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NIPS Workshops, Lake Tahoe 2013

NIPS Workshops, Lake Tahoe 2013

113 Videos · Dec 9, 2013

About

The Post-Conference Workshop Program covered a wide range of topics from Neuroscience to Machine Learning.

Detailed information can be found at NIPS 2013 Workshops homepage.

Videos

Crowdsourcing: Theory, Algorithms and Applications

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15:50

Social Status and the Design of Optimal Badges

Greg Stoddard

calendar icon Oct 6, 2014 1774 views

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12:18

Adaptive Contract Design for Crowdsourcing

Chien-Ju Ho

calendar icon Oct 6, 2014 1887 views

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17:16

Matching Workers Expertise with Tasks: Incentives in Heterogeneous

Afshin Nikzad

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29:56

Algorithmic Crowdsourcing

Dengyong Zhou

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31:00

Collaborative Decision Making

Devavrat Shah

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33:57

Crowdsourcing knowledge, one billion facts at a time

Evgeniy Gabrilovich

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33:21

Incentive Design for Crowdsourcing: A Game-Theoretic Approach

Arpita Ghosh

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26:52

Crowd-Powered Systems

Michael S. Bernstein

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Deep Learning

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29:49

Two architectures for one-shot learning

Joshua B. Tenenbaum

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23:08

New insights on parameter estimation

Nando de Freitas

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27:09

A PAC-Bayesian Analysis of Dropouts

David McAllester

calendar icon Oct 6, 2014 2110 views

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18:55

Playing Atari with Deep Reinforcement Learning

Volodymyr Mnih

calendar icon Oct 6, 2014 5143 views

Discrete Optimization in Machine Learning: Connecting Theory and Practice

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35:54

Balancing the Explore/Exploit Tradeoff in Interactive Structured Prediction

Yisong Yue

calendar icon Oct 6, 2014 2707 views

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41:27

MAD-Bayes: MAP-based Asymptotic Derivations from Bayes

Michael I. Jordan

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50:50

Summarizing Big Data: A Practical Use for Submodular Functions

Jeff A. Bilmes

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50:17

Tutorial on Discrete Convex Analysis: Basics, DC Programming, and Submodular Wel...

Kazuo Murota

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Large Scale Matrix Analysis and Inference

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27:03

Large-scale matrix operations using a data-flow engine

Matei Zaharia

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31:42

Sketching as a Tool for Numerical Linear Algebra

David P. Woodruff

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21:51

Large Scale Matrix Analysis and Inference

Manfred K. Warmuth

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31:05

Primal-Dual Graph Algorithms for MapReduce

Ashish Goel

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29:27

Learning with Matrix Parameters

Nathan Srebro

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28:30

Efficiently implementing sparsity in learning

Malik Magdon-Ismail

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28:05

Near-Optimal Algorithms for Online Matrix Prediction

Satyen Kale

calendar icon Oct 6, 2014 1894 views

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32:22

Spectral sparsification of graphs: an overview of theory and practical methods

Yiannis Koutis

calendar icon Oct 6, 2014 1637 views

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28:30

Large scale matrix algorithms and matrix completion

Benjamin Recht

calendar icon Oct 6, 2014 1986 views

MLINI-13: Machine Learning and Interpretation in Neuroimaging

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20:20

When brain and behavior disagree: A novel ML approach for handling systematic la...

Marius Kloft

calendar icon Oct 6, 2014 1639 views

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50:51

Dissimilarity Representation for Unsupervised and Supervised Tract Segmentation

Paolo Avesani

calendar icon Oct 6, 2014 1595 views

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41:16

Sparse Modeling in fMRI Analysis

Irina Rish

calendar icon Oct 6, 2014 1767 views

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57:16

The geometry of high-level visual representations

Nikolaus Kriegeskorte

calendar icon Oct 6, 2014 1690 views

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51:27

Building common, high-dimensional models of neural representational spaces using...

James V. Haxby

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28:50

Resting state functional connectivity: perils and promises

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41:57

Predicting Short-Term Cognitive Change from Longitudinal Neuroimaging Analysis

Michael Coen

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21:59

Learning to Classify Psychiatric Disorders based on fMR Images: Autism vs Health...

Sina Ghiassian

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47:08

Speech-based Psychiatric Evaluation

Guillermo A. Cecchi

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20:40

Hyperalignment of Multi-Subject fMRI Data by Synchronized Projections

Raif M. Rustamov

calendar icon Oct 6, 2014 1672 views

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22:16

An oblique approach to prediction of conversion to Alzheimer's Disease with mult...

Jonathan Young

calendar icon Oct 6, 2014 1732 views

Modern Nonparametric Methods in Machine Learning

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31:48

Analysis of the copula correlation matrix for meta-elliptical distributions

Yue Zhao

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41:44

Nonparametric Active Learning

Robert D. Nowak

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42:50

Kernel means and shrinkage

Bernhard Schölkopf

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38:16

The Hidden Convexity of Spectral Clustering

Mikhail Belkin

calendar icon Oct 6, 2014 1941 views

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44:01

Regularization and Computations: Early stopping for Online Learning

Lorenzo Rosasco

calendar icon Oct 6, 2014 1707 views

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40:48

Surprising phenomena in inference for iid p dimensional data for 0<p/n<1 and for...

Peter J. Bickel

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36:39

Laplace operators and regularization Fast algorithms for translation invariant a...

Alex Smola

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NIPS 2013 Workshop on Causality: Large-scale Experiment Design and Inference of Causal Mechanisms

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30:33

Results and analysis of the 2013 ChaLearn cause-effect pair challenge

Isabelle Guyon

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15:43

Experiment Design in Static Models of Dynamic Biological Systems

Karen Sachs

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12:30

Automated Feature Engineering Applied to Causality

Diogo Moitinho de Almeida

calendar icon Oct 6, 2014 2390 views

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14:37

Why Am I Stuck? Token-Level Causal Reasoning for AI and Robotics

Denver Dash

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15:41

Clinical trials with non-adherence and unblinding: a graphical perspective

Lizzie Silver

calendar icon Oct 6, 2014 1829 views

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11:41

Codalab - A new service for data exchange, code execution, benchmarks and reprod...

Evelyne Viegas

calendar icon Oct 6, 2014 1825 views

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27:09

Distinguishing between cause and effect: estimation of causal graphs with two va...

Jonas Peters

calendar icon Oct 6, 2014 1995 views

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15:17

Causal Transportability with Limited Experiments

Elias Bareinboim

calendar icon Oct 6, 2014 1801 views

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17:59

Learning Causal Structure from Undersampled Time Series

David Danks

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39:06

Summary of the challenge results and award distribution

Isabelle Guyon

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44:33

Historical perspective in causal structure learning from observational and exper...

Richard Scheines

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13:24

Conditional distribution variability measures for causality detection

José Adrián Rodríguez Fonollosa

calendar icon Oct 6, 2014 1803 views

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15:05

Path Constraints for Causal Discovery

Frederick Eberhardt

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16:54

A Review of Partially Observable Markov Decision Processes for Causal Modeling

Finale Doshi-Velez

calendar icon Oct 6, 2014 2048 views

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13:45

Bayesian experimental design

Matthias W. Seeger

calendar icon Oct 6, 2014 1896 views

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50:21

Causal inferences from complex observational and randomized studies with time-va...

James Robins

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Output Representation Learning

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27:12

GSNs: Avoiding the Intractability of Marginalization by Learning the Transition ...

Yoshua Bengio

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10:58

Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling

Kihyuk Sohn

calendar icon Oct 6, 2014 1660 views

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18:47

Learning with Marginalized Corruption

Kilian Q. Weinberger

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25:35

DeViSE: A Deep Visual-Semantic Embedding Model

Samy Bengio

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29:05

On the Design of Output Representations in Deep Networks for Speech Recognition

Li Deng

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11:44

Predicting Dialogue Outcomes over Structured Latent Representations

Dan Goldwasser

calendar icon Oct 6, 2014 1448 views

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17:42

Latent Structured Ranking

Jason Weston

calendar icon Oct 6, 2014 1659 views

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35:28

Amortized Integer Linear Programming Inference

Dan Roth

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Data Driven Education

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25:55

What I've Learned about Learning

Peter Norvig

calendar icon Oct 6, 2014 1736 views

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27:32

Discovering and removing barriers to learning

Kenneth R. Koedinger

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26:26

Creating Infinitely Adaptable Courseware

Zoran Popović

calendar icon Oct 6, 2014 1620 views

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27:27

Personalized Learning and Temporal Modeling at Khan Academy

Jascha Sohl-Dickstein

calendar icon Oct 6, 2014 1919 views

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24:35

Opportunities and Challenges for Education Research on Coursera

Andrew Maas

calendar icon Oct 6, 2014 1808 views

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25:32

Demographics and learner behavior in MITx and HarvardX MOOCs

Daniel Seaton

calendar icon Oct 6, 2014 1569 views

Knowledge Extraction from Text (KET)

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29:37

Structured Learning for Mapping Natural Language to Spatial Calculi Models

Parisa Kordjamshidi

calendar icon Oct 6, 2014 1615 views

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28:21

Never-Ending Language Learning (NELL)

Partha Pratim Talukdar

calendar icon Oct 6, 2014 1849 views

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28:42

Quick over of Machine Reading Approaches

Estevam R. Hruschka

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28:23

What should be extracted from text

Mitja Trampuš

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28:34

The Wisdom of the Crowds to Assist Never Ending Learning Tasks through Conversin...

Estevam R. Hruschka

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51:02

Semantic Construction Grammars

Michael Witbrock

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51:21

Knowledge Extraction from Archaeological Texts

Christopher Ré

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01:02:54

Knowledge Extraction From Business Texts

James Hodson

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14:47

Information Retrieval from Clinical Reports

Michel Oleynik

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Learning Faster From Easy Data

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47:02

Follow the leader if you can, Hedge if you must

Tim van Erven

calendar icon Oct 6, 2014 2003 views

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42:30

Optimistic Rates

Nathan Srebro

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24:37

Localization and Adaptation in Online Learning Through Relaxations

Karthik Sridharan

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38:05

Fast rates for the multi-armed bandit

Sébastien Bubeck

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30:51

Selective sampling algorithms for cost-sensitive multiclass prediction

Alekh Agarwal

calendar icon Oct 6, 2014 1819 views

Machine Learning for Sustainability

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20:27

Network Design Problems in Landscape Connectivity Conservation

Bistra Dilkina

calendar icon Oct 6, 2014 1580 views

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27:51

SMART-ISO: High-Dimensional Stochastic Optimization for Renewables Integration

Hugo P. Simao

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33:38

Computational Sustainability

Carla P. Gomes

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29:09

Adaptive management across time and space

Iadine Chadès

calendar icon Oct 6, 2014 1428 views

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25:42

BirdCast: Novel Machine Learning Methods for Understanding Continent-Scale Bird ...

Daniel R. Sheldon

calendar icon Oct 6, 2014 1588 views

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23:45

Large-scale Probabilistic Energy Forecasting

J. Zico Kolter

calendar icon Oct 6, 2014 1480 views

Machine Learning in Computational Biology

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16:07

Identifying Perturbed Genes in the Regulatory Networks from Gene Expression Data

Maxim Grechkin

calendar icon Oct 6, 2014 1648 views

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19:12

Multi-trait genomic selection via multivariate regression with structured regula...

Julien Chiquet

calendar icon Oct 6, 2014 1421 views

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41:05

Multi-view multi-task learning for drug sensitivity prediction

Samuel Kaski

calendar icon Oct 6, 2014 1949 views

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48:00

Genetic variation in gene regulation

Jonathan Pritchard

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17:52

A Poisson-multivariate normal hierarchical model for measuring microbial conditi...

Surojit Biswas

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17:19

Kernel bilinear regression for toxicogenetics

Erwan Scornet

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19:44

A convolutional model of RNA-binding proteins

Andrew Delong

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19:33

Sparse Estimation of Module Gaussian Graphical Models with Applications to Cance...

Safiye Celik

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20:55

Epigenome-Wide Association Studies Without the Need for Cell-Type Composition

James Y. Zou

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20:05

Multisource transfer learning for host-pathogen protein interaction prediction i...

Meghana Kshirsagar

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New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks

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34:00

An Overview of Transfer Learning

Sinno Jialin Pan

calendar icon Oct 6, 2014 3227 views

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33:13

Learning kernels for visual domain adaptation

Fei Sha

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29:13

Nonparametric Bayesian inference using kernel distribution embeddings

Arthur Gretton

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34:28

Sparse Coding for Multi-task and Transfer Learning

Massimiliano Pontil

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36:06

Understanding Domain Adaptation Learning - the good and the not so good

Shai Ben-David

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Workshop on Spectral Learning

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59:47

Discovering Hidden Variables in Noisy-Or Networks

David Sontag

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50:11

Clustering Data: Does Theory Help?

Ravindran Kannan

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39:26

Weighted Spectral Learning and the Efficiency Sharpening Algorithm

Michael Thon

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51:46

Nonparametric Latent Variable Models via Kernel Embedding of Distributions

Le Song

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32:11

Partial Information from Spectral Methods

Percy Liang

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