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ORCID25. NIPS 2012: Lake Tahoe, Nevada, USA
- Peter L. Bartlett, Fernando C. N. Pereira, Christopher J. C. Burges, Léon Bottou, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. 2012 - Andrew Ziegler, Eric M. Christiansen, David J. Kriegman, Serge J. Belongie:
Locally Uniform Comparison Image Descriptor. 1-9 - Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf:
Learning from Distributions via Support Measure Machines. 10-18 - Ehsan Elhamifar, Guillermo Sapiro, René Vidal:
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery. 19-27 - Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin:
Feature Clustering for Accelerating Parallel Coordinate Descent. 28-36 - Chuanxin Minos Niu, Sirish K. Nandyala, Won Joon Sohn, Terence D. Sanger:
Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA. 37-45 - Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani:
Active Learning of Model Evidence Using Bayesian Quadrature. 46-54 - Dahua Lin, John W. Fisher III:
Coupling Nonparametric Mixtures via Latent Dirichlet Processes. 55-63 - Minjie Xu, Jun Zhu, Bo Zhang:
Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction. 64-72 - Feng Cao, Soumya Ray:
Bayesian Hierarchical Reinforcement Learning. 73-81 - Christoph H. Lampert:
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction. 82-90 - Joseph Wang, Venkatesh Saligrama:
Local Supervised Learning through Space Partitioning. 91-99 - S. M. Ali Eslami, Christopher K. I. Williams:
A Generative Model for Parts-based Object Segmentation. 100-107 - Jianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian:
Super-Bit Locality-Sensitive Hashing. 108-116 - Nicholas Ruozzi
:
The Bethe Partition Function of Log-supermodular Graphical Models. 117-125 - Hossein Azari Soufiani, David C. Parkes, Lirong Xia:
Random Utility Theory for Social Choice. 126-134 - Wouter M. Koolen, Dmitry Adamskiy, Manfred K. Warmuth:
Putting Bayes to sleep. 135-143 - Suvrit Sra:
A new metric on the manifold of kernel matrices with application to matrix geometric means. 144-152 - Wei Bi, James T. Kwok:
Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification. 153-161 - Tuo Zhao, Kathryn Roeder, Han Liu:
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation. 162-170 - Fang Han, Han Liu:
Semiparametric Principal Component Analysis. 171-179 - Shinsuke Koyama:
Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing. 180-188 - Francesco Dinuzzo, Bernhard Schölkopf:
The representer theorem for Hilbert spaces: a necessary and sufficient condition. 189-196 - Clément Calauzènes, Nicolas Usunier, Patrick Gallinari:
"On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking". 197-205 - Manuel Lopes, Tobias Lang, Marc Toussaint, Pierre-Yves Oudeyer:
Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress. 206-214 - Purushottam Kar, Prateek Jain:
Supervised Learning with Similarity Functions. 215-223 - Yuxuan Wang, DeLiang Wang:
Cocktail Party Processing via Structured Prediction. 224-232 - Takayuki Osogami:
Robustness and risk-sensitivity in Markov decision processes. 233-241 - Xiaolong Wang, Liang Lin:
Dynamical And-Or Graph Learning for Object Shape Modeling and Detection. 242-250 - Alexandra Carpentier, Rémi Munos:
Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions. 251-259 - Varun Kanade, Zhenming Liu, Bozidar Radunovic:
Distributed Non-Stochastic Experts. 260-268 - Allison Chang, Dimitris Bertsimas, Cynthia Rudin:
An Integer Optimization Approach to Associative Classification. 269-277 - Tomasz Trzcinski, C. Mario Christoudias, Vincent Lepetit, Pascal Fua:
Learning Image Descriptors with the Boosting-Trick. 278-286 - Chunxiao Zhou, Jiseong Park, Yun Fu:
Fast Resampling Weighted v-Statistics. 287-295 - Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He:
Multi-task Vector Field Learning. 296-304 - Aditya Khosla, Jianxiong Xiao, Antonio Torralba, Aude Oliva:
Memorability of Image Regions. 305-313 - Jaedeug Choi, Kee-Eung Kim:
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions. 314-322 - Joonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon:
Automatic Feature Induction for Stagewise Collaborative Filtering. 323-331 - Quanquan Gu, Tong Zhang, Chris H. Q. Ding, Jiawei Han:
Selective Labeling via Error Bound Minimization. 332-340 - Koby Crammer, Tal Wagner:
Volume Regularization for Binary Classification. 341-349 - Junyuan Xie, Linli Xu, Enhong Chen:
Image Denoising and Inpainting with Deep Neural Networks. 350-358 - Du Tran, Junsong Yuan:
Max-Margin Structured Output Regression for Spatio-Temporal Action Localization. 359-367 - Fang Han, Han Liu:
Transelliptical Component Analysis. 368-376 - Hankz Hankui Zhuo, Qiang Yang, Subbarao Kambhampati:
Action-Model Based Multi-agent Plan Recognition. 377-385 - Angela Eigenstetter, Björn Ommer:
Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity. 386-394 - Nikhil Bhat, Ciamac C. Moallemi, Vivek F. Farias:
Non-parametric Approximate Dynamic Programming via the Kernel Method. 395-403 - Xi Chen, Qihang Lin, Javier Peña:
Optimal Regularized Dual Averaging Methods for Stochastic Optimization. 404-412 - Emanuele Coviello, Antoni B. Chan, Gert R. G. Lanckriet:
The variational hierarchical EM algorithm for clustering hidden Markov models. 413-421 - Chong Wang, David M. Blei:
Truncation-free Online Variational Inference for Bayesian Nonparametric Models. 422-430 - Hyun Soo Park, Eakta Jain, Yaser Sheikh:
3D Social Saliency from Head-mounted Cameras. 431-439 - Peter Kontschieder, Samuel Rota Bulò, Antonio Criminisi, Pushmeet Kohli, Marcello Pelillo, Horst Bischof:
Context-Sensitive Decision Forests for Object Detection. 440-448 - Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, O. Anatole von Lilienfeld, Klaus-Robert Müller:
Learning Invariant Representations of Molecules for Atomization Energy Prediction. 449-457 - Joan Fruitet, Alexandra Carpentier, Rémi Munos, Maureen Clerc:
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button. 458-466 - Jeremy C. Weiss, Sriraam Natarajan, David Page:
Multiplicative Forests for Continuous-Time Processes. 467-475 - Jenna Wiens, John V. Guttag, Eric Horvitz:
Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification Task. 476-484 - Tianbao Yang, Yufeng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou:
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. 485-493 - Amit Daniely, Sivan Sabato, Shai Shalev-Shwartz:
Multiclass Learning Approaches: A Theoretical Comparison with Implications. 494-502 - Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi:
Stochastic Gradient Descent with Only One Projection. 503-511 - Dmitri B. Chklovskii, Daniel Soudry:
"Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter". 512-520 - Pietro Di Lena, Pierre Baldi, Ken Nagata:
Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction. 521-529 - Ognjen Arandjelovic:
Assessing Blinding in Clinical Trials. 530-538 - Suvrit Sra:
Scalable nonconvex inexact proximal splitting. 539-547 - Julian J. McAuley, Jure Leskovec:
Learning to Discover Social Circles in Ego Networks. 548-556 - Li-Ping Liu, Thomas G. Dietterich:
A Conditional Multinomial Mixture Model for Superset Label Learning. 557-565 - Tony Jebara, Anna Choromanska:
Majorization for CRFs and Latent Likelihoods. 566-574 - Kumar Sricharan, Alfred O. Hero III:
Ensemble weighted kernel estimators for multivariate entropy estimation. 575-583 - Paul Vernaza, Drew Bagnell:
Efficient high dimensional maximum entropy modeling via symmetric partition functions. 584-592 - Xiaofeng Ren, Liefeng Bo:
Discriminatively Trained Sparse Code Gradients for Contour Detection. 593-601 - Mohsen Hejrati, Deva Ramanan:
Analyzing 3D Objects in Cluttered Images. 602-610 - Zhihua Zhang, Bojun Tu:
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates. 611-619 - Sanja Fidler, Sven J. Dickinson, Raquel Urtasun:
3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model. 620-628 - Karthik Mohan, Michael Jae-Yoon Chung, Seungyeop Han, Daniela M. Witten, Su-In Lee, Maryam Fazel:
Structured Learning of Gaussian Graphical Models. 629-637 - Elad Hazan, Zohar Shay Karnin:
A Polylog Pivot Steps Simplex Algorithm for Classification. 638-646 - Kevin D. Tang, Vignesh Ramanathan, Li Fei-Fei, Daphne Koller:
Shifting Weights: Adapting Object Detectors from Image to Video. 647-655 - Shusen Wang, Zhihua Zhang:
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound. 656-664 - Richard Socher, Brody Huval, Bharath Putta Bath, Christopher D. Manning, Andrew Y. Ng:
Convolutional-Recursive Deep Learning for 3D Object Classification. 665-673 - David López-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf:
Semi-Supervised Domain Adaptation with Non-Parametric Copulas. 674-682 - Firdaus Janoos, Weichang Li, Niranjan A. Subrahmanya, István Ákos Mórocz, William M. Wells III:
Identification of Recurrent Patterns in the Activation of Brain Networks. 683-691 - Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi:
Density-Difference Estimation. 692-700 - Qiang Liu, Jian Peng, Alexander Ihler:
Variational Inference for Crowdsourcing. 701-709 - Vinayak A. Rao, Yee Whye Teh:
MCMC for continuous-time discrete-state systems. 710-718 - Pieter-Jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen:
A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling. 719-727 - Elad Mezuman, Yair Weiss:
Learning about Canonical Views from Internet Image Collections. 728-736 - Assaf Glazer, Michael Lindenbaum, Shaul Markovitch:
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data. 737-745 - Emily B. Fox, David B. Dunson:
Multiresolution Gaussian Processes. 746-754 - Jianxiong Xiao, Bryan C. Russell, Antonio Torralba:
Localizing 3D cuboids in single-view images. 755-763 - Peder A. Olsen, Figen Öztoprak, Jorge Nocedal, Steven J. Rennie:
Newton-Like Methods for Sparse Inverse Covariance Estimation. 764-772 - Gary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller:
Learning to Align from Scratch. 773-781 - Stefan Habenschuss, Johannes Bill, Bernhard Nessler:
Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints. 782-790 - Nan Li, Longin Jan Latecki:
Clustering Aggregation as Maximum-Weight Independent Set. 791-799 - Marcelo Fiori, Pablo Musé, Guillermo Sapiro:
Topology Constraints in Graphical Models. 800-808 - Han Liu, Fang Han, Cun-Hui Zhang:
Transelliptical Graphical Models. 809-817 - Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori:
Kernel Latent SVM for Visual Recognition. 818-826 - Erik Talvitie:
Learning Partially Observable Models Using Temporally Abstract Decision Trees. 827-835 - Jason D. Lee, Yuekai Sun, Michael A. Saunders:
Proximal Newton-type methods for convex optimization. 836-844 - Bo Liu, Sridhar Mahadevan, Ji Liu:
Regularized Off-Policy TD-Learning. 845-853 - Ko-Jen Hsiao, Kevin S. Xu, Jeff Calder, Alfred O. Hero III:
Multi-criteria Anomaly Detection using Pareto Depth Analysis. 854-862 - Jake V. Bouvrie, Jean-Jacques E. Slotine:
Synchronization can Control Regularization in Neural Systems via Correlated Noise Processes. 863-871 - Tingni Sun, Cun-Hui Zhang:
Calibrated Elastic Regularization in Matrix Completion. 872-880 - Uri Maoz, Shengxuan Ye, Ian B. Ross, Adam N. Mamelak, Christof Koch:
Predicting Action Content On-Line and in Real Time before Action Onset - an Intracranial Human Study. 881-889 - Bogdan Alexe, Nicolas Heess, Yee Whye Teh, Vittorio Ferrari:
Searching for objects driven by context. 890-898 - Sergey Karayev, Tobias Baumgartner, Mario Fritz, Trevor Darrell:
Timely Object Recognition. 899-907 - Gal Elidan, Cobi Cario:
Nonparanormal Belief Propagation (NPNBP). 908-916 - Ryan Kiros, Csaba Szepesvári:
Deep Representations and Codes for Image Auto-Annotation. 917-925 - Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-Kai Liu:
A Spectral Algorithm for Latent Dirichlet Allocation. 926-934 - Aharon Birnbaum, Shai Shalev-Shwartz:
Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs. 935-943 - Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov:
Matrix reconstruction with the local max norm. 944-952 - Anteo Smerieri, François Duport, Yvan Paquot, Benjamin Schrauwen, Marc Haelterman, Serge Massar:
Analog readout for optical reservoir computers. 953-961 - Stephen P. Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic:
Accuracy at the Top. 962-970 - Andrew Delong, Olga Veksler, Anton Osokin, Yuri Boykov:
Minimizing Sparse High-Order Energies by Submodular Vertex-Cover. 971-979 - Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan:
Perfect Dimensionality Recovery by Variational Bayesian PCA. 980-988 - Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz:
Mirror Descent Meets Fixed Share (and feels no regret). 989-997 - Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha:
Near-optimal Differentially Private Principal Components. 998-1006 - James Robert Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy:
Random function priors for exchangeable arrays with applications to graphs and relational data. 1007-1015 - Edouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin:
Inverse Reinforcement Learning through Structured Classification. 1016-1024 - Ashwini Shukla, Aude Billard:
Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics. 1025-1033 - Arthur Guez, David Silver, Peter Dayan:
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. 1034-1042 - Chi Jin, Liwei Wang:
Dimensionality Dependent PAC-Bayes Margin Bound. 1043-1051 - Animashree Anandkumar, Ragupathyraj Valluvan:
Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs. 1052-1060 - Animashree Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade:
Learning Mixtures of Tree Graphical Models. 1061-1069 - Mohammad Norouzi, David J. Fleet, Ruslan Salakhutdinov:
Hamming Distance Metric Learning. 1070-1078 - Romain Daniel Cazé, Mark D. Humphries, Boris S. Gutkin:
Spiking and saturating dendrites differentially expand single neuron computation capacity. 1079-1087