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ORCIDNIPS 2014: Montreal, Quebec, Canada
- Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. 2014
- Krikamol Muandet, Bharath K. Sriperumbudur, Bernhard Schölkopf:
Kernel Mean Estimation via Spectral Filtering. 1-9 - Yichuan Zhang, Charles Sutton:
Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models. 10-18 - Mu Li, David G. Andersen, Alexander J. Smola, Kai Yu:
Communication Efficient Distributed Machine Learning with the Parameter Server. 19-27 - Halid Ziya Yerebakan, Bartek Rajwa, Murat Dundar:
The Infinite Mixture of Infinite Gaussian Mixtures. 28-36 - Anqi Liu, Brian D. Ziebart:
Robust Classification Under Sample Selection Bias. 37-45 - Yuanjun Xiong, Wei Liu, Deli Zhao, Xiaoou Tang:
Zeta Hull Pursuits: Learning Nonconvex Data Hulls. 46-54 - Katerina Fragkiadaki, Marta Salas, Pablo Andrés Arbeláez, Jitendra Malik:
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction. 55-63 - Ferran Diego Andilla, Fred A. Hamprecht:
Sparse Space-Time Deconvolution for Calcium Image Analysis. 64-72 - Takayuki Osogami, Makoto Otsuka:
Restricted Boltzmann machines modeling human choice. 73-81 - Pedro F. Felzenszwalb, John G. Oberlin:
Multiscale Fields of Patterns. 82-90 - Yichao Lu, Dean P. Foster:
large scale canonical correlation analysis with iterative least squares. 91-99 - Stefan Wager, William Fithian, Sida Wang, Percy Liang:
Altitude Training: Strong Bounds for Single-Layer Dropout. 100-108 - M. Pawan Kumar:
Rounding-based Moves for Metric Labeling. 109-117 - Xinghao Pan, Stefanie Jegelka, Joseph E. Gonzalez, Joseph K. Bradley, Michael I. Jordan:
Parallel Double Greedy Submodular Maximization. 118-126 - Han Liu, Lie Wang, Tuo Zhao:
Multivariate Regression with Calibration. 127-135 - Jason D. Lee, Jonathan E. Taylor:
Exact Post Model Selection Inference for Marginal Screening. 136-144 - Yingzhen Yang, Feng Liang, Shuicheng Yan, Zhangyang Wang, Thomas S. Huang:
On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification. 145-153 - S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli, John M. Winn:
Just-In-Time Learning for Fast and Flexible Inference. 154-162 - Ohad Shamir:
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation. 163-171 - Danfeng Qin, Xuanli Chen, Matthieu Guillaumin, Luc Van Gool:
Quantized Kernel Learning for Feature Matching. 172-180 - Huahua Wang, Arindam Banerjee, Zhi-Quan Luo:
Parallel Direction Method of Multipliers. 181-189 - Giorgio Patrini, Richard Nock, Tibério S. Caetano, Paul Rivera:
(Almost) No Label No Cry. 190-198 - Yonatan Gur, Assaf Zeevi, Omar Besbes:
Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards. 199-207 - Jan Feyereisl, Suha Kwak, Jeany Son, Bohyung Han:
Object Localization based on Structural SVM using Privileged Information. 208-216 - Zhenyao Zhu, Ping Luo, Xiaogang Wang, Xiaoou Tang:
Multi-View Perceptron: a Deep Model for Learning Face Identity and View Representations. 217-225 - Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman:
Shape and Illumination from Shading using the Generic Viewpoint Assumption. 226-234 - Jason Chang, John W. Fisher III:
Parallel Sampling of HDPs using Sub-Cluster Splits. 235-243 - Josip Djolonga, Andreas Krause:
From MAP to Marginals: Variational Inference in Bayesian Submodular Models. 244-252 - Jiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan:
Robust Logistic Regression and Classification. 253-261 - Tianbao Yang, Rong Jin:
Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities. 262-270 - Sung Ju Hwang, Leonid Sigal:
A Unified Semantic Embedding: Relating Taxonomies and Attributes. 271-279 - Elias Bareinboim, Judea Pearl:
Transportability from Multiple Environments with Limited Experiments: Completeness Results. 280-288 - Siamak Ravanbakhsh, Reihaneh Rabbany, Russell Greiner:
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning. 289-297 - Ricardo Silva, Robin J. Evans:
Causal Inference through a Witness Protection Program. 298-306 - Margareta Ackerman, Sanjoy Dasgupta:
Incremental Clustering: The Case for Extra Clusters. 307-315 - Firdaus Janoos, Huseyin Denli, Niranjan A. Subrahmanya:
Multi-scale Graphical Models for Spatio-Temporal Processes. 316-324 - Tapani Raiko, Li Yao, KyungHyun Cho, Yoshua Bengio:
Iterative Neural Autoregressive Distribution Estimator NADE-k. 325-333 - Yash Deshpande, Andrea Montanari:
Sparse PCA via Covariance Thresholding. 334-342 - Evan W. Archer, Urs Köster, Jonathan W. Pillow, Jakob H. Macke:
Low-dimensional models of neural population activity in sensory cortical circuits. 343-351 - Yuanyuan Mi, Luozheng Li, Dahui Wang, Si Wu:
A Synaptical Story of Persistent Activity with Graded Lifetime in a Neural System. 352-360 - Harsh H. Pareek, Pradeep Ravikumar:
A Representation Theory for Ranking Functions. 361-369 - Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch:
Near-optimal sample compression for nearest neighbors. 370-378 - Shouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen:
Combinatorial Pure Exploration of Multi-Armed Bandits. 379-387 - Minh Ha Quang, Marco San-Biagio, Vittorio Murino:
Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces. 388-396 - Debarghya Ghoshdastidar, Ambedkar Dukkipati:
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model. 397-405 - Alaa Saade, Florent Krzakala, Lenka Zdeborová:
Spectral Clustering of graphs with the Bethe Hessian. 406-414 - Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann:
Fast and Robust Least Squares Estimation in Corrupted Linear Models. 415-423 - Woonhyun Nam, Piotr Dollár, Joon Hee Han:
Local Decorrelation For Improved Pedestrian Detection. 424-432 - Robert A. Vandermeulen, Clayton D. Scott:
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space. 433-441 - Chicheng Zhang, Kamalika Chaudhuri:
Beyond Disagreement-Based Agnostic Active Learning. 442-450 - Arthur Guez, Nicolas Heess, David Silver, Peter Dayan:
Bayes-Adaptive Simulation-based Search with Value Function Approximation. 451-459 - Sahar Akram, Jonathan Z. Simon, Shihab A. Shamma, Behtash Babadi:
A State-Space Model for Decoding Auditory Attentional Modulation from MEG in a Competing-Speaker Environment. 460-468 - Sivan Sabato, Rémi Munos:
Active Regression by Stratification. 469-477 - Joseph G. Makin, Philip N. Sabes:
Sensory Integration and Density Estimation. 478-486 - Bolei Zhou, Àgata Lapedriza, Jianxiong Xiao, Antonio Torralba, Aude Oliva:
Learning Deep Features for Scene Recognition using Places Database. 487-495 - Ryan D. Turner, Steven Bottone, Bhargav Avasarala:
A Complete Variational Tracker. 496-504 - Yuanyuan Mi, C. C. Alan Fung, K. Y. Michael Wong, Si Wu:
Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks. 505-513 - Hemant Tyagi, Bernd Gärtner, Andreas Krause:
Efficient Sampling for Learning Sparse Additive Models in High Dimensions. 514-522 - Xiaolong Wang, Liliang Zhang, Liang Lin, Zhujin Liang, Wangmeng Zuo:
Deep Joint Task Learning for Generic Object Extraction. 523-531 - Changyou Chen, Jun Zhu, Xinhua Zhang:
Robust Bayesian Max-Margin Clustering. 532-540 - Deepti Pachauri, Risi Kondor, Gautam Sargur, Vikas Singh:
Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision. 541-549 - Tor Lattimore, Rémi Munos:
Bounded Regret for Finite-Armed Structured Bandits. 550-558 - Guy Rosman, Mikhail Volkov, Dan Feldman, John W. Fisher III, Daniela Rus:
Coresets for k-Segmentation of Streaming Data. 559-567 - Karen Simonyan, Andrew Zisserman:
Two-Stream Convolutional Networks for Action Recognition in Videos. 568-576 - Greg Ver Steeg, Aram Galstyan:
Discovering Structure in High-Dimensional Data Through Correlation Explanation. 577-585 - Christof Seiler, Simon Rubinstein-Salzedo, Susan P. Holmes:
Positive Curvature and Hamiltonian Monte Carlo. 586-594 - Sewoong Oh, Devavrat Shah:
Learning Mixed Multinomial Logit Model from Ordinal Data. 595-603 - Ian Osband, Benjamin Van Roy:
Near-optimal Reinforcement Learning in Factored MDPs. 604-612 - Tomás Kocák, Gergely Neu, Michal Valko, Rémi Munos:
Efficient learning by implicit exploration in bandit problems with side observations. 613-621 - Kareem Amin, Afshin Rostamizadeh, Umar Syed:
Repeated Contextual Auctions with Strategic Buyers. 622-630 - Christopher Meek, Marina Meila:
Recursive Inversion Models for Permutations. 631-639 - Robert Nishihara, Stefanie Jegelka, Michael I. Jordan:
On the Convergence Rate of Decomposable Submodular Function Minimization. 640-648 - Happy Mittal, Prasoon Goyal, Vibhav Gogate, Parag Singla:
New Rules for Domain Independent Lifted MAP Inference. 649-657 - James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang:
PAC-Bayesian AUC classification and scoring. 658-666 - Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam:
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. 667-675 - Oluwasanmi Koyejo, Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack:
On Prior Distributions and Approximate Inference for Structured Variables. 676-684 - Prateek Jain, Ambuj Tewari, Purushottam Kar:
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation. 685-693 - Purushottam Kar, Harikrishna Narasimhan, Prateek Jain:
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions. 694-702 - Marthinus Christoffel du Plessis, Gang Niu, Masashi Sugiyama:
Analysis of Learning from Positive and Unlabeled Data. 703-711 - Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju:
Dimensionality Reduction with Subspace Structure Preservation. 712-720 - Quoc Tran-Dinh, Volkan Cevher:
Constrained convex minimization via model-based excessive gap. 721-729 - Florian Stimberg, Andreas Ruttor, Manfred Opper:
Poisson Process Jumping between an Unknown Number of Rates: Application to Neural Spike Data. 730-738 - Michael Schober, David Duvenaud, Philipp Hennig:
Probabilistic ODE Solvers with Runge-Kutta Means. 739-747 - Jan Drugowitsch, Rubén Moreno-Bote, Alexandre Pouget:
Optimal decision-making with time-varying evidence reliability. 748-756 - Dongqu Chen:
Learning Shuffle Ideals Under Restricted Distributions. 757-765 - Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox:
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. 766-774 - David Adametz, Volker Roth:
Distance-Based Network Recovery under Feature Correlation. 775-783 - Elad Hazan, Kfir Y. Levy:
Bandit Convex Optimization: Towards Tight Bounds. 784-792 - Shuhang Gu, Lei Zhang, Wangmeng Zuo, Xiangchu Feng:
Projective dictionary pair learning for pattern classification. 793-801 - Deeparnab Chakrabarty, Prateek Jain, Pravesh Kothari:
Provable Submodular Minimization using Wolfe's Algorithm. 802-809 - Amir Sani, Gergely Neu, Alessandro Lazaric:
Exploiting easy data in online optimization. 810-818 - Daniele Calandriello, Alessandro Lazaric, Marcello Restelli:
Sparse Multi-Task Reinforcement Learning. 819-827 - Marta Soare, Alessandro Lazaric, Rémi Munos:
Best-Arm Identification in Linear Bandits. 828-836 - Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto:
Mind the Nuisance: Gaussian Process Classification using Privileged Noise. 837-845 - Rémi Lemonnier, Kevin Scaman, Nicolas Vayatis:
Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology. 846-854 - Roi Livni, Shai Shalev-Shwartz, Ohad Shamir:
On the Computational Efficiency of Training Neural Networks. 855-863 - Xavier Boix, Gemma Roig, Salomon Diether, Luc Van Gool:
Self-Adaptable Templates for Feature Coding. 864-872 - Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor:
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. 873-881 - XiaoJian Wu, Daniel Sheldon, Shlomo Zilberstein:
Stochastic Network Design in Bidirected Trees. 882-890 - George O. Mohler:
Learning convolution filters for inverse covariance estimation of neural network connectivity. 891-899 - Fajwel Fogel, Alexandre d'Aspremont, Milan Vojnovic:
SerialRank: Spectral Ranking using Seriation. 900-908 - Adrian Weller, Tony Jebara:
Clamping Variables and Approximate Inference. 909-917 - José Miguel Hernández-Lobato, Matthew W. Hoffman, Zoubin Ghahramani:
Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. 918-926 - Eran Treister, Javier Turek:
A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation. 927-935 - Shenlong Wang, Alexander G. Schwing, Raquel Urtasun:
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials. 936-944 - Austin R. Benson, Jason D. Lee, Bartek Rajwa, David F. Gleich:
Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices. 945-953 - Kenneth W. Latimer, E. J. Chichilnisky, Fred Rieke, Jonathan W. Pillow:
Inferring synaptic conductances from spike trains with a biophysically inspired point process model. 954-962 - Daniel Soudry, Itay Hubara, Ron Meir:
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights. 963-971 - Franziska Meier, Philipp Hennig, Stefan Schaal:
Incremental Local Gaussian Regression. 972-980 - Isabel Valera, Zoubin Ghahramani:
General Table Completion using a Bayesian Nonparametric Model. 981-989 - Hengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar:
Universal Option Models. 990-998 - Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch:
Approximating Hierarchical MV-sets for Hierarchical Clustering. 999-1007 - Ian En-Hsu Yen, Cho-Jui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon:
Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings. 1008-1016 - Deanna Needell, Rachel Ward, Nathan Srebro:
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm. 1017-1025 - Luigi Acerbi, Wei Ji Ma, Sethu Vijayakumar:
A Framework for Testing Identifiability of Bayesian Models of Perception. 1026-1034 - Balázs Szörényi, Gunnar Kedenburg, Rémi Munos:
Optimistic Planning in Markov Decision Processes Using a Generative Model. 1035-1043 - Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani:
Gaussian Process Volatility Model. 1044-1052 - Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, Jieping Ye:
A Safe Screening Rule for Sparse Logistic Regression. 1053-1061 - Guy Bresler, David Gamarnik, Devavrat Shah:
Hardness of parameter estimation in graphical models. 1062-1070 - Sergey Levine, Pieter Abbeel:
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics. 1071-1079 - Nisheeth Srivastava, Ed Vul, Paul R. Schrater:
Magnitude-sensitive preference formation. 1080-1088 - Alexandra Carpentier, Michal Valko:
Extreme bandits. 1089-1097