NeurIPS 2012
370 papers
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon, Pradeep K. Ravikumar A Geometric Take on Metric Learning
Søren Hauberg, Oren Freifeld, Michael J. Black A Latent Factor Model for Highly Multi-Relational Data
Rodolphe Jenatton, Nicolas L. Roux, Antoine Bordes, Guillaume R. Obozinski A Linear Time Active Learning Algorithm for Link Classification
Nicolò Cesa-bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella A Nonparametric Variable Clustering Model
Konstantina Palla, Zoubin Ghahramani, David A. Knowles A Polynomial-Time Form of Robust Regression
Yao-liang Yu, Özlem Aslan, Dale Schuurmans A Spectral Algorithm for Latent Dirichlet Allocation
Anima Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-kai Liu Accuracy at the Top
Stephen Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic Action-Model Based Multi-Agent Plan Recognition
Hankz H. Zhuo, Qiang Yang, Subbarao Kambhampati Active Comparison of Prediction Models
Christoph Sawade, Niels Landwehr, Tobias Scheffer Active Learning of Model Evidence Using Bayesian Quadrature
Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts, Carl E. Rasmussen Algorithms for Learning Markov Field Policies
Abdeslam Boularias, Jan R. Peters, Oliver B. Kroemer Analog Readout for Optical Reservoir Computers
Anteo Smerieri, François Duport, Yvon Paquot, Benjamin Schrauwen, Marc Haelterman, Serge Massar Ancestor Sampling for Particle Gibbs
Fredrik Lindsten, Thomas Schön, Michael I. Jordan Bayesian Models for Large-Scale Hierarchical Classification
Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-mizil Bayesian Nonparametric Modeling of Suicide Attempts
Francisco Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz Cardinality Restricted Boltzmann Machines
Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov, Ryan P. Adams Clustering Sparse Graphs
Yudong Chen, Sujay Sanghavi, Huan Xu Collaborative Gaussian Processes for Preference Learning
Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Jose M. Hernández-lobato Context-Sensitive Decision Forests for Object Detection
Peter Kontschieder, Samuel R. Bulò, Antonio Criminisi, Pushmeet Kohli, Marcello Pelillo, Horst Bischof Continuous Relaxations for Discrete Hamiltonian Monte Carlo
Yichuan Zhang, Zoubin Ghahramani, Amos J. Storkey, Charles A. Sutton Convergence and Energy Landscape for Cheeger Cut Clustering
Xavier Bresson, Thomas Laurent, David Uminsky, James V. Brecht Convex Multi-View Subspace Learning
Martha White, Xinhua Zhang, Dale Schuurmans, Yao-liang Yu Convolutional-Recursive Deep Learning for 3D Object Classification
Richard Socher, Brody Huval, Bharath Bath, Christopher D. Manning, Andrew Y. Ng Density-Difference Estimation
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus D. Plessis, Song Liu, Ichiro Takeuchi Distributed Non-Stochastic Experts
Varun Kanade, Zhenming Liu, Bozidar Radunovic Entangled Monte Carlo
Seong-hwan Jun, Liangliang Wang, Alexandre Bouchard-côté Factoring Nonnegative Matrices with Linear Programs
Ben Recht, Christopher Re, Joel Tropp, Victor Bittorf FastEx: Hash Clustering with Exponential Families
Amr Ahmed, Sujith Ravi, Alex J. Smola, Shravan M. Narayanamurthy Feature Clustering for Accelerating Parallel Coordinate Descent
Chad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin Fusion with Diffusion for Robust Visual Tracking
Yu Zhou, Xiang Bai, Wenyu Liu, Longin J. Latecki GenDeR: A Generic Diversified Ranking Algorithm
Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw Szymanski Graphical Models via Generalized Linear Models
Eunho Yang, Genevera Allen, Zhandong Liu, Pradeep K. Ravikumar Hamming Distance Metric Learning
Mohammad Norouzi, David J Fleet, Ruslan Salakhutdinov Hierarchical Spike Coding of Sound
Yan Karklin, Chaitanya Ekanadham, Eero P. Simoncelli Human Memory Search as a Random Walk in a Semantic Network
Joseph L. Austerweil, Joshua T. Abbott, Thomas L. Griffiths Identification of Recurrent Patterns in the Activation of Brain Networks
Firdaus Janoos, Weichang Li, Niranjan Subrahmanya, Istvan Morocz, William Wells Imitation Learning by Coaching
He He, Jason Eisner, Hal Daume Interpreting Prediction Markets: A Stochastic Approach
Rafael M. Frongillo, Nicolas Della Penna, Mark D. Reid Isotropic Hashing
Weihao Kong, Wu-jun Li Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
Benjamin Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki Kernel Hyperalignment
Alexander Lorbert, Peter J. Ramadge Kernel Latent SVM for Visual Recognition
Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori 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 Learning from Distributions via Support Measure Machines
Krikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf Learning Image Descriptors with the Boosting-Trick
Tomasz Trzcinski, Mario Christoudias, Vincent Lepetit, Pascal Fua 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 Learning Manifolds with K-Means and K-Flats
Guillermo Canas, Tomaso Poggio, Lorenzo Rosasco Learning Mixtures of Tree Graphical Models
Anima Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade Learning Optimal Spike-Based Representations
Ralph Bourdoukan, David Barrett, Sophie Deneve, Christian K. Machens Learning the Dependency Structure of Latent Factors
Yunlong He, Yanjun Qi, Koray Kavukcuoglu, Haesun Park Learning to Align from Scratch
Gary Huang, Marwan Mattar, Honglak Lee, Erik G. Learned-miller Learning with Partially Absorbing Random Walks
Xiao-ming Wu, Zhenguo Li, Anthony M. So, John Wright, Shih-fu Chang Learning with Recursive Perceptual Representations
Oriol Vinyals, Yangqing Jia, Li Deng, Trevor Darrell Learning with Target Prior
Zuoguan Wang, Siwei Lyu, Gerwin Schalk, Qiang Ji Localizing 3D Cuboids in Single-View Images
Jianxiong Xiao, Bryan Russell, Antonio Torralba Locally Uniform Comparison Image Descriptor
Andrew Ziegler, Eric Christiansen, David Kriegman, Serge J. Belongie MAP Inference in Chains Using Column Generation
David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum Matrix Reconstruction with the Local Max Norm
Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov Memorability of Image Regions
Aditya Khosla, Jianxiong Xiao, Antonio Torralba, Aude Oliva Minimizing Uncertainty in Pipelines
Nilesh Dalvi, Aditya Parameswaran, Vibhor Rastogi Mirror Descent Meets Fixed Share (and Feels No Regret)
Nicolò Cesa-bianchi, Pierre Gaillard, Gabor Lugosi, Gilles Stoltz Mixability in Statistical Learning
Tim V. Erven, Peter Grünwald, Mark D. Reid, Robert C. Williamson Multi-Stage Multi-Task Feature Learning
Pinghua Gong, Jieping Ye, Chang-shui Zhang Multi-Task Averaging
Sergey Feldman, Maya Gupta, Bela Frigyik Multi-Task Vector Field Learning
Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He Multiclass Learning with Simplex Coding
Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco, Jean-jeacques Slotine Multiple Operator-Valued Kernel Learning
Hachem Kadri, Alain Rakotomamonjy, Philippe Preux, Francis R. Bach Newton-like Methods for Sparse Inverse Covariance Estimation
Figen Oztoprak, Jorge Nocedal, Steven Rennie, Peder A. Olsen Non-Linear Metric Learning
Dor Kedem, Stephen Tyree, Fei Sha, Gert R. Lanckriet, Kilian Q. Weinberger Nonparametric Reduced Rank Regression
Rina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty One Permutation Hashing
Ping Li, Art Owen, Cun-hui Zhang Online Sum-Product Computation over Trees
Mark Herbster, Stephen Pasteris, Fabio Vitale Optimal Kernel Choice for Large-Scale Two-Sample Tests
Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu, Bharath K. Sriperumbudur Perceptron Learning of SAT
Alex Flint, Matthew Blaschko Perfect Dimensionality Recovery by Variational Bayesian PCA
Shinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. D. Babacan Privacy Aware Learning
Martin J. Wainwright, Michael I. Jordan, John C. Duchi Probabilistic Low-Rank Subspace Clustering
S. D. Babacan, Shinichi Nakajima, Minh Do Probabilistic N-Choose-K Models for Classification and Ranking
Kevin Swersky, Brendan J. Frey, Daniel Tarlow, Richard S. Zemel, Ryan P. Adams Putting Bayes to Sleep
Dmitry Adamskiy, Manfred K. Warmuth, Wouter M. Koolen Random Utility Theory for Social Choice
Hossein Azari, David Parks, Lirong Xia Regularized Off-Policy TD-Learning
Bo Liu, Sridhar Mahadevan, Ji Liu Relax and Randomize : From Value to Algorithms
Sasha Rakhlin, Ohad Shamir, Karthik Sridharan Repulsive Mixtures
Francesca Petralia, Vinayak Rao, David B. Dunson Risk-Aversion in Multi-Armed Bandits
Amir Sani, Alessandro Lazaric, Rémi Munos Scalable Inference of Overlapping Communities
Prem Gopalan, Sean Gerrish, Michael Freedman, David M. Blei, David M. Mimno Searching for Objects Driven by Context
Bogdan Alexe, Nicolas Heess, Yee W. Teh, Vittorio Ferrari Selective Labeling via Error Bound Minimization
Quanquan Gu, Tong Zhang, Jiawei Han, Chris H. Ding Semi-Supervised Domain Adaptation with Non-Parametric Copulas
David Lopez-paz, Jose M. Hernández-lobato, Bernhard Schölkopf Slice Normalized Dynamic Markov Logic Networks
Tivadar Papai, Henry Kautz, Daniel Stefankovic Sparse Prediction with the $k$-Support Norm
Andreas Argyriou, Rina Foygel, Nathan Srebro Stochastic Gradient Descent with Only One Projection
Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi Structured Learning of Gaussian Graphical Models
Karthik Mohan, Mike Chung, Seungyeop Han, Daniela Witten, Su-in Lee, Maryam Fazel Super-Bit Locality-Sensitive Hashing
Jianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian The Lovász Θ Function, SVMs and Finding Large Dense Subgraphs
Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt Dubhashi The Perturbed Variation
Maayan Harel, Shie Mannor Timely Object Recognition
Sergey Karayev, Tobias Baumgartner, Mario Fritz, Trevor Darrell Topic-Partitioned Multinetwork Embeddings
Peter Krafft, Juston Moore, Bruce Desmarais, Hanna M. Wallach Topology Constraints in Graphical Models
Marcelo Fiori, Pablo Musé, Guillermo Sapiro Transelliptical Graphical Models
Han Liu, Fang Han, Cun-hui Zhang Value Pursuit Iteration
Amir M. Farahmand, Doina Precup 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 Weighted Likelihood Policy Search with Model Selection
Tsuyoshi Ueno, Kohei Hayashi, Takashi Washio, Yoshinobu Kawahara