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Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2013

Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2013

20 Videos · Sep 23, 2013

About

The goal of this workshop is to bring together researchers from both industry and academia to share their experiences of implementing large-scale applications of online learning and decision-making. A selection of example applications includes banner advertisement selection, news story selection, targeted email and recommender systems. The workshop will focus on the scalability of current online methods to large-scale implementations that are of practical value to industry. Relevant methods include exploration/exploitation trade-offs (e.g. contextual bandits), large-scale gradient descent, parallelization, collaborative filtering, unsupervised feature learning and dimensionality reduction.

For more information visit the LSOLDM 2013 website.

Videos

Welcome to workshop

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06:43

Welcome

David Silver

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Keynote Talks

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01:04:03

Numerical exploration-exploitation trade-off for large-scale function optimizati...

Rémi Munos

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56:05

Using Machine Learning Powers for Good

Rayid Ghani

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01:06:50

How Watson Learns Superhuman Jeopardy! Strategies

Gerry Tesauro

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Lectures

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30:47

Causal Reasoning and Learning Systems

Elon Portugaly

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34:13

Bayesian Optimization in a Billion Dimensions via Random Embeddings

Nando de Freitas

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28:30

Tensor Factorization for Large-Scale Relational Learning

Maximilian Nickel

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26:29

Challenges in online learning to rank for information retrieval

Katja Hofmann

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26:19

Deep-er Kernels

John Shawe-Taylor

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20:59

A New Convex Relaxation for Tensor Completion

Bernardino Romera-Paredes

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30:38

Real-time news recommendation with rich representation

Marko Grobelnik

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20:39

Online gradient descent for LS regression: Non-asymptotic bounds and application...

Prashanth. L.A.

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29:30

Thompson Sampling: a provably good Bayesian heuristic for bandit problems

Shipra Agrawal

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24:21

Real-time Decisions on Big Data

Leonard Newnham

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18:51

Directing exploratory search with interactive intent modelling

Samuel Kaski

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19:05

DNA matching as an example of Bayesian inference

Bert Kappen

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Private
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32:46

What Makes People Click?

Nello Cristianini

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24:23

Large Scale Model-Based Machine Learning

Tom Diethe

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27:56

Private traits and attributes are predictable from digital records of human beha...

Thore Graepel

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26:59

Bayesian Machine Learning for Controlling Autonomous Systems

Marc Peter Deisenroth

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