13th International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia 2010

13th International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia 2010

27 Lectures · May 13, 2010

About

This is the thirteenth conference conference on Artificial Intelligence and Statistics and the first to be held in Europe. Formerly AISTATS was held every two years. In the future the plan is to hold the meeting each year alternating between North America and Europe. AISTATS is an interdisciplinary gathering of researchers at the intersection of computer science, statistics, and related areas. Since its inception in 1985, the primary goal of this conference has been to broaden research in both of these fields by promoting the exchange of ideas between them. We encourage the submission of all papers which are in keeping with this objective.

More about the event at http://www.aistats.org/

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Uploaded videos:

Welcome Address

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06:04

Welcome

Neil D. Lawrence,

Yee Whye Teh

Jun 03, 2010

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4414 Views

Opening

Invited Talks

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01:12:24

Forensic Statistics: Where are We and Where are We Going?

Richard Gill

Jun 03, 2010

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5095 Views

Invited Talk
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54:12

Approximate Bayesian Computation: What, Why and How?

Simon Tavaré

Jun 17, 2010

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7735 Views

Invited Talk

Network Models

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21:14

Boosted optimization for network classification

Timothy Hancock

Jun 03, 2010

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3598 Views

Lecture
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23:19

Detecting weak but hierarchically-structured patterns in networks

Aarti Singh

Jun 03, 2010

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4208 Views

Lecture

Statistical Learning Theory

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20:46

Function class complexity and cluster structure with applications to transductio...

Guy Lever

Jun 03, 2010

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3362 Views

Lecture
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22:28

Multiclass-multilabel classification with more labels than examples

Ofer Dekel

Jun 03, 2010

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4767 Views

Lecture
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19:18

Empirical Bernstein boosting

Pannaga Shivaswamy

Jun 03, 2010

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4059 Views

Lecture

Bayesian Nonparametrics and Causal Inference

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17:53

Sufficient covariates and linear propensity analysis

Hui Guo

Jun 03, 2010

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3505 Views

Lecture
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17:44

Dirichlet process mixtures of generalised linear models

Lauren A. Hannah

May 20, 2010

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4504 Views

Lecture
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19:11

Bayesian Gaussian process latent variable model

Michalis K. Titsias

Jun 03, 2010

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8421 Views

Lecture

Deep Learning

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24:38

Factored 3-way restricted Boltzmann machines for modeling natural images

Marc’Aurelio Ranzato

Jun 03, 2010

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6049 Views

Lecture
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20:48

Learning the structure of deep sparse graphical models

Hanna M. Wallach

Jun 03, 2010

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7572 Views

Lecture

Approximate Inference

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15:20

Solving the uncapacitated facility location problem using message passing algori...

Nevena Lazic

Jun 03, 2010

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6433 Views

Lecture
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21:42

Dense message passing for sparse principal component analysis

Kevin Sharp

Jun 03, 2010

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4637 Views

Lecture
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22:10

Focused belief propagation for query-specific inference

Anton Chechetka

Jun 03, 2010

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3385 Views

Lecture

Online Learning, Control and Information Theory

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20:25

Exploiting feature covariance in high-dimensional online learning

Justin Ma

Jun 03, 2010

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3939 Views

Lecture
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19:53

REGO: Rank-based estimation of Renyi information using Euclidean graph optimizat...

Barnabás Póczos

Jun 14, 2010

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3339 Views

Lecture
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21:34

Coherent inference on optimal play in game trees

Philipp Hennig

Jun 03, 2010

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3389 Views

Lecture

Kernel Methods

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24:55

Nonlinear functional regression: A functional RKHS approach

Hachem Kadri

Jun 03, 2010

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4015 Views

Lecture
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22:26

On the relation between universality, characteristic kernels and RKHS embedding ...

Bharath K. Sriperumbudur

Jun 03, 2010

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3554 Views

Lecture

Graphical Models and Causal Inference

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27:33

On combining graph-based variance reduction schemes

Vibhav Gogate

Jun 07, 2010

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3300 Views

Lecture
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27:36

Convex structure learning in log-linear models beyond pairwise potentials

Mark Schmidt

Jun 03, 2010

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5941 Views

Lecture
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19:45

Modeling annotator expertise: Learning when everybody knows a bit of something

Yan Yan

Jun 03, 2010

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5589 Views

Lecture

Low-rank Methods and Information Retrieval

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20:27

Fluid dynamics models for low rank discriminant analysis

Yung-Kyun Noh

Jun 03, 2010

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4182 Views

Lecture
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20:37

Reduced-rank hidden Markov models

Byron Boots

Aug 29, 2011

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5443 Views

Lecture
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21:44

Half transductive ranking

Jason Weston

Jun 03, 2010

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3387 Views

Lecture