinton (University of Toronto) - Why equivariance is better than premature invariance?
17.40 - 18.10 Coffee Break
18.10 - 18.40 Yann LeCun (NYU) - TBA
18.40 - 19.30 Open discussion
19.10 - 19.30 Poster session




List of accepted posters:
Srinath Ravindran and Dennis Bahler: “On Imbalanced Data, Hierarchical Models and Transfer Learning
North Carolina State University

Sheng-Jun Huang, Yang Yu and Zhi-Hua Zhou: “Multi-Label Boosting via Hypothesis Reuse
Nanjing University

Yunlong He, Koray Kavukcuoglu, Yanjun Qi and Haesun Park: “Structured Latent Factor Analysis
Georgia Tech and NEC

Alexandre Passos, Hanna Wallach and Andrew McCallum: “Correlations and Anticorrelations in LDA Inference
University of Massachusetts Amherst

Youssef Mroueh, Tomaso Poggio and Lorenzo Rosasco: “Multi-category and Taxonomy Learning : A Regularization Approach
MIT

Ian J. Goodfellow, Aaron Courville and Yoshua Bengio: “Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery
University of Montreal

Bernardino Romera-Paredes, Massimiliano Pontil and Nadia Berthouze: “Leveraging Different Transfer Learning Assumptions: Shared Features, Hierarchical and Semi-Supervised
University College London

Oriol Vinyals, Daniel Povey. "Krylov Subspace Descent for Deep Learning"
University of Berkeley


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Romera.pdf
(190k)
Quoc Le,
Dec 9, 2011, 3:54 PM
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Quoc Le,
Apr 3, 2012, 2:19 PM
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grenada.ppt
(1839k)
Quoc Le,
Dec 22, 2011, 12:01 AM
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huang.pdf
(1786k)
Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
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mroueh.pdf
(201k)
Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
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Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
Ċ
ď
Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
Ċ
ď
Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
Ċ
ď
Marc'Aurelio Ranzato,
Dec 9, 2011, 3:39 PM
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