26th Annual Conference on Neural Information Processing Systems (NIPS), Lake Tahoe 2012

26th Annual Conference on Neural Information Processing Systems (NIPS), Lake Tahoe 2012

24 Lectures · Dec 3, 2012

About

You are invited to participate in the Twenty-Sixth Annual Conference on Neural Information Processing Systems, which is the premier scientific meeting on Neural Computation.

Detailed information can be found at NIPS 2012 Conference homepage.


NIPS Spotlight Sessions videos are available at [[machine_learning_video_abstracts_vol3/]]

NIPS Workshops videos are available at [[nipsworkshops2012_laketahoe]]

Related categories

Uploaded videos:

Posner Lectures

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48:07

Suspicious Coincidences in the Brain

Terrence J. Sejnowski

Jan 16, 2013

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8469 Views

Keynote

Invited Talks

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53:11

Quantum information and the Brain

Scott Aaronson

Jan 16, 2013

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30349 Views

Invited Talk
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43:14

Classification with Deep Invariant Scattering Networks

Stéphane Mallat

Jan 16, 2013

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16422 Views

Invited Talk
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49:44

Signatures of Conscious Processing in the Human Brain

Stanislas Dehaene

Jan 17, 2013

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5404 Views

Invited Talk
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25:19

Dropout: A simple and effective way to improve neural networks

Geoffrey E. Hinton

Jan 16, 2013

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54763 Views

Invited Talk
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18:47

Merck Molecular Activity Challenge

George E. Dahl

Jan 16, 2013

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5492 Views

Invited Talk

Oral Sessions

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15:11

TCA: High Dimensional Principal Component Analysis for non-Gaussian Data

Fang Han

Jan 16, 2013

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5959 Views

Lecture
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16:07

Spectral Learning of General Weighted Automata via Constrained Matrix Completion

Borja Balle

Jan 16, 2013

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3523 Views

Lecture
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18:10

Relax and Randomize: From Value to Algorithms

Karthik Sridharan

Jan 16, 2013

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3410 Views

Lecture
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15:20

A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Tra...

Nicolas Le Roux

Jan 22, 2013

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7416 Views

Lecture
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14:27

Approximating Concavely Parameterized Optimization Problems

Sören Laue

Jan 16, 2013

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3971 Views

Lecture
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16:16

Spectral learning of linear dynamics from generalisedlinear observations with ap...

Lars Buesing

Jan 16, 2013

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3163 Views

Lecture
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15:12

High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Marke...

Hua Wang

Jan 16, 2013

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3928 Views

Lecture
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15:36

Multimodal Learning with Deep Boltzmann Machines

Ruslan Salakhutdinov

Jan 16, 2013

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14983 Views

Lecture
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16:41

Discriminative Learning of Sum-Product Networks

Robert Gens

Jan 16, 2013

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13591 Views

Lecture
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17:59

Augmented-SVM: Automatic space partitioning for combining multiple non-linear dy...

Ashwini Shukla

Jan 16, 2013

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4332 Views

Lecture
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15:16

A Unifying Perspective of Parametric Policy Search Methods for Markov Decision P...

Thomas Furmston

Jan 16, 2013

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2824 Views

Lecture
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21:06

Privacy Aware Learning

John Duchi

Jan 16, 2013

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4169 Views

Lecture
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14:26

Graphical Models via Generalized Linear Models

Eunho Yang

Jan 16, 2013

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5683 Views

Lecture
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19:00

No voodoo here! Learning discrete graphical models via inverse covariance estima...

Po-Ling Loh

Jan 16, 2013

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6431 Views

Lecture
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21:53

Near-Optimal MAP Inference for Determinantal Point Processes

Jennifer A. Gillenwater

Jan 16, 2013

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5793 Views

Lecture
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18:46

Bayesian nonparametric models for bipartite graphs

François Caron

Jan 16, 2013

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3564 Views

Lecture
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18:19

Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making

Angela J. Yu

Jan 16, 2013

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4881 Views

Lecture
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18:07

Gradient Weights help Nonparametric Regressors

Samory Kpotufe

Jan 16, 2013

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3353 Views

Lecture