NeurIPS 2012

370 papers

Weighted Likelihood Policy Search with Model Selection

Tsuyoshi Ueno, Kohei Hayashi, Takashi Washio, Yoshinobu Kawahara

Label Ranking with Partial Abstention based on Thresholded Probabilistic Models

Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker

Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging

Chris Hinrichs, Vikas Singh, Jiming Peng, Sterling Johnson

On Lifting the Gibbs Sampling Algorithm

Deepak Venugopal, Vibhav Gogate

Perceptron Learning of SAT

Alex Flint, Matthew Blaschko

Online Regret Bounds for Undiscounted Continuous Reinforcement Learning

Ronald Ortner, Daniil Ryabko

Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes

Jake Bouvrie, Jean-jeacques Slotine

Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification

Wei Bi, James T. Kwok

Near-optimal Differentially Private Principal Components

Kamalika Chaudhuri, Anand Sarwate, Kaushik Sinha

Matrix reconstruction with the local max norm

Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov

Angular Quantization-based Binary Codes for Fast Similarity Search

Yunchao Gong, Sanjiv Kumar, Vishal Verma, Svetlana Lazebnik

Towards a learning-theoretic analysis of spike-timing dependent plasticity

David Balduzzi, Michel Besserve

Learning the Architecture of Sum-Product Networks Using Clustering on Variables

Aaron Dennis, Dan Ventura

Density-Difference Estimation

Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus D. Plessis, Song Liu

Nonparametric Reduced Rank Regression

Rina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty

Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins

Alex Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun

Pointwise Tracking the Optimal Regression Function

Yair Wiener, Ran El-Yaniv

Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inference

Xue-xin Wei, Alan Stocker

Online allocation and homogeneous partitioning for piecewise constant mean-approximation

Alexandra Carpentier, Odalric-ambrym Maillard

Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation

Benjamin Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki

A Geometric take on Metric Learning

Søren Hauberg, Oren Freifeld, Michael J. Black

The representer theorem for Hilbert spaces: a necessary and sufficient condition

Francesco Dinuzzo, Bernhard Schölkopf

One Permutation Hashing

Ping Li, Art Owen, Cun-hui Zhang

Projection Retrieval for Classification

Madalina Fiterau, Artur Dubrawski

Memorability of Image Regions

Aditya Khosla, Jianxiong Xiao, Antonio Torralba, Aude Oliva

Natural Images, Gaussian Mixtures and Dead Leaves

Daniel Zoran, Yair Weiss

Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression

Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy

Selecting Diverse Features via Spectral Regularization

Abhimanyu Das, Anirban Dasgupta, Ravi Kumar

Communication-Efficient Algorithms for Statistical Optimization

Yuchen Zhang, Martin J. Wainwright, John C. Duchi

Query Complexity of Derivative-Free Optimization

Kevin G. Jamieson, Robert Nowak, Ben Recht

Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods

Andre Wibisono, Martin J. Wainwright, Michael I. Jordan, John C. Duchi

Expectation Propagation in Gaussian Process Dynamical Systems

Marc Deisenroth, Shakir Mohamed

Calibrated Elastic Regularization in Matrix Completion

Tingni Sun, Cun-hui Zhang

Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds

Teodor M. Moldovan, Pieter Abbeel

Online Sum-Product Computation Over Trees

Mark Herbster, Stephen Pasteris, Fabio Vitale

Multilabel Classification using Bayesian Compressed Sensing

Ashish Kapoor, Raajay Viswanathan, Prateek Jain

Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation

Christian Mayr, Paul Stärke, Johannes Partzsch, Love Cederstroem, Rene Schüffny

A quasi-Newton proximal splitting method

Stephen Becker, Jalal Fadili

Density Propagation and Improved Bounds on the Partition Function

Stefano Ermon, Ashish Sabharwal, Bart Selman, Carla P. Gomes

Bayesian Pedigree Analysis using Measure Factorization

Bonnie Kirkpatrick, Alexandre Bouchard-côté

Random function priors for exchangeable arrays with applications to graphs and relational data

James Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy

Learning the Dependency Structure of Latent Factors

Yunlong He, Yanjun Qi, Koray Kavukcuoglu, Haesun Park

Transelliptical Component Analysis

Fang Han, Han Liu

Learning curves for multi-task Gaussian process regression

Peter Sollich, Simon Ashton

Online L1-Dictionary Learning with Application to Novel Document Detection

Shiva P. Kasiviswanathan, Huahua Wang, Arindam Banerjee, Prem Melville

Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning

Jinfeng Yi, Rong Jin, Shaili Jain, Tianbao Yang, Anil K. Jain

Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL

Nishant Mehta, Dongryeol Lee, Alexander G. Gray

Entangled Monte Carlo

Seong-hwan Jun, Liangliang Wang, Alexandre Bouchard-côté

Optimal kernel choice for large-scale two-sample tests

Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil

Submodular-Bregman and the Lovász-Bregman Divergences with Applications

Rishabh Iyer, Jeff A. Bilmes

Affine Independent Variational Inference

Edward Challis, David Barber

Bayesian Warped Gaussian Processes

Miguel Lázaro-Gredilla

Learning to Align from Scratch

Gary Huang, Marwan Mattar, Honglak Lee, Erik G. Learned-miller

Learning Networks of Heterogeneous Influence

Nan Du, Le Song, Ming Yuan, Alex J. Smola

Scalable Inference of Overlapping Communities

Prem Gopalan, Sean Gerrish, Michael Freedman, David M. Blei, David M. Mimno

Assessing Blinding in Clinical Trials

Ognjen Arandjelovic

Spectral learning of linear dynamics from generalised-linear observations with application to neural population data

Lars Buesing, Jakob H. Macke, Maneesh Sahani

Semantic Kernel Forests from Multiple Taxonomies

Sung Ju Hwang, Kristen Grauman, Fei Sha

Feature-aware Label Space Dimension Reduction for Multi-label Classification

Yao-nan Chen, Hsuan-tien Lin

Majorization for CRFs and Latent Likelihoods

Tony Jebara, Anna Choromanska

Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling

Antonino Freno, Mikaela Keller, Marc Tommasi

A Polylog Pivot Steps Simplex Algorithm for Classification

Elad Hazan, Zohar Karnin

Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization

Konstantinos Tsianos, Sean Lawlor, Michael G. Rabbat

Robustness and risk-sensitivity in Markov decision processes

Takayuki Osogami

Multiple Choice Learning: Learning to Produce Multiple Structured Outputs

Abner Guzmán-rivera, Dhruv Batra, Pushmeet Kohli

Tractable Objectives for Robust Policy Optimization

Katherine Chen, Michael Bowling

Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding

Philip Sterne, Joerg Bornschein, Abdul-saboor Sheikh, Jörg Lücke, Jacquelyn A. Shelton

Variational Inference for Crowdsourcing

Qiang Liu, Jian Peng, Alex Ihler

Multiplicative Forests for Continuous-Time Processes

Jeremy Weiss, Sriraam Natarajan, David Page

Generalization Bounds for Domain Adaptation

Chao Zhang, Lei Zhang, Jieping Ye

Learning with Target Prior

Zuoguan Wang, Siwei Lyu, Gerwin Schalk, Qiang Ji

Continuous Relaxations for Discrete Hamiltonian Monte Carlo

Yichuan Zhang, Zoubin Ghahramani, Amos J. Storkey, Charles A. Sutton

Slice Normalized Dynamic Markov Logic Networks

Tivadar Papai, Henry Kautz, Daniel Stefankovic

Exponential Concentration for Mutual Information Estimation with Application to Forests

Han Liu, Larry Wasserman, John D. Lafferty

Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction

Minjie Xu, Jun Zhu, Bo Zhang

The Time-Marginalized Coalescent Prior for Hierarchical Clustering

Levi Boyles, Max Welling

Unsupervised Structure Discovery for Semantic Analysis of Audio

Sourish Chaudhuri, Bhiksha Raj

Sketch-Based Linear Value Function Approximation

Marc Bellemare, Joel Veness, Michael Bowling

A systematic approach to extracting semantic information from functional MRI data

Francisco Pereira, Matthew Botvinick

Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization

Stephen Bach, Matthias Broecheler, Lise Getoor, Dianne O'leary

Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data

Michael C Hughes, Emily B. Fox, Erik B. Sudderth

Learning Probability Measures with respect to Optimal Transport Metrics

Guillermo Canas, Lorenzo Rosasco

Stochastic Gradient Descent with Only One Projection

Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton

Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions

Mathieu Sinn, Bei Chen

Priors for Diversity in Generative Latent Variable Models

James T. Kwok, Ryan P. Adams

Locally Uniform Comparison Image Descriptor

Andrew Ziegler, Eric Christiansen, David Kriegman, Serge J. Belongie

Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction

Christoph H. Lampert

A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling

Pieter-jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen

A Linear Time Active Learning Algorithm for Link Classification

Nicolò Cesa-bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella

Kernel Latent SVM for Visual Recognition

Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori

Approximating Concavely Parameterized Optimization Problems

Joachim Giesen, Jens Mueller, Soeren Laue, Sascha Swiercy

Context-Sensitive Decision Forests for Object Detection

Peter Kontschieder, Samuel R. Bulò, Antonio Criminisi, Pushmeet Kohli, Marcello Pelillo

Confusion-Based Online Learning and a Passive-Aggressive Scheme

Liva Ralaivola

Distributed Probabilistic Learning for Camera Networks with Missing Data

Sejong Yoon, Vladimir Pavlovic

Convergence Rate Analysis of MAP Coordinate Minimization Algorithms

Ofer Meshi, Amir Globerson, Tommi S. Jaakkola

Graphical Gaussian Vector for Image Categorization

Tatsuya Harada, Yasuo Kuniyoshi

Clustering by Nonnegative Matrix Factorization Using Graph Random Walk

Zhirong Yang, Tele Hao, Onur Dikmen, Xi Chen, Erkki Oja

Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models

Jeff Beck, Alexandre Pouget, Katherine A. Heller

Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting

Amadou Ba, Mathieu Sinn, Yannig Goude, Pascal Pompey