NIPS 2015

67 Program Highlights »

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

Minimum Weight Perfect Matching via Blossom Belief Propagation

Sungsoo Ahn · Sung-Soo Ahn · Sejun Park · Misha Chertkov · Jinwoo Shin

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

Super-Resolution Off the Grid

Qingqing Huang · Sham Kakade

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

b-bit Marginal Regression

Martin Slawski · Ping Li

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements

CHRISTOS THRAMPOULIDIS · Ehsan Abbasi · Babak Hassibi

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

Optimal Rates for Random Fourier Features

Bharath Sriperumbudur · Zoltan Szabo

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

Submodular Hamming Metrics

Jennifer Gillenwater · Rishabh K Iyer · Bethany Lusch · Rahul Kidambi · Jeff A Bilmes

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Tue Dec 8th 10:10 - 10:35 AM @ Room 210 A

Top-k Multiclass SVM

Maksim Lapin · Matthias Hein · Bernt Schiele

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Distributionally Robust Logistic Regression

Soroosh Shafieezadeh Abadeh · Peyman Esfahani · Daniel Kuhn

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

On some provably correct cases of variational inference for topic models

Pranjal Awasthi · Andrej Risteski

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Extending Gossip Algorithms to Distributed Estimation of U-statistics

Igor Colin · Aurélien Bellet · Joseph Salmon · Stéphan Clémençon

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

The Self-Normalized Estimator for Counterfactual Learning

Adith Swaminathan · Thorsten Joachims

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees

François-Xavier Briol · Chris Oates · Mark Girolami · Michael A Osborne

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma

Murat A. Erdogdu

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization

Xiangru Lian · Yijun Huang · Yuncheng Li · Ji Liu

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Tue Dec 8th 11:35 AM - 12:00 PM @ Room 210 A

Distributed Submodular Cover: Succinctly Summarizing Massive Data

Baharan Mirzasoleiman · Amin Karbasi · Ashwinkumar Badanidiyuru · Andreas Krause

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes

Ryan J Giordano · Tamara Broderick · Michael I Jordan

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Latent Bayesian melding for integrating individual and population models

Mingjun Zhong · Nigel Goddard · Charles Sutton

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width

Christopher M De Sa · Ce Zhang · Kunle Olukotun · Christopher Ré · Christopher Ré

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Automatic Variational Inference in Stan

Alp Kucukelbir · Rajesh Ranganath · Andrew Gelman · David Blei

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Data Generation as Sequential Decision Making

Philip Bachman · Doina Precup

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Stochastic Expectation Propagation

Yingzhen Li · José Miguel Hernández-Lobato · Richard E Turner

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Tue Dec 8th 03:30 - 04:00 PM @ Room 210 A

Deep learning with Elastic Averaging SGD

Sixin Zhang · Anna E Choromanska · Yann LeCun

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

The Human Kernel

Andrew G Wilson · Christoph Dann · Chris Lucas · Eric P Xing

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

On the Pseudo-Dimension of Nearly Optimal Auctions

Jamie H Morgenstern · Tim Roughgarden

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

High-dimensional neural spike train analysis with generalized count linear dynamical systems

YUANJUN GAO · Lars Busing · Krishna V Shenoy · John Cunningham

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

Measuring Sample Quality with Stein's Method

Jackson Gorham · Lester Mackey

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

Biologically Inspired Dynamic Textures for Probing Motion Perception

Jonathan Vacher · Andrew Isaac Meso · Laurent U Perrinet · Gabriel Peyré

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings

Piyush Rai · Changwei Hu · Ricardo Henao · Lawrence Carin

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

Closed-form Estimators for High-dimensional Generalized Linear Models

Eunho Yang · Aurelie C Lozano · Pradeep K Ravikumar

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Tue Dec 8th 05:30 - 06:00 PM @ Room 210 A

Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels

Felipe Tobar · Thang Bui · Richard E Turner

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces

Takashi Takenouchi · Takafumi Kanamori

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection

Jie Wang · Jieping Ye

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Optimal Testing for Properties of Distributions

Jayadev Acharya · Constantinos Daskalakis · Gautam C Kamath

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents

Mithun Chakraborty · Sanmay Das

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Information-theoretic lower bounds for convex optimization with erroneous oracles

Yaron Singer · Jan Vondrak

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff

Ofer Dekel · Ronen Eldan · Tomer Koren

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Accelerated Mirror Descent in Continuous and Discrete Time

Walid Krichene · Alexandre Bayen · Peter L Bartlett

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Wed Dec 9th 10:10 - 10:35 AM @ Room 210 A

Adaptive Online Learning

Dylan J Foster · Alexander Rakhlin · Karthik Sridharan

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Attention-Based Models for Speech Recognition

Jan K Chorowski · Dzmitry Bahdanau · Dmitriy Serdyuk · Kyunghyun Cho · Yoshua Bengio

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Where are they looking?

Adria Recasens · Aditya Khosla · Carl Vondrick · Antonio Torralba

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding

Rie Johnson · Tong Zhang

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Training Very Deep Networks

Rupesh K Srivastava · Klaus Greff · Juergen Schmidhuber

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Deep Convolutional Inverse Graphics Network

Tejas D Kulkarni · William F. Whitney · Pushmeet Kohli · Josh Tenenbaum

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Learning to Segment Object Candidates

Pedro O Pinheiro · Ronan Collobert · Piotr Dollar

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors

Dan Rosenbaum · Yair Weiss

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Wed Dec 9th 11:35 AM - 12:00 PM @ Room 210 A

Spatial Transformer Networks

Max Jaderberg · Karen Simonyan · Andrew Zisserman · koray kavukcuoglu

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

Armand Joulin · Tomas Mikolov

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation

Seunghoon Hong · Hyeonwoo Noh · Bohyung Han

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Action-Conditional Video Prediction using Deep Networks in Atari Games

Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

On-the-Job Learning with Bayesian Decision Theory

Keenon Werling · Arun Tejasvi Chaganty · Percy S Liang · Christopher Manning

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Learning Wake-Sleep Recurrent Attention Models

Jimmy Ba · Ruslan R Salakhutdinov · Roger B Grosse · Brendan J Frey

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Backpropagation for Energy-Efficient Neuromorphic Computing

Steve K Esser · Rathinakumar Appuswamy · Paul Merolla · John Arthur · Dharmendra S Modha

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding

Yuval Harel · Ron Meir · Manfred Opper

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Wed Dec 9th 03:30 - 04:00 PM @ Room 210 A

Color Constancy by Learning to Predict Chromaticity from Luminance

Ayan Chakrabarti

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Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A

Pointer Networks

Oriol Vinyals · Meire Fortunato · Navdeep Jaitly

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Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A

Precision-Recall-Gain Curves: PR Analysis Done Right

Peter Flach · Meelis Kull

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Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A

NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning

Kevin G Jamieson · Lalit Jain · Chris Fernandez · Nicholas J. Glattard · Rob Nowak

Spotlight

Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A

Structured Transforms for Small-Footprint Deep Learning

Vikas Sindhwani · Tara Sainath · Sanjiv Kumar

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Wed Dec 9th 05:40 - 06:00 PM @ Room 210 A

Equilibrated adaptive learning rates for non-convex optimization

Yann Dauphin · Harm de Vries · Yoshua Bengio

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