NeurIPS 2014

411 papers

Efficient learning by implicit exploration in bandit problems with side observations

Tomáš Kocák, Gergely Neu, Michal Valko, Rémi Munos

Pre-training of Recurrent Neural Networks via Linear Autoencoders

Luca Pasa, Alessandro Sperduti

Rounding-based Moves for Metric Labeling

M. Pawan Kumar

Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data

Florian Stimberg, Andreas Ruttor, Manfred Opper

Structure learning of antiferromagnetic Ising models

Guy Bresler, David Gamarnik, Devavrat Shah

Unsupervised learning of an efficient short-term memory network

Pietro Vertechi, Wieland Brendel, Christian K. Machens

Projective dictionary pair learning for pattern classification

Shuhang Gu, Lei Zhang, Wangmeng Zuo, Xiangchu Feng

Projecting Markov Random Field Parameters for Fast Mixing

Xianghang Liu, Justin Domke

Learning on graphs using Orthonormal Representation is Statistically Consistent

Rakesh Shivanna, Chiranjib Bhattacharyya

Automated Variational Inference for Gaussian Process Models

Trung V Nguyen, Edwin V. Bonilla

Distributed Balanced Clustering via Mapping Coresets

Mohammadhossein Bateni, Aditya Bhaskara, Silvio Lattanzi, Vahab Mirrokni

Sparse Polynomial Learning and Graph Sketching

Murat Kocaoglu, Karthikeyan Shanmugam, Alexandros G Dimakis, Adam Klivans

Feedback Detection for Live Predictors

Stefan Wager, Nick Chamandy, Omkar Muralidharan, Amir Najmi

Multivariate f-divergence Estimation With Confidence

Kevin Moon, Alfred Hero

On the relations of LFPs & Neural Spike Trains

David E Carlson, Jana Schaich Borg, Kafui Dzirasa, Lawrence Carin

Coresets for k-Segmentation of Streaming Data

Guy Rosman, Mikhail Volkov, Dan Feldman, John W. Fisher III, Daniela Rus

Convolutional Kernel Networks

Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid

Universal Option Models

Hengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar

Parallel Sampling of HDPs using Sub-Cluster Splits

Jason Chang, John W. Fisher III

An Accelerated Proximal Coordinate Gradient Method

Qihang Lin, Zhaosong Lu, Lin Xiao

Metric Learning for Temporal Sequence Alignment

Damien Garreau, Rémi Lajugie, Sylvain Arlot, Francis Bach

Constrained convex minimization via model-based excessive gap

Volkan Cevher, Quoc Tran Dinh, Quoc Tran-Dinh

Bayes-Adaptive Simulation-based Search with Value Function Approximation

Arthur Guez, Nicolas Heess, David Silver, Peter Dayan

An Integer Polynomial Programming Based Framework for Lifted MAP Inference

Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav G Gogate

How hard is my MDP?" The distribution-norm to the rescue"

Odalric-ambrym Maillard, Timothy A Mann, Shie Mannor

Incremental Clustering: The Case for Extra Clusters

Margareta Ackerman, Sanjoy Dasgupta

Content-based recommendations with Poisson factorization

Prem Gopalan, Laurent Charlin, David Blei

Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing

Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan, Michael I Jordan

Efficient Sampling for Learning Sparse Additive Models in High Dimensions

Hemant Tyagi, Bernd Gärtner, Andreas Krause

Semi-supervised Learning with Deep Generative Models

Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling

Repeated Contextual Auctions with Strategic Buyers

Kareem Amin, Afshin Rostamizadeh, Umar Syed

Parallel Direction Method of Multipliers

Huahua Wang, Arindam Banerjee, Zhi-Quan Luo

Articulated Pose Estimation by a Graphical Model with Image Dependent Pairwise Relations

Xianjie Chen, Alan L. Yuille

Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers

Mehryar Mohri, Andres Munoz

Large-scale L-BFGS using MapReduce

Weizhu Chen, Zhenghao Wang, Jingren Zhou

Learning a Concept Hierarchy from Multi-labeled Documents

Viet-An Nguyen, Jordan L Ying, Philip Resnik, Jonathan Chang

Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems

Cong Han Lim, Stephen Wright

Bregman Alternating Direction Method of Multipliers

Huahua Wang, Arindam Banerjee

A Safe Screening Rule for Sparse Logistic Regression

Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye

Predictive Entropy Search for Efficient Global Optimization of Black-box Functions

José Miguel Hernández-Lobato, Matthew W Hoffman, Zoubin Ghahramani

Stochastic variational inference for hidden Markov models

Nicholas Foti, Jason Xu, Dillon Laird, Emily B. Fox

Parallel Double Greedy Submodular Maximization

Xinghao Pan, Stefanie Jegelka, Joseph E Gonzalez, Joseph K. Bradley, Michael I. Jordan

Concavity of reweighted Kikuchi approximation

Po-ling Loh, Andre Wibisono

A Bayesian model for identifying hierarchically organised states in neural population activity

Patrick Putzky, Florian Franzen, Giacomo Bassetto, Jakob H. Macke

Making Pairwise Binary Graphical Models Attractive

Nicholas Ruozzi, Tony Jebara

Design Principles of the Hippocampal Cognitive Map

Kimberly L Stachenfeld, Matthew Botvinick, Samuel J Gershman

Fast Sampling-Based Inference in Balanced Neuronal Networks

Guillaume Hennequin, Laurence Aitchison, Máté Lengyel

Diverse Sequential Subset Selection for Supervised Video Summarization

Boqing Gong, Wei-Lun Chao, Kristen Grauman, Fei Sha

Tight Continuous Relaxation of the Balanced k-Cut Problem

Syama Sundar Rangapuram, Pramod Kaushik Mudrakarta, Matthias Hein

Learning the Learning Rate for Prediction with Expert Advice

Wouter M. Koolen, Tim van Erven, Peter Grünwald

A Unified Semantic Embedding: Relating Taxonomies and Attributes

Sung Ju Hwang, Leonid Sigal

Efficient Partial Monitoring with Prior Information

Hastagiri P Vanchinathan, Gabor Bartok, Andreas Krause

Optimizing F-Measures by Cost-Sensitive Classification

Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet

Shaping Social Activity by Incentivizing Users

Mehrdad Farajtabar, Nan Du, Manuel Gomez Rodriguez, Isabel Valera, Hongyuan Zha

Low-dimensional models of neural population activity in sensory cortical circuits

Evan W Archer, Urs Koster, Jonathan W Pillow, Jakob H. Macke

The Infinite Mixture of Infinite Gaussian Mixtures

Halid Z Yerebakan, Bartek Rajwa, Murat Dundar

Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks

Yanping Huang, Rajesh P. Rao

Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology

Mehmet Gönen, Adam A Margolin

Sequence to Sequence Learning with Neural Networks

Ilya Sutskever, Oriol Vinyals, Quoc V Le

Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning

Mohammad Taha Bahadori, Qi (Rose) Yu, Yan Liu

Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks

Yuanyuan Mi, C. C. Alan Fung, K. Y. Michael Wong, Si Wu

Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings

Sebastian Stober, Daniel J Cameron, Jessica A Grahn

Learning to Discover Efficient Mathematical Identities

Wojciech Zaremba, Karol Kurach, Rob Fergus

Quantized Estimation of Gaussian Sequence Models in Euclidean Balls

Yuancheng Zhu, John Lafferty

Fairness in Multi-Agent Sequential Decision-Making

Chongjie Zhang, Julie A Shah

Learning to Search in Branch and Bound Algorithms

He He, Hal Daume III, Jason M Eisner

How transferable are features in deep neural networks?

Jason Yosinski, Jeff Clune, Yoshua Bengio, Hod Lipson

The Blinded Bandit: Learning with Adaptive Feedback

Ofer Dekel, Elad Hazan, Tomer Koren

Analysis of Brain States from Multi-Region LFP Time-Series

Kyle R Ulrich, David E Carlson, Wenzhao Lian, Jana S Borg, Kafui Dzirasa

Time--Data Tradeoffs by Aggressive Smoothing

John J Bruer, Joel A Tropp, Volkan Cevher, Stephen Becker

Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction

Katerina Fragkiadaki, Marta Salas, Pablo Arbelaez, Jitendra Malik

Optimal Teaching for Limited-Capacity Human Learners

Kaustubh R Patil, Xiaojin Zhu, Łukasz Kopeć, Bradley C. Love

Do Convnets Learn Correspondence?

Jonathan L Long, Ning Zhang, Trevor Darrell

Multitask learning meets tensor factorization: task imputation via convex optimization

Kishan Wimalawarne, Masashi Sugiyama, Ryota Tomioka

Exclusive Feature Learning on Arbitrary Structures via ℓ_1,2-norm

Deguang Kong, Ryohei Fujimaki, Ji Liu, Feiping Nie, Chris Ding

Robust Logistic Regression and Classification

Jiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan

A Wild Bootstrap for Degenerate Kernel Tests

Kacper P Chwialkowski, Dino Sejdinovic, Arthur Gretton

Analysis of Variational Bayesian Latent Dirichlet Allocation: Weaker Sparsity Than MAP

Shinichi Nakajima, Issei Sato, Masashi Sugiyama, Kazuho Watanabe, Hiroko Kobayashi

Blossom Tree Graphical Models

Zhe Liu, John Lafferty

Zeta Hull Pursuits: Learning Nonconvex Data Hulls

Yuanjun Xiong, Wei Liu, Deli Zhao, Xiaoou Tang

New Rules for Domain Independent Lifted MAP Inference

Happy Mittal, Prasoon Goyal, Vibhav G Gogate, Parag Singla

Scalable Non-linear Learning with Adaptive Polynomial Expansions

Alekh Agarwal, Alina Beygelzimer, Daniel J. Hsu, John Langford, Matus J. Telgarsky

Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space

Ian En-Hsu Yen, Ting-Wei Lin, Shou-De Lin, Pradeep K Ravikumar, Inderjit S Dhillon

A provable SVD-based algorithm for learning topics in dominant admixture corpus

Trapit Bansal, Chiranjib Bhattacharyya, Ravindran Kannan

Searching for Higgs Boson Decay Modes with Deep Learning

Peter J Sadowski, Daniel Whiteson, Pierre Baldi

Learning Generative Models with Visual Attention

Charlie Tang, Nitish Srivastava, Ruslan Salakhutdinov

Communication-Efficient Distributed Dual Coordinate Ascent

Martin Jaggi, Virginia Smith, Martin Takac, Jonathan Terhorst, Sanjay Krishnan

Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning

Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner

Scaling-up Importance Sampling for Markov Logic Networks

Deepak Venugopal, Vibhav G Gogate

Finding a sparse vector in a subspace: Linear sparsity using alternating directions

Qing Qu, Ju Sun, John Wright

Submodular Attribute Selection for Action Recognition in Video

Jingjing Zheng, Zhuolin Jiang, Rama Chellappa, Jonathon P Phillips

Deep Symmetry Networks

Robert Gens, Pedro M Domingos

Learning Mixtures of Submodular Functions for Image Collection Summarization

Sebastian Tschiatschek, Rishabh K Iyer, Haochen Wei, Jeff A. Bilmes

Quantized Kernel Learning for Feature Matching

Danfeng Qin, Xuanli Chen, Matthieu Guillaumin, Luc V Gool, Luc V. Gool

The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification

Been Kim, Cynthia Rudin, Julie A Shah

A Statistical Decision-Theoretic Framework for Social Choice

Hossein Azari Soufiani, David C. Parkes, Lirong Xia

Near-optimal sample compression for nearest neighbors

Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch

Elementary Estimators for Graphical Models

Eunho Yang, Aurelie C. Lozano, Pradeep K Ravikumar

Tight convex relaxations for sparse matrix factorization

Emile Richard, Guillaume R. Obozinski, Jean-philippe Vert

Recurrent Models of Visual Attention

Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu