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ORCID24. NIPS 2011: Granada, Spain
- John Shawe-Taylor, Richard S. Zemel, Peter L. Bartlett, Fernando C. N. Pereira, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain. 2011
- Hua Wang, Heng Huang, Farhad Kamangar, Feiping Nie, Chris H. Q. Ding:
Maximum Margin Multi-Instance Learning. 1-9 - Francis R. Bach:
Shaping Level Sets with Submodular Functions. 10-18 - Sergey Levine, Zoran Popovic, Vladlen Koltun:
Nonlinear Inverse Reinforcement Learning with Gaussian Processes. 19-27 - Carl Vondrick, Deva Ramanan:
Video Annotation and Tracking with Active Learning. 28-36 - Stéphan Clémençon:
On U-processes and clustering performance. 37-45 - Yong Zhang, Zhaosong Lu:
Penalty Decomposition Methods for Rank Minimization. 46-54 - Ehsan Elhamifar, René Vidal:
Sparse Manifold Clustering and Embedding. 55-63 - Siwei Lyu:
Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction. 64-72 - Yibiao Zhao, Song Chun Zhu:
Image Parsing with Stochastic Scene Grammar. 73-81 - Mehdi Keramati, Boris S. Gutkin:
A Reinforcement Learning Theory for Homeostatic Regulation. 82-90 - Philip M. Long, Rocco A. Servedio:
Learning large-margin halfspaces with more malicious noise. 91-99 - Richard G. Gibson, Duane Szafron:
On Strategy Stitching in Large Extensive Form Multiplayer Games. 100-108 - Philipp Krähenbühl, Vladlen Koltun:
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. 109-117 - Joseph J. Lim, Ruslan Salakhutdinov, Antonio Torralba:
Transfer Learning by Borrowing Examples for Multiclass Object Detection. 118-126 - Dylan A. Simon, Nathaniel D. Daw:
Environmental statistics and the trade-off between model-based and TD learning in humans. 127-135 - Danilo Jimenez Rezende, Daan Wierstra, Wulfram Gerstner:
Variational Learning for Recurrent Spiking Networks. 136-144 - Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence:
Multiple Instance Learning on Structured Data. 145-153 - Nitesh Shroff, Pavan K. Turaga
, Rama Chellappa:
Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds. 154-162 - Ali Tofigh, Erik Sjölund, Mattias Höglund, Jens Lagergren:
A Global Structural EM Algorithm for a Model of Cancer Progression. 163-171 - Amir Massoud Farahmand:
Action-Gap Phenomenon in Reinforcement Learning. 172-180 - Nobuyuki Morioka, Shin'ichi Satoh:
Generalized Lasso based Approximation of Sparse Coding for Visual Recognition. 181-189 - Ricardo Silveira Cabral, Fernando De la Torre, João Paulo Costeira, Alexandre Bernardino:
Matrix Completion for Multi-label Image Classification. 190-198 - Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Multi-View Learning of Word Embeddings via CCA. 199-207 - Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan:
Global Solution of Fully-Observed Variational Bayesian Matrix Factorization is Column-Wise Independent. 208-216 - Ryota Kobayashi, Yasuhiro Tsubo, Petr Lánský, Shigeru Shinomoto:
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron. 217-225 - David Duvenaud, Hannes Nickisch, Carl Edward Rasmussen:
Additive Gaussian Processes. 226-234 - Hai-Son Le, Ziv Bar-Joseph:
Inferring Interaction Networks using the IBP applied to microRNA Target Prediction. 235-243 - Hema Swetha Koppula, Abhishek Anand, Thorsten Joachims, Ashutosh Saxena:
Semantic Labeling of 3D Point Clouds for Indoor Scenes. 244-252 - Shilin Ding, Grace Wahba, Xiaojin (Jerry) Zhu:
Learning Higher-Order Graph Structure with Features by Structure Penalty. 253-261 - Tingting Zhao, Hirotaka Hachiya, Gang Niu, Masashi Sugiyama:
Analysis and Improvement of Policy Gradient Estimation. 262-270 - Ioannis Gkioulekas, Todd E. Zickler:
Dimensionality Reduction Using the Sparse Linear Model. 271-279 - Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont:
Robust Multi-Class Gaussian Process Classification. 280-288 - Christoph H. Lampert:
Maximum Margin Multi-Label Structured Prediction. 289-297 - Ke Chen, Ahmad Salman:
Extracting Speaker-Specific Information with a Regularized Siamese Deep Network. 298-306 - Ricardo Bezerra de Andrade e Silva:
Thinning Measurement Models and Questionnaire Design. 307-315 - Charles Kemp:
Inductive reasoning about chimeric creatures. 316-324 - Philipp Hennig:
Optimal Reinforcement Learning for Gaussian Systems. 325-333 - Weiran Wang, Miguel Á. Carreira-Perpiñán, Zhengdong Lu:
A Denoising View of Matrix Completion. 334-342 - Nicolò Cesa-Bianchi, Ohad Shamir:
Efficient Online Learning via Randomized Rounding. 343-351 - Lei Yuan, Jun Liu, Jieping Ye:
Efficient Methods for Overlapping Group Lasso. 352-360 - Jing Lei:
Differentially Private M-Estimators. 361-369 - Kamil Wnuk, Stefano Soatto:
Multiple Instance Filtering. 370-378 - Morteza Alamgir, Ulrike von Luxburg:
Phase transition in the family of p-resistances. 379-387 - Yoonho Hwang, Hee-Kap Ahn:
Convergent Bounds on the Euclidean Distance. 388-396 - Yangqing Jia, Trevor Darrell:
Heavy-tailed Distances for Gradient Based Image Descriptors. 397-405 - Nicolas Boumal, Pierre-Antoine Absil:
RTRMC: A Riemannian trust-region method for low-rank matrix completion. 406-414 - Guido Montúfar, Johannes Rauh, Nihat Ay:
Expressive Power and Approximation Errors of Restricted Boltzmann Machines. 415-423 - Jasmina Bogojeska:
History distribution matching method for predicting effectiveness of HIV combination therapies. 424-432 - Binbin Lin, Chiyuan Zhang, Xiaofei He:
Semi-supervised Regression via Parallel Field Regularization. 433-441 - Ross B. Girshick, Pedro F. Felzenszwalb, David A. McAllester:
Object Detection with Grammar Models. 442-450 - Francis R. Bach, Eric Moulines:
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. 451-459 - Stefanie Jegelka, Hui Lin, Jeff A. Bilmes:
On fast approximate submodular minimization. 460-468 - Matthias S. Keil:
Emergence of Multiplication in a Biophysical Model of a Wide-Field Visual Neuron for Computing Object Approaches: Dynamics, Peaks, & Fits. 469-477 - Kumar Sricharan, Alfred O. Hero III:
Efficient anomaly detection using bipartite k-NN graphs. 478-486 - Jun Liu, Liang Sun, Jieping Ye:
Projection onto A Nonnegative Max-Heap. 487-495 - David Newman, Edwin V. Bonilla, Wray L. Buntine:
Improving Topic Coherence with Regularized Topic Models. 496-504 - Qian Sun, Rita Chattopadhyay, Sethuraman Panchanathan, Jieping Ye:
A Two-Stage Weighting Framework for Multi-Source Domain Adaptation. 505-513 - Joseph L. Austerweil, Abram L. Friesen, Thomas L. Griffiths:
An ideal observer model for identifying the reference frame of objects. 514-522 - Artin Armagan, David B. Dunson, Merlise Clyde:
Generalized Beta Mixtures of Gaussians. 523-531 - Youwei Zhang, Laurent El Ghaoui:
Large-Scale Sparse Principal Component Analysis with Application to Text Data. 532-539 - Trung-Thanh Pham, Tat-Jun Chin, Jin Yu, David Suter:
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC. 540-548 - Congcong Li, Ashutosh Saxena, Tsuhan Chen:
$\theta$-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding. 549-557 - Ryan Gomes, Peter Welinder, Andreas Krause, Pietro Perona:
Crowdclustering. 558-566 - Jia Deng, Sanjeev Satheesh, Alexander C. Berg, Li Fei-Fei:
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition. 567-575 - Ichiro Takeuchi, Masashi Sugiyama:
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification. 576-584 - Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella:
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. 585-593 - Makoto Yamada, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, Masashi Sugiyama:
Relative Density-Ratio Estimation for Robust Distribution Comparison. 594-602 - Denis Deratani Mauá, Cassio Polpo de Campos:
Solving Decision Problems with Limited Information. 603-611 - Zhouchen Lin, Risheng Liu, Zhixun Su:
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation. 612-620 - Sung Ju Hwang, Kristen Grauman, Fei Sha:
Learning a Tree of Metrics with Disjoint Visual Features. 621-629 - Oliver Stegle, Christoph Lippert, Joris M. Mooij, Neil D. Lawrence, Karsten M. Borgwardt:
Efficient inference in matrix-variate Gaussian models with \iid observation noise. 630-638 - Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf:
On Causal Discovery with Cyclic Additive Noise Models. 639-647 - Viren Jain, Srinivas C. Turaga, Kevin L. Briggman, Moritz Helmstaedter, Winfried Denk, H. Sebastian Seung:
Learning to Agglomerate Superpixel Hierarchies. 648-656 - Simon Wiesler, Hermann Ney:
A Convergence Analysis of Log-Linear Training. 657-665 - Olivier Delalleau, Yoshua Bengio:
Shallow vs. Deep Sum-Product Networks. 666-674 - Sebastian Kurtek, Anuj Srivastava, Wei Wu:
Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment. 675-683 - Shie Mannor, Ohad Shamir:
From Bandits to Experts: On the Value of Side-Observations. 684-692 - Benjamin Recht, Christopher Ré, Stephen J. Wright, Feng Niu:
Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent. 693-701 - Jiayu Zhou, Jianhui Chen, Jieping Ye:
Clustered Multi-Task Learning Via Alternating Structure Optimization. 702-710 - Joel Z. Leibo, Jim Mutch, Tomaso A. Poggio:
Why The Brain Separates Face Recognition From Object Recognition. 711-719 - André da Motta Salles Barreto, Doina Precup, Joelle Pineau:
Reinforcement Learning using Kernel-Based Stochastic Factorization. 720-728 - Samory Kpotufe:
k-NN Regression Adapts to Local Intrinsic Dimension. 729-737 - Xaq Pitkow, Yashar Ahmadian, Kenneth D. Miller:
Learning unbelievable probabilities. 738-746 - Matthew A. Kayala, Pierre Baldi:
A Machine Learning Approach to Predict Chemical Reactions. 747-755 - Biljana Petreska, Byron M. Yu, John P. Cunningham, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani:
Dynamical segmentation of single trials from population neural data. 756-764 - Peter V. Gehler, Carsten Rother, Martin Kiefel, Lumin Zhang, Bernhard Schölkopf:
Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance. 765-773 - Emin Orhan, Robert A. Jacobs:
Probabilistic Modeling of Dependencies Among Visual Short-Term Memory Representations. 774-782 - Rémi Munos:
Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness. 783-791 - Flavio Chierichetti, Jon M. Kleinberg, David Liben-Nowell:
Reconstructing Patterns of Information Diffusion from Incomplete Observations. 792-800 - Richard Socher, Eric H. Huang, Jeffrey Pennington, Andrew Y. Ng, Christopher D. Manning:
Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection. 801-809 - Nir Ailon:
Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity. 810-818 - Yee Whye Teh, Charles Blundell, Lloyd T. Elliott:
Modelling Genetic Variations using Fragmentation-Coagulation Processes. 819-827 - Michael Kapralov, Rina Panigrahy:
Prediction strategies without loss. 828-836 - Xiaoyin Ge, Issam Safa, Mikhail Belkin, Yusu Wang:
Data Skeletonization via Reeb Graphs. 837-845 - Kamiar Rahnama Rad, Liam Paninski:
Information Rates and Optimal Decoding in Large Neural Populations. 846-854 - Dmitry Pidan, Ran El-Yaniv:
Selective Prediction of Financial Trends with Hidden Markov Models. 855-863 - Xinggang Wang, Xiang Bai, Xingwei Yang, Wenyu Liu, Longin Jan Latecki:
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning. 864-872 - Alekh Agarwal, John C. Duchi:
Distributed Delayed Stochastic Optimization. 873-881 - Ambuj Tewari, Pradeep Ravikumar, Inderjit S. Dhillon:
Greedy Algorithms for Structurally Constrained High Dimensional Problems. 882-890 - Elad Hazan, Satyen Kale:
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction. 891-899 - Zhen James Xiang, Hao Xu, Peter J. Ramadge:
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries. 900-908 - Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh:
Minimax Localization of Structural Information in Large Noisy Matrices. 909-917 - Vijay Mahadevan, Chi Wah Wong, José Costa Pereira, Tom Liu, Nuno Vasconcelos, Lawrence K. Saul:
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data. 918-926 - Sham M. Kakade, Adam Kalai, Varun Kanade, Ohad Shamir:
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression. 927-935 - Bo Chen, David E. Carlson, Lawrence Carin:
On the Analysis of Multi-Channel Neural Spike Data. 936-944 - Wouter M. Koolen, Wojciech Kotlowski, Manfred K. Warmuth:
Learning Eigenvectors for Free. 945-953 - Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh:
Noise Thresholds for Spectral Clustering. 954-962 - Lu Ren, Yingjian Wang, David B. Dunson, Lawrence Carin:
The Kernel Beta Process. 963-971 - Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima:
Statistical Performance of Convex Tensor Decomposition. 972-980 - Richard E. Turner, Maneesh Sahani:
Probabilistic amplitude and frequency demodulation. 981-989 - Dominique C. Perrault-Joncas, Marina Meila:
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators. 990-998 - Yan Karklin, Eero P. Simoncelli:
Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons. 999-1007 - David A. Sontag, Daniel M. Roy:
Complexity of Inference in Latent Dirichlet Allocation. 1008-1016 - Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng:
ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning. 1017-1025 - Maxim Raginsky, Alexander Rakhlin:
Lower Bounds for Passive and Active Learning. 1026-1034 - Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin:
Stochastic convex optimization with bandit feedback. 1035-1043 - Shulin Yang, Ali Rahimi:
Structure Learning for Optimization. 1044-1052 - Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa, John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern:
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. 1053-1061 - Tianshi Gao, Daphne Koller:
Active Classification based on Value of Classifier. 1062-1070 - Liang Xiong, Barnabás Póczos, Jeff G. Schneider:
Group Anomaly Detection using Flexible Genre Models. 1071-1079 - Dan Garber, Elad Hazan:
Approximating Semidefinite Programs in Sublinear Time. 1080-1088 - Andrew E. Waters, Aswin C. Sankaranarayanan, Richard G. Baraniuk:
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements. 1089-1097 - Javad Azimi, Alan Fern, Xiaoli Z. Fern:
Budgeted Optimization with Concurrent Stochastic-Duration Experiments. 1098-1106 - Andrew Guillory, Jeff A. Bilmes:
Online Submodular Set Cover, Ranking, and Repeated Active Learning. 1107-1115 - Arthur Szlam, Karol Gregor, Yann LeCun:
Structured sparse coding via lateral inhibition. 1116-1124 - Jiquan Ngiam, Pang Wei Koh, Zhenghao Chen, Sonia A. Bhaskar, Andrew Y. Ng:
Sparse Filtering. 1125-1133 - Lester W. Mackey, Ameet Talwalkar, Michael I. Jordan:
Divide-and-Conquer Matrix Factorization. 1134-1142 - Vicente Ordonez, Girish Kulkarni, Tamara L. Berg:
Im2Text: Describing Images Using 1 Million Captioned Photographs. 1143-1151