NeurIPS 2012

370 papers

Dimensionality Dependent PAC-Bayes Margin Bound

Chi Jin, Liwei Wang

A Generative Model for Parts-based Object Segmentation

S. Eslami, Christopher Williams

Link Prediction in Graphs with Autoregressive Features

Emile Richard, Stephane Gaiffas, Nicolas Vayatis

Scaled Gradients on Grassmann Manifolds for Matrix Completion

Thanh Ngo, Yousef Saad

Learning with Recursive Perceptual Representations

Oriol Vinyals, Yangqing Jia, Li Deng, Trevor Darrell

Spectral Learning of General Weighted Automata via Constrained Matrix Completion

Borja Balle, Mehryar Mohri

MCMC for continuous-time discrete-state systems

Vinayak Rao, Yee W. Teh

Cost-Sensitive Exploration in Bayesian Reinforcement Learning

Dongho Kim, Kee-eung Kim, Pascal Poupart

Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making

Pradeep Shenoy, Angela J. Yu

Image Denoising and Inpainting with Deep Neural Networks

Junyuan Xie, Linli Xu, Enhong Chen

Near-Optimal MAP Inference for Determinantal Point Processes

Jennifer Gillenwater, Alex Kulesza, Ben Taskar

Joint Modeling of a Matrix with Associated Text via Latent Binary Features

Xianxing Zhang, Lawrence Carin

Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses

Po-ling Loh, Martin J. Wainwright

Large Scale Distributed Deep Networks

Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin

Augment-and-Conquer Negative Binomial Processes

Mingyuan Zhou, Lawrence Carin

Factorial LDA: Sparse Multi-Dimensional Text Models

Michael Paul, Mark Dredze

Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data

Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs

Aharon Birnbaum, Shai S. Shwartz

Symmetric Correspondence Topic Models for Multilingual Text Analysis

Kosuke Fukumasu, Koji Eguchi, Eric P. Xing

Mixability in Statistical Learning

Tim V. Erven, Peter Grünwald, Mark D. Reid, Robert C. Williamson

Compressive Sensing MRI with Wavelet Tree Sparsity

Chen Chen, Junzhou Huang

Bayesian Hierarchical Reinforcement Learning

Feng Cao, Soumya Ray

Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification

Yung-kyun Noh, Frank Park, Daniel D. Lee

Active Learning of Model Evidence Using Bayesian Quadrature

Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts

Spiking and saturating dendrites differentially expand single neuron computation capacity

Romain Cazé, Mark Humphries, Boris S. Gutkin

Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison

Tianbao Yang, Yu-feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou

Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing

Shinsuke Koyama

Entropy Estimations Using Correlated Symmetric Stable Random Projections

Ping Li, Cun-hui Zhang

Structured Learning of Gaussian Graphical Models

Karthik Mohan, Mike Chung, Seungyeop Han, Daniela Witten, Su-in Lee

How Prior Probability Influences Decision Making: A Unifying Probabilistic Model

Yanping Huang, Timothy Hanks, Mike Shadlen, Abram L. Friesen, Rajesh P. Rao

The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes

Simon Lyons, Amos J. Storkey, Simo Särkkä

Co-Regularized Hashing for Multimodal Data

Yi Zhen, Dit-Yan Yeung

Hamming Distance Metric Learning

Mohammad Norouzi, David J Fleet, Ruslan Salakhutdinov

A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation

Aaron Defazio, Tibério S. Caetano

Localizing 3D cuboids in single-view images

Jianxiong Xiao, Bryan Russell, Antonio Torralba

Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button

Joan Fruitet, Alexandra Carpentier, Maureen Clerc, Rémi Munos

Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions

Alekh Agarwal, Sahand Negahban, Martin J. Wainwright

Discriminative Learning of Sum-Product Networks

Robert Gens, Pedro Domingos

Efficient and direct estimation of a neural subunit model for sensory coding

Brett Vintch, Andrew Zaharia, J Movshon, Eero P. Simoncelli

Inverse Reinforcement Learning through Structured Classification

Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin

Relax and Randomize : From Value to Algorithms

Sasha Rakhlin, Ohad Shamir, Karthik Sridharan

Learning with Partially Absorbing Random Walks

Xiao-ming Wu, Zhenguo Li, Anthony M. So, John Wright, Shih-fu Chang

On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking

Clément Calauzènes, Nicolas Usunier, Patrick Gallinari

Identifiability and Unmixing of Latent Parse Trees

Daniel J. Hsu, Sham M. Kakade, Percy Liang

Fast Variational Inference in the Conjugate Exponential Family

James Hensman, Magnus Rattray, Neil D. Lawrence

Phoneme Classification using Constrained Variational Gaussian Process Dynamical System

Hyunsin Park, Sungrack Yun, Sanghyuk Park, Jongmin Kim, Chang D. Yoo

Feature Clustering for Accelerating Parallel Coordinate Descent

Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin

Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression

Piyush Rai, Abhishek Kumar, Hal Daume

Neurally Plausible Reinforcement Learning of Working Memory Tasks

Jaldert Rombouts, Pieter Roelfsema, Sander M. Bohte

Causal discovery with scale-mixture model for spatiotemporal variance dependencies

Zhitang Chen, Kun Zhang, Laiwan Chan

Volume Regularization for Binary Classification

Koby Crammer, Tal Wagner

Efficient Sampling for Bipartite Matching Problems

Maksims Volkovs, Richard S. Zemel

The topographic unsupervised learning of natural sounds in the auditory cortex

Hiroki Terashima, Masato Okada

Parametric Local Metric Learning for Nearest Neighbor Classification

Jun Wang, Alexandros Kalousis, Adam Woznica

Learning from the Wisdom of Crowds by Minimax Entropy

Dengyong Zhou, Sumit Basu, Yi Mao, John C. Platt

Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images

Dan Ciresan, Alessandro Giusti, Luca M. Gambardella, Jürgen Schmidhuber

Bayesian active learning with localized priors for fast receptive field characterization

Mijung Park, Jonathan W Pillow, Jonathan W. Pillow

Sparse Approximate Manifolds for Differential Geometric MCMC

Ben Calderhead, Mátyás A. Sustik

Putting Bayes to sleep

Dmitry Adamskiy, Manfred K. Warmuth, Wouter M. Koolen

Non-linear Metric Learning

Dor Kedem, Stephen Tyree, Fei Sha, Gert R. Lanckriet, Kilian Q. Weinberger

Bayesian Nonparametric Modeling of Suicide Attempts

Francisco Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz

Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions

Alexandra Carpentier, Rémi Munos

Nonparanormal Belief Propagation (NPNBP)

Gal Elidan, Cobi Cario

Interpreting prediction markets: a stochastic approach

Rafael M. Frongillo, Nicolas Della Penna, Mark D. Reid

Ancestor Sampling for Particle Gibbs

Fredrik Lindsten, Thomas Schön, Michael I. Jordan

Modelling Reciprocating Relationships with Hawkes Processes

Charles Blundell, Jeff Beck, Katherine A. Heller

Transferring Expectations in Model-based Reinforcement Learning

Trung Nguyen, Tomi Silander, Tze Y. Leong

Convolutional-Recursive Deep Learning for 3D Object Classification

Richard Socher, Brody Huval, Bharath Bath, Christopher D. Manning, Andrew Y. Ng

Fusion with Diffusion for Robust Visual Tracking

Yu Zhou, Xiang Bai, Wenyu Liu, Longin J. Latecki

Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions

Neil Burch, Marc Lanctot, Duane Szafron, Richard G. Gibson

Meta-Gaussian Information Bottleneck

Melanie Rey, Volker Roth

Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task

Jenna Wiens, Eric Horvitz, John V. Guttag

Deep Representations and Codes for Image Auto-Annotation

Ryan Kiros, Csaba Szepesvári

Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models

Ke Jiang, Brian Kulis, Michael I. Jordan

Collaborative Ranking With 17 Parameters

Maksims Volkovs, Richard S. Zemel

Learning optimal spike-based representations

Ralph Bourdoukan, David Barrett, Sophie Deneve, Christian K. Machens

CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem

Henrik Ohlsson, Allen Yang, Roy Dong, Shankar Sastry

Emergence of Object-Selective Features in Unsupervised Feature Learning

Adam Coates, Andrej Karpathy, Andrew Y. Ng

Learning Partially Observable Models Using Temporally Abstract Decision Trees

Erik Talvitie

No-Regret Algorithms for Unconstrained Online Convex Optimization

Brendan Mcmahan, Matthew Streeter

Multiple Operator-valued Kernel Learning

Hachem Kadri, Alain Rakotomamonjy, Philippe Preux, Francis R. Bach

Neuronal Spike Generation Mechanism as an Oversampling, Noise-shaping A-to-D converter

Dmitri B. Chklovskii, Daniel Soudry

Dual-Space Analysis of the Sparse Linear Model

Yi Wu, David P. Wipf

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Arthur Guez, David Silver, Peter Dayan

A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound

Shusen Wang, Zhihua Zhang

Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space

Yanyan Lan, Jiafeng Guo, Xueqi Cheng, Tie-yan Liu

Recognizing Activities by Attribute Dynamics

Weixin Li, Nuno Vasconcelos

Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA

C. M. Niu, Sirish Nandyala, Won J. Sohn, Terence Sanger

A lattice filter model of the visual pathway

Karol Gregor, Dmitri B. Chklovskii

Learning about Canonical Views from Internet Image Collections

Elad Mezuman, Yair Weiss

Imitation Learning by Coaching

He He, Jason Eisner, Hal Daume

Symbolic Dynamic Programming for Continuous State and Observation POMDPs

Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting

On the connections between saliency and tracking

Vijay Mahadevan, Nuno Vasconcelos

Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs

Anima Anandkumar, Ragupathyraj Valluvan

Rational inference of relative preferences

Nisheeth Srivastava, Paul R. Schrater

Fast Resampling Weighted v-Statistics

Chunxiao Zhou, Jiseong Park, Yun Fu

Multi-Stage Multi-Task Feature Learning

Pinghua Gong, Jieping Ye, Changshui Zhang, Chang-shui Zhang

Controlled Recognition Bounds for Visual Learning and Exploration

Vasiliy Karasev, Alessandro Chiuso, Stefano Soatto

Locating Changes in Highly Dependent Data with Unknown Number of Change Points

Azadeh Khaleghi, Daniil Ryabko

Regularized Off-Policy TD-Learning

Bo Liu, Sridhar Mahadevan, Ji Liu