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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

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.

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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