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Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2012

Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2012

21 Videos · Sep 17, 2012

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 online 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 Workshop website.

Videos

Keynotes

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49:02

Counterfactual Reasoning and Learning Systems

Léon Bottou

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01:01:11

Some Recent Bandit Results

Nicolò Cesa-Bianchi

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52:52

Learning in the Loop

John Langford

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Lectures

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31:47

Online Reinforcement Learning from Concurrent Customer Interaction Sequences

David Silver

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28:45

Multi Period Information Retrieval and Optimal Relevance Feedback using Dynamic ...

Marc Sloan

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29:48

Real-time Decisions in the Real World

Leonard Newnham

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43:33

Multi-Label Learning with Millions of Categories

Manik Varma

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22:07

Large Scale Recommender System for The One Class Problem

Ulrich Paquet

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19:34

Lessons from Exploration and Exploitation Challenges

Jeremie Mary

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36:11

The optimistic principle for online planning in Markov decision processes

Rémi Munos

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30:23

Scalable Tensor Decompositions for Learning Hidden Variable Models

Sham M. Kakade

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27:37

Large-Scale Mining of Medical Text- a Hybrid Statistical/Semantic Approach

Tom Diethe

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32:57

A Top-down Approach to Feature Selection in Reinforcement Learning

Mohammad Ghavamzadeh

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24:49

Bayesian Online Event Detection

David Barber

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23:43

Putting Bayes to Sleep

Wouter M. Koolen

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26:10

Learning from a Few labels and a Stream of Unlabeled Data

Michal Valko

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17:42

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Arthur Guez

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27:21

Asymptotic Statistical Analysis of Time Series: Clustering, Change Point, and Ot...

Daniil Ryabko

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Private
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36:22

Large Scale Image Segmentation for Mapping the Connectivity of Real Biological N...

Srini Turaga

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14:50

Thompson Sampling for the Duelling Bandits Problem

Noel Welsh

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22:40

From Data to Decision: Investigating the Struq Pipeline

Douglas Mcllwraith

calendar icon May 28, 2013 2153 views

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