Advances in Neural Information Processing Systems 25

NIPS 2012

Edited by F. Pereira and C.J. Burges and L. Bottou and K.Q. Weinberger

ISBN: 9781627480031

370 papers

Topology Constraints in Graphical Models Marcelo Fiori, Pablo Musé, Guillermo Sapiro
Clustering Aggregation as Maximum-Weight Independent Set Nan Li, Longin J. Latecki
FastEx: Hash Clustering with Exponential Families Amr Ahmed, Sujith Ravi, Alex J. Smola, Shravan M. Narayanamurthy
The Bethe Partition Function of Log-supermodular Graphical Models Nicholas Ruozzi
Selective Labeling via Error Bound Minimization Quanquan Gu, Tong Zhang, Jiawei Han, Chris H. Ding
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek, Hugo Larochelle, Ryan P. Adams
Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss Zhuo Wang, Alan Stocker, Daniel D Lee
Probabilistic Event Cascades for Alzheimer's disease Jonathan Huang, Daniel Alexander
Super-Bit Locality-Sensitive Hashing Jianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian
Bayesian nonparametric models for bipartite graphs Francois Caron
Learning Label Trees for Probabilistic Modelling of Implicit Feedback Andriy Mnih, Yee W. Teh
Factoring nonnegative matrices with linear programs Ben Recht, Christopher Re, Joel Tropp, Victor Bittorf
Privacy Aware Learning Martin J. Wainwright, Michael I. Jordan, John C. Duchi
Truncation-free Online Variational Inference for Bayesian Nonparametric Models Chong Wang, David M. Blei
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva
Learning Image Descriptors with the Boosting-Trick Tomasz Trzcinski, Mario Christoudias, Vincent Lepetit, Pascal Fua
A latent factor model for highly multi-relational data Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski
Bayesian estimation of discrete entropy with mixtures of stick-breaking priors Evan Archer, Ill Memming Park, Jonathan W. Pillow
Timely Object Recognition Sergey Karayev, Tobias Baumgartner, Mario Fritz, Trevor Darrell
Efficient high dimensional maximum entropy modeling via symmetric partition functions Paul Vernaza, Drew Bagnell
Topic-Partitioned Multinetwork Embeddings Peter Krafft, Juston Moore, Bruce Desmarais, Hanna M. Wallach
Recovery of Sparse Probability Measures via Convex Programming Mert Pilanci, Laurent E. Ghaoui, Venkat Chandrasekaran
Proximal Newton-type methods for convex optimization Jason Lee, Yuekai Sun, Michael Saunders
Learning visual motion in recurrent neural networks Marius Pachitariu, Maneesh Sahani
Graphical Models via Generalized Linear Models Eunho Yang, Genevera Allen, Zhandong Liu, Pradeep K. Ravikumar
Searching for objects driven by context Bogdan Alexe, Nicolas Heess, Yee W. Teh, Vittorio Ferrari
Learning Mixtures of Tree Graphical Models Anima Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade
Convex Multi-view Subspace Learning Martha White, Xinhua Zhang, Dale Schuurmans, Yao-liang Yu
Learning Invariant Representations of Molecules for Atomization Energy Prediction Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, Anatole V. Lilienfeld, Klaus-Robert Müller
On Multilabel Classification and Ranking with Partial Feedback Claudio Gentile, Francesco Orabona
A dynamic excitatory-inhibitory network in a VLSI chip for spiking information reregistrations Juan Huo
Distributed Non-Stochastic Experts Varun Kanade, Zhenming Liu, Bozidar Radunovic
Deep Learning of Invariant Features via Simulated Fixations in Video Will Zou, Shenghuo Zhu, Kai Yu, Andrew Y. Ng
Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints Stefan Habenschuss, Johannes Bill, Bernhard Nessler
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions Jaedeug Choi, Kee-eung Kim
Human memory search as a random walk in a semantic network Joseph L. Austerweil, Joshua T. Abbott, Thomas L. Griffiths
Multi-criteria Anomaly Detection using Pareto Depth Analysis Ko-jen Hsiao, Kevin Xu, Jeff Calder, Alfred O. Hero
A Spectral Algorithm for Latent Dirichlet Allocation Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-kai Liu
The Perturbed Variation Maayan Harel, Shie Mannor
Discriminatively Trained Sparse Code Gradients for Contour Detection Ren Xiaofeng, Liefeng Bo
A Bayesian Approach for Policy Learning from Trajectory Preference Queries Aaron Wilson, Alan Fern, Prasad Tadepalli
Kernel Hyperalignment Alexander Lorbert, Peter J. Ramadge
Multi-Task Averaging Sergey Feldman, Maya Gupta, Bela Frigyik
A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes Thomas Furmston, David Barber
Convergence and Energy Landscape for Cheeger Cut Clustering Xavier Bresson, Thomas Laurent, David Uminsky, James V. Brecht
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon, Pradeep K. Ravikumar
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates Zhihua Zhang, Bojun Tu
How They Vote: Issue-Adjusted Models of Legislative Behavior Sean Gerrish, David M. Blei
Multiclass Learning Approaches: A Theoretical Comparison with Implications Amit Daniely, Sivan Sabato, Shai S. Shwartz
Dynamical And-Or Graph Learning for Object Shape Modeling and Detection Xiaolong Wang, Liang Lin
Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics Ashwini Shukla, Aude Billard
3D Social Saliency from Head-mounted Cameras Hyun S. Park, Eakta Jain, Yaser Sheikh
Coupling Nonparametric Mixtures via Latent Dirichlet Processes Dahua Lin, John W. Fisher
Multiclass Learning with Simplex Coding Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco, Jean-jeacques Slotine
Clustering Sparse Graphs Yudong Chen, Sujay Sanghavi, Huan Xu
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization Andre Barreto, Doina Precup, Joelle Pineau
Accelerated Training for Matrix-norm Regularization: A Boosting Approach Xinhua Zhang, Dale Schuurmans, Yao-liang Yu
Supervised Learning with Similarity Functions Purushottam Kar, Prateek Jain
A Simple and Practical Algorithm for Differentially Private Data Release Moritz Hardt, Katrina Ligett, Frank Mcsherry
Persistent Homology for Learning Densities with Bounded Support Florian T. Pokorny, Hedvig Kjellström, Danica Kragic, Carl Ek
Proper losses for learning from partial labels Jesús Cid-sueiro
Predicting Action Content On-Line and in Real Time before Action Onset – an Intracranial Human Study Uri Maoz, Shengxuan Ye, Ian Ross, Adam Mamelak, Christof Koch
Classification Calibration Dimension for General Multiclass Losses Harish G. Ramaswamy, Shivani Agarwal
Analog readout for optical reservoir computers Anteo Smerieri, François Duport, Yvon Paquot, Benjamin Schrauwen, Marc Haelterman, Serge Massar
Perfect Dimensionality Recovery by Variational Bayesian PCA Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. D. Babacan
Compressive neural representation of sparse, high-dimensional probabilities Zachary Pitkow
Shifting Weights: Adapting Object Detectors from Image to Video Kevin Tang, Vignesh Ramanathan, Li Fei-fei, Daphne Koller
Minimization of Continuous Bethe Approximations: A Positive Variation Jason Pacheco, Erik B. Sudderth
Optimal Regularized Dual Averaging Methods for Stochastic Optimization Xi Chen, Qihang Lin, Javier Pena
Gradient Weights help Nonparametric Regressors Samory Kpotufe, Abdeslam Boularias
Regularized Off-Policy TD-Learning Bo Liu, Sridhar Mahadevan, Ji Liu
Locating Changes in Highly Dependent Data with Unknown Number of Change Points Azadeh Khaleghi, Daniil Ryabko
Controlled Recognition Bounds for Visual Learning and Exploration Vasiliy Karasev, Alessandro Chiuso, Stefano Soatto
Multi-Stage Multi-Task Feature Learning Pinghua Gong, Jieping Ye, Chang-shui Zhang
Fast Resampling Weighted v-Statistics Chunxiao Zhou, Jiseong Park, Yun Fu
Rational inference of relative preferences Nisheeth Srivastava, Paul R. Schrater
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs Anima Anandkumar, Ragupathyraj Valluvan
On the connections between saliency and tracking Vijay Mahadevan, Nuno Vasconcelos
Symbolic Dynamic Programming for Continuous State and Observation POMDPs Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting
Imitation Learning by Coaching He He, Jason Eisner, Hal Daume
Learning about Canonical Views from Internet Image Collections Elad Mezuman, Yair Weiss
A lattice filter model of the visual pathway Karol Gregor, Dmitri B. Chklovskii
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
Recognizing Activities by Attribute Dynamics Weixin Li, Nuno Vasconcelos
Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space Yanyan Lan, Jiafeng Guo, Xueqi Cheng, Tie-yan Liu
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound Shusen Wang, Zhihua Zhang
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search Arthur Guez, David Silver, Peter Dayan
Dual-Space Analysis of the Sparse Linear Model Yi Wu, David P. Wipf
Neuronal Spike Generation Mechanism as an Oversampling, Noise-shaping A-to-D converter Dmitri B. Chklovskii, Daniel Soudry
Multiple Operator-valued Kernel Learning Hachem Kadri, Alain Rakotomamonjy, Philippe Preux, Francis R. Bach
No-Regret Algorithms for Unconstrained Online Convex Optimization Brendan Mcmahan, Matthew Streeter
Learning Partially Observable Models Using Temporally Abstract Decision Trees Erik Talvitie
Emergence of Object-Selective Features in Unsupervised Feature Learning Adam Coates, Andrej Karpathy, Andrew Y. Ng
CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem Henrik Ohlsson, Allen Yang, Roy Dong, Shankar Sastry
Learning optimal spike-based representations Ralph Bourdoukan, David Barrett, Sophie Deneve, Christian K. Machens
Collaborative Ranking With 17 Parameters Maksims Volkovs, Richard S. Zemel
Small-Variance Asymptotics for Exponential Family Dirichlet Process Mixture Models Ke Jiang, Brian Kulis, Michael I. Jordan
Deep Representations and Codes for Image Auto-Annotation Ryan Kiros, Csaba Szepesvári
Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task Jenna Wiens, Eric Horvitz, John V. Guttag
Meta-Gaussian Information Bottleneck Melanie Rey, Volker Roth
Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions Neil Burch, Marc Lanctot, Duane Szafron, Richard G. Gibson
Fusion with Diffusion for Robust Visual Tracking Yu Zhou, Xiang Bai, Wenyu Liu, Longin J. Latecki
Convolutional-Recursive Deep Learning for 3D Object Classification Richard Socher, Brody Huval, Bharath Bath, Christopher D. Manning, Andrew Y. Ng
Transferring Expectations in Model-based Reinforcement Learning Trung Nguyen, Tomi Silander, Tze Y. Leong
Modelling Reciprocating Relationships with Hawkes Processes Charles Blundell, Jeff Beck, Katherine A. Heller
Ancestor Sampling for Particle Gibbs Fredrik Lindsten, Thomas Schön, Michael I. Jordan
Interpreting prediction markets: a stochastic approach Rafael M. Frongillo, Nicolas Della Penna, Mark D. Reid
Nonparanormal Belief Propagation (NPNBP) Gal Elidan, Cobi Cario
Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions Alexandra Carpentier, Rémi Munos
Bayesian Nonparametric Modeling of Suicide Attempts Francisco Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz
Non-linear Metric Learning Dor Kedem, Stephen Tyree, Fei Sha, Gert R. Lanckriet, Kilian Q. Weinberger
Putting Bayes to sleep Dmitry Adamskiy, Manfred K. Warmuth, Wouter M. Koolen
Sparse Approximate Manifolds for Differential Geometric MCMC Ben Calderhead, Mátyás A. Sustik
Bayesian active learning with localized priors for fast receptive field characterization Mijung Park, Jonathan W. Pillow
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images Dan Ciresan, Alessandro Giusti, Luca M. Gambardella, Jürgen Schmidhuber
Learning from the Wisdom of Crowds by Minimax Entropy Dengyong Zhou, Sumit Basu, Yi Mao, John C. Platt
Parametric Local Metric Learning for Nearest Neighbor Classification Jun Wang, Alexandros Kalousis, Adam Woznica
The topographic unsupervised learning of natural sounds in the auditory cortex Hiroki Terashima, Masato Okada
Efficient Sampling for Bipartite Matching Problems Maksims Volkovs, Richard S. Zemel
Volume Regularization for Binary Classification Koby Crammer, Tal Wagner
Causal discovery with scale-mixture model for spatiotemporal variance dependencies Zhitang Chen, Kun Zhang, Laiwan Chan
Neurally Plausible Reinforcement Learning of Working Memory Tasks Jaldert Rombouts, Pieter Roelfsema, Sander M. Bohte
Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression Piyush Rai, Abhishek Kumar, Hal Daume
Feature Clustering for Accelerating Parallel Coordinate Descent Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin
Phoneme Classification using Constrained Variational Gaussian Process Dynamical System Hyunsin Park, Sungrack Yun, Sanghyuk Park, Jongmin Kim, Chang D. Yoo
Fast Variational Inference in the Conjugate Exponential Family James Hensman, Magnus Rattray, Neil D. Lawrence
Identifiability and Unmixing of Latent Parse Trees Daniel J. Hsu, Sham M. Kakade, Percy Liang
On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking Clément Calauzènes, Nicolas Usunier, Patrick Gallinari
Learning with Partially Absorbing Random Walks Xiao-ming Wu, Zhenguo Li, Anthony M. So, John Wright, Shih-fu Chang
Relax and Randomize : From Value to Algorithms Sasha Rakhlin, Ohad Shamir, Karthik Sridharan
Inverse Reinforcement Learning through Structured Classification Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin
Efficient and direct estimation of a neural subunit model for sensory coding Brett Vintch, Andrew Zaharia, J Movshon, Eero P. Simoncelli
Discriminative Learning of Sum-Product Networks Robert Gens, Pedro Domingos
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions Alekh Agarwal, Sahand Negahban, Martin J. Wainwright
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button Joan Fruitet, Alexandra Carpentier, Maureen Clerc, Rémi Munos
Localizing 3D cuboids in single-view images Jianxiong Xiao, Bryan Russell, Antonio Torralba
A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation Aaron Defazio, Tibério S. Caetano
Hamming Distance Metric Learning Mohammad Norouzi, David J Fleet, Ruslan Salakhutdinov
Co-Regularized Hashing for Multimodal Data Yi Zhen, Dit-Yan Yeung
The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes Simon Lyons, Amos J. Storkey, Simo Särkkä
How Prior Probability Influences Decision Making: A Unifying Probabilistic Model Yanping Huang, Timothy Hanks, Mike Shadlen, Abram L. Friesen, Rajesh P. Rao
Structured Learning of Gaussian Graphical Models Karthik Mohan, Mike Chung, Seungyeop Han, Daniela Witten, Su-in Lee, Maryam Fazel
Entropy Estimations Using Correlated Symmetric Stable Random Projections Ping Li, Cun-hui Zhang
Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing Shinsuke Koyama
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison Tianbao Yang, Yu-feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou
Spiking and saturating dendrites differentially expand single neuron computation capacity Romain Cazé, Mark Humphries, Boris S. Gutkin
Active Learning of Model Evidence Using Bayesian Quadrature Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts, Carl E. Rasmussen
Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification Yung-kyun Noh, Frank Park, Daniel D. Lee
Bayesian Hierarchical Reinforcement Learning Feng Cao, Soumya Ray
Compressive Sensing MRI with Wavelet Tree Sparsity Chen Chen, Junzhou Huang
Mixability in Statistical Learning Tim V. Erven, Peter Grünwald, Mark D. Reid, Robert C. Williamson
Symmetric Correspondence Topic Models for Multilingual Text Analysis Kosuke Fukumasu, Koji Eguchi, Eric P. Xing
Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs Aharon Birnbaum, Shai S. Shwartz
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
Factorial LDA: Sparse Multi-Dimensional Text Models Michael Paul, Mark Dredze
Augment-and-Conquer Negative Binomial Processes Mingyuan Zhou, Lawrence Carin
Large Scale Distributed Deep Networks Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Mark Mao, Marc'aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, Quoc V. Le, Andrew Y. Ng
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses Po-ling Loh, Martin J. Wainwright
Joint Modeling of a Matrix with Associated Text via Latent Binary Features Xianxing Zhang, Lawrence Carin
Near-Optimal MAP Inference for Determinantal Point Processes Jennifer Gillenwater, Alex Kulesza, Ben Taskar
Image Denoising and Inpainting with Deep Neural Networks Junyuan Xie, Linli Xu, Enhong Chen
Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making Pradeep Shenoy, Angela J. Yu
Cost-Sensitive Exploration in Bayesian Reinforcement Learning Dongho Kim, Kee-eung Kim, Pascal Poupart
MCMC for continuous-time discrete-state systems Vinayak Rao, Yee W. Teh
Spectral Learning of General Weighted Automata via Constrained Matrix Completion Borja Balle, Mehryar Mohri
Learning with Recursive Perceptual Representations Oriol Vinyals, Yangqing Jia, Li Deng, Trevor Darrell
Scaled Gradients on Grassmann Manifolds for Matrix Completion Thanh Ngo, Yousef Saad
Link Prediction in Graphs with Autoregressive Features Emile Richard, Stephane Gaiffas, Nicolas Vayatis
A Generative Model for Parts-based Object Segmentation S. Eslami, Christopher Williams
Dimensionality Dependent PAC-Bayes Margin Bound Chi Jin, Liwei Wang
MAP Inference in Chains using Column Generation David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum
Cocktail Party Processing via Structured Prediction Yuxuan Wang, Deliang Wang
Fused sparsity and robust estimation for linear models with unknown variance Arnak Dalalyan, Yin Chen
On the Sample Complexity of Robust PCA Matthew Coudron, Gilad Lerman
Learning to Discover Social Circles in Ego Networks Jure Leskovec, Julian J. Mcauley
Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential _1-Minimization Demba Ba, Behtash Babadi, Patrick Purdon, Emery Brown
Tight Bounds on Profile Redundancy and Distinguishability Jayadev Acharya, Hirakendu Das, Alon Orlitsky
On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks Qirong Ho, Junming Yin, Eric P. Xing
A Better Way to Pretrain Deep Boltzmann Machines Geoffrey E. Hinton, Ruslan Salakhutdinov
Semi-supervised Eigenvectors for Locally-biased Learning Toke Hansen, Michael W. Mahoney
The variational hierarchical EM algorithm for clustering hidden Markov models Emanuele Coviello, Gert R. Lanckriet, Antoni B. Chan
Scalable nonconvex inexact proximal splitting Suvrit Sra
Bayesian nonparametric models for ranked data Francois Caron, Yee W. Teh
GenDeR: A Generic Diversified Ranking Algorithm Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw Szymanski
Accuracy at the Top Stephen Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic
Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand Amy Greenwald, Jiacui Li, Eric Sodomka
Multiresolution Gaussian Processes Emily B. Fox, David B. Dunson
Burn-in, bias, and the rationality of anchoring Falk Lieder, Tom Griffiths, Noah Goodman
Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes Michael Bryant, Erik B. Sudderth
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model Sanja Fidler, Sven Dickinson, Raquel Urtasun
Risk-Aversion in Multi-armed Bandits Amir Sani, Alessandro Lazaric, Rémi Munos
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning Ulugbek Kamilov, Sundeep Rangan, Michael Unser, Alyson K. Fletcher
Gradient-based kernel method for feature extraction and variable selection Kenji Fukumizu, Chenlei Leng
Scalable imputation of genetic data with a discrete fragmentation-coagulation process Lloyd Elliott, Yee W. Teh
Non-parametric Approximate Dynamic Programming via the Kernel Method Nikhil Bhat, Vivek Farias, Ciamac C. Moallemi
Probabilistic n-Choose-k Models for Classification and Ranking Kevin Swersky, Brendan J. Frey, Daniel Tarlow, Richard S. Zemel, Ryan P. Adams
Delay Compensation with Dynamical Synapses Chi Fung, K. Wong, Si Wu
Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity Angela Eigenstetter, Bjorn Ommer
High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon Risacher, Andrew Saykin, Li Shen
Multiresolution analysis on the symmetric group Risi Kondor, Walter Dempsey
Learned Prioritization for Trading Off Accuracy and Speed Jiarong Jiang, Adam Teichert, Jason Eisner, Hal Daume
Learning as MAP Inference in Discrete Graphical Models Xianghang Liu, James Petterson, Tibério S. Caetano
Hierarchical Optimistic Region Selection driven by Curiosity Odalric-ambrym Maillard
Trajectory-Based Short-Sighted Probabilistic Planning Felipe Trevizan, Manuela Veloso
Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence Victor Gabillon, Mohammad Ghavamzadeh, Alessandro Lazaric
On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes Bruno Scherrer, Boris Lesner
Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction Pietro D. Lena, Ken Nagata, Pierre F. Baldi
Isotropic Hashing Weihao Kong, Wu-jun Li
Repulsive Mixtures Francesca Petralia, Vinayak Rao, David B. Dunson
Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models Kei Wakabayashi, Takao Miura
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery Ehsan Elhamifar, Guillermo Sapiro, René Vidal
Mirror Descent Meets Fixed Share (and feels no regret) Nicolò Cesa-bianchi, Pierre Gaillard, Gabor Lugosi, Gilles Stoltz
Semi-Supervised Domain Adaptation with Non-Parametric Copulas David Lopez-paz, Jose M. Hernández-lobato, Bernhard Schölkopf
The Lovász ϑ function, SVMs and finding large dense subgraphs Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi
Slice sampling normalized kernel-weighted completely random measure mixture models Nicholas Foti, Sinead Williamson
Automatic Feature Induction for Stagewise Collaborative Filtering Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon
A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets Nicolas L. Roux, Mark Schmidt, Francis R. Bach
Monte Carlo Methods for Maximum Margin Supervised Topic Models Qixia Jiang, Jun Zhu, Maosong Sun, Eric P. Xing
Analyzing 3D Objects in Cluttered Images Mohsen Hejrati, Deva Ramanan
A mechanistic model of early sensory processing based on subtracting sparse representations Shaul Druckmann, Tao Hu, Dmitri B. Chklovskii
Ensemble weighted kernel estimators for multivariate entropy estimation Kumar Sricharan, Alfred O. Hero
Active Comparison of Prediction Models Christoph Sawade, Niels Landwehr, Tobias Scheffer
Reducing statistical time-series problems to binary classification Daniil Ryabko, Jeremie Mary
Max-Margin Structured Output Regression for Spatio-Temporal Action Localization Du Tran, Junsong Yuan
Minimizing Sparse High-Order Energies by Submodular Vertex-Cover Andrew Delong, Olga Veksler, Anton Osokin, Yuri Boykov
A new metric on the manifold of kernel matrices with application to matrix geometric means Suvrit Sra
Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination Won H. Kim, Deepti Pachauri, Charles Hatt, Moo. K. Chung, Sterling Johnson, Vikas Singh
Cardinality Restricted Boltzmann Machines Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov, Ryan P. Adams
Sparse Prediction with the $k$-Support Norm Andreas Argyriou, Rina Foygel, Nathan Srebro
A Marginalized Particle Gaussian Process Regression Yali Wang, Brahim Chaib-draa
Iterative ranking from pair-wise comparisons Sahand Negahban, Sewoong Oh, Devavrat Shah
Training sparse natural image models with a fast Gibbs sampler of an extended state space Lucas Theis, Jascha Sohl-dickstein, Matthias Bethge
Learning from Distributions via Support Measure Machines Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf
Learning Multiple Tasks using Shared Hypotheses Koby Crammer, Yishay Mansour
Minimizing Uncertainty in Pipelines Nilesh Dalvi, Aditya Parameswaran, Vibhor Rastogi
An Integer Optimization Approach to Associative Classification Dimitris Bertsimas, Allison Chang, Cynthia Rudin
Algorithms for Learning Markov Field Policies Abdeslam Boularias, Jan R. Peters, Oliver B. Kroemer
Bayesian Probabilistic Co-Subspace Addition Lei Shi
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress Manuel Lopes, Tobias Lang, Marc Toussaint, Pierre-yves Oudeyer
From Deformations to Parts: Motion-based Segmentation of 3D Objects Soumya Ghosh, Matthew Loper, Erik B. Sudderth, Michael J. Black
Bayesian models for Large-scale Hierarchical Classification Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-mizil
Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model Sander M. Bohte
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach Dijun Luo, Heng Huang, Feiping Nie, Chris H. Ding
Random Utility Theory for Social Choice Hossein Azari, David Parks, Lirong Xia
Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs Michael Collins, Shay B. Cohen
Action-Model Based Multi-agent Plan Recognition Hankz H. Zhuo, Qiang Yang, Subbarao Kambhampati
Semiparametric Principal Component Analysis Fang Han, Han Liu
Multi-task Vector Field Learning Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He
Local Supervised Learning through Space Partitioning Joseph Wang, Venkatesh Saligrama
Dip-means: an incremental clustering method for estimating the number of clusters Argyris Kalogeratos, Aristidis Likas
Unsupervised Template Learning for Fine-Grained Object Recognition Shulin Yang, Liefeng Bo, Jue Wang, Linda G. Shapiro
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function Pedro Ortega, Jordi Grau-moya, Tim Genewein, David Balduzzi, Daniel Braun
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems Morteza Ibrahimi, Adel Javanmard, Benjamin V. Roy
A Conditional Multinomial Mixture Model for Superset Label Learning Liping Liu, Thomas G. Dietterich
Value Pursuit Iteration Amir M. Farahmand, Doina Precup
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning Matthew Der, Lawrence K. Saul
Identification of Recurrent Patterns in the Activation of Brain Networks Firdaus Janoos, Weichang Li, Niranjan Subrahmanya, Istvan Morocz, William Wells
Hierarchical spike coding of sound Yan Karklin, Chaitanya Ekanadham, Eero P. Simoncelli
A Polynomial-time Form of Robust Regression Yao-liang Yu, Özlem Aslan, Dale Schuurmans
Multimodal Learning with Deep Boltzmann Machines Nitish Srivastava, Ruslan Salakhutdinov
A nonparametric variable clustering model Konstantina Palla, Zoubin Ghahramani, David A. Knowles
Transelliptical Graphical Models Han Liu, Fang Han, Cun-hui Zhang
Collaborative Gaussian Processes for Preference Learning Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Jose M. Hernández-lobato
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation Tuo Zhao, Kathryn Roeder, Han Liu
Learning Manifolds with K-Means and K-Flats Guillermo Canas, Tomaso Poggio, Lorenzo Rosasco
Newton-Like Methods for Sparse Inverse Covariance Estimation Figen Oztoprak, Jorge Nocedal, Steven Rennie, Peder A. Olsen
A Neural Autoregressive Topic Model Hugo Larochelle, Stanislas Lauly
Active Learning of Multi-Index Function Models Tyagi Hemant, Volkan Cevher
Probabilistic Low-Rank Subspace Clustering S. D. Babacan, Shinichi Nakajima, Minh Do
Fully Bayesian inference for neural models with negative-binomial spiking Jonathan W. Pillow, James Scott
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting Amadou Ba, Mathieu Sinn, Yannig Goude, Pascal Pompey
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models Jeff Beck, Alexandre Pouget, Katherine A. Heller
Clustering by Nonnegative Matrix Factorization Using Graph Random Walk Zhirong Yang, Tele Hao, Onur Dikmen, Xi Chen, Erkki Oja
Graphical Gaussian Vector for Image Categorization Tatsuya Harada, Yasuo Kuniyoshi
Convergence Rate Analysis of MAP Coordinate Minimization Algorithms Ofer Meshi, Amir Globerson, Tommi S. Jaakkola
Distributed Probabilistic Learning for Camera Networks with Missing Data Sejong Yoon, Vladimir Pavlovic
Confusion-Based Online Learning and a Passive-Aggressive Scheme Liva Ralaivola
Context-Sensitive Decision Forests for Object Detection Peter Kontschieder, Samuel R. Bulò, Antonio Criminisi, Pushmeet Kohli, Marcello Pelillo, Horst Bischof
Approximating Concavely Parameterized Optimization Problems Joachim Giesen, Jens Mueller, Soeren Laue, Sascha Swiercy
Kernel Latent SVM for Visual Recognition Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori
A Linear Time Active Learning Algorithm for Link Classification Nicolò Cesa-bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella
A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling Pieter-jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction Christoph H. Lampert
Locally Uniform Comparison Image Descriptor Andrew Ziegler, Eric Christiansen, David Kriegman, Serge J. Belongie
Priors for Diversity in Generative Latent Variable Models James T. Kwok, Ryan P. Adams
Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions Mathieu Sinn, Bei Chen
ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton
Stochastic Gradient Descent with Only One Projection Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi
Learning Probability Measures with respect to Optimal Transport Metrics Guillermo Canas, Lorenzo Rosasco
Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data Michael C Hughes, Emily B. Fox, Erik B. Sudderth
Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization Stephen Bach, Matthias Broecheler, Lise Getoor, Dianne O'leary
A systematic approach to extracting semantic information from functional MRI data Francisco Pereira, Matthew Botvinick
Sketch-Based Linear Value Function Approximation Marc Bellemare, Joel Veness, Michael Bowling
Unsupervised Structure Discovery for Semantic Analysis of Audio Sourish Chaudhuri, Bhiksha Raj
The Time-Marginalized Coalescent Prior for Hierarchical Clustering Levi Boyles, Max Welling
Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction Minjie Xu, Jun Zhu, Bo Zhang
Exponential Concentration for Mutual Information Estimation with Application to Forests Han Liu, Larry Wasserman, John D. Lafferty
Slice Normalized Dynamic Markov Logic Networks Tivadar Papai, Henry Kautz, Daniel Stefankovic
Continuous Relaxations for Discrete Hamiltonian Monte Carlo Yichuan Zhang, Zoubin Ghahramani, Amos J. Storkey, Charles A. Sutton
Learning with Target Prior Zuoguan Wang, Siwei Lyu, Gerwin Schalk, Qiang Ji
Generalization Bounds for Domain Adaptation Chao Zhang, Lei Zhang, Jieping Ye
Multiplicative Forests for Continuous-Time Processes Jeremy Weiss, Sriraam Natarajan, David Page
Variational Inference for Crowdsourcing Qiang Liu, Jian Peng, Alex Ihler
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
Tractable Objectives for Robust Policy Optimization Katherine Chen, Michael Bowling
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs Abner Guzmán-rivera, Dhruv Batra, Pushmeet Kohli
Robustness and risk-sensitivity in Markov decision processes Takayuki Osogami
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization Konstantinos Tsianos, Sean Lawlor, Michael G. Rabbat
A Polylog Pivot Steps Simplex Algorithm for Classification Elad Hazan, Zohar Karnin
Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling Antonino Freno, Mikaela Keller, Marc Tommasi
Majorization for CRFs and Latent Likelihoods Tony Jebara, Anna Choromanska
Feature-aware Label Space Dimension Reduction for Multi-label Classification Yao-nan Chen, Hsuan-tien Lin
Semantic Kernel Forests from Multiple Taxonomies Sung Ju Hwang, Kristen Grauman, Fei Sha
Spectral learning of linear dynamics from generalised-linear observations with application to neural population data Lars Buesing, Jakob H. Macke, Maneesh Sahani
Assessing Blinding in Clinical Trials Ognjen Arandjelovic
Scalable Inference of Overlapping Communities Prem Gopalan, Sean Gerrish, Michael Freedman, David M. Blei, David M. Mimno
Learning Networks of Heterogeneous Influence Nan Du, Le Song, Ming Yuan, Alex J. Smola
Learning to Align from Scratch Gary Huang, Marwan Mattar, Honglak Lee, Erik G. Learned-miller
Bayesian Warped Gaussian Processes Miguel Lázaro-Gredilla
Affine Independent Variational Inference Edward Challis, David Barber
Submodular-Bregman and the Lovász-Bregman Divergences with Applications Rishabh Iyer, Jeff A. Bilmes
Optimal kernel choice for large-scale two-sample tests Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu, Bharath K. Sriperumbudur
Entangled Monte Carlo Seong-hwan Jun, Liangliang Wang, Alexandre Bouchard-côté
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL Nishant Mehta, Dongryeol Lee, Alexander G. Gray
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning Jinfeng Yi, Rong Jin, Shaili Jain, Tianbao Yang, Anil K. Jain
Online L1-Dictionary Learning with Application to Novel Document Detection Shiva P. Kasiviswanathan, Huahua Wang, Arindam Banerjee, Prem Melville
Learning curves for multi-task Gaussian process regression Peter Sollich, Simon Ashton
Transelliptical Component Analysis Fang Han, Han Liu
Learning the Dependency Structure of Latent Factors Yunlong He, Yanjun Qi, Koray Kavukcuoglu, Haesun Park
Random function priors for exchangeable arrays with applications to graphs and relational data James Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy
Bayesian Pedigree Analysis using Measure Factorization Bonnie Kirkpatrick, Alexandre Bouchard-côté
Density Propagation and Improved Bounds on the Partition Function Stefano Ermon, Ashish Sabharwal, Bart Selman, Carla P. Gomes
A quasi-Newton proximal splitting method Stephen Becker, Jalal Fadili
Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation Christian Mayr, Paul Stärke, Johannes Partzsch, Love Cederstroem, Rene Schüffny, Yao Shuai, Nan Du, Heidemarie Schmidt
Multilabel Classification using Bayesian Compressed Sensing Ashish Kapoor, Raajay Viswanathan, Prateek Jain
Online Sum-Product Computation Over Trees Mark Herbster, Stephen Pasteris, Fabio Vitale
Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds Teodor M. Moldovan, Pieter Abbeel
Calibrated Elastic Regularization in Matrix Completion Tingni Sun, Cun-hui Zhang
Expectation Propagation in Gaussian Process Dynamical Systems Marc Deisenroth, Shakir Mohamed
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods Andre Wibisono, Martin J. Wainwright, Michael I. Jordan, John C. Duchi
Query Complexity of Derivative-Free Optimization Kevin G. Jamieson, Robert Nowak, Ben Recht
Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, Martin J. Wainwright, John C. Duchi
Selecting Diverse Features via Spectral Regularization Abhimanyu Das, Anirban Dasgupta, Ravi Kumar
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
Natural Images, Gaussian Mixtures and Dead Leaves Daniel Zoran, Yair Weiss
Memorability of Image Regions Aditya Khosla, Jianxiong Xiao, Antonio Torralba, Aude Oliva
Projection Retrieval for Classification Madalina Fiterau, Artur Dubrawski
One Permutation Hashing Ping Li, Art Owen, Cun-hui Zhang
The representer theorem for Hilbert spaces: a necessary and sufficient condition Francesco Dinuzzo, Bernhard Schölkopf
A Geometric take on Metric Learning Søren Hauberg, Oren Freifeld, Michael J. Black
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation Benjamin Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki
Online allocation and homogeneous partitioning for piecewise constant mean-approximation Alexandra Carpentier, Odalric-ambrym Maillard
Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inference Xue-xin Wei, Alan Stocker
Pointwise Tracking the Optimal Regression Function Yair Wiener, Ran El-Yaniv
Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins Alex Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun
Nonparametric Reduced Rank Regression Rina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty
Density-Difference Estimation Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus D. Plessis, Song Liu, Ichiro Takeuchi
Learning the Architecture of Sum-Product Networks Using Clustering on Variables Aaron Dennis, Dan Ventura
Towards a learning-theoretic analysis of spike-timing dependent plasticity David Balduzzi, Michel Besserve
Angular Quantization-based Binary Codes for Fast Similarity Search Yunchao Gong, Sanjiv Kumar, Vishal Verma, Svetlana Lazebnik
Matrix reconstruction with the local max norm Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov
Near-optimal Differentially Private Principal Components Kamalika Chaudhuri, Anand Sarwate, Kaushik Sinha
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification Wei Bi, James T. Kwok
Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes Jake Bouvrie, Jean-jeacques Slotine
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning Ronald Ortner, Daniil Ryabko
Perceptron Learning of SAT Alex Flint, Matthew Blaschko
On Lifting the Gibbs Sampling Algorithm Deepak Venugopal, Vibhav Gogate
Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging Chris Hinrichs, Vikas Singh, Jiming Peng, Sterling Johnson
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker
Weighted Likelihood Policy Search with Model Selection Tsuyoshi Ueno, Kohei Hayashi, Takashi Washio, Yoshinobu Kawahara

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