Abstract is missing.
- A dynamic excitatory-inhibitory network in a VLSI chip for spiking information reregistrationJuan Huo. [doi]
- Generalization Bounds for Domain AdaptationChao Zhang, Lei Zhang, Jieping Ye. [doi]
- Locally Uniform Comparison Image DescriptorAndrew Ziegler, Eric M. Christiansen, David J. Kriegman, Serge J. Belongie. 1-9 [doi]
- Learning from Distributions via Support Measure MachinesKrikamol Muandet, Kenji Fukumizu, Francesco Dinuzzo, Bernhard Schölkopf. 10-18 [doi]
- Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse RecoveryEhsan Elhamifar, Guillermo Sapiro, René Vidal. 19-27 [doi]
- Feature Clustering for Accelerating Parallel Coordinate DescentChad Scherrer, Ambuj Tewari, Mahantesh Halappanavar, David Haglin. 28-36 [doi]
- Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGAC. Minos Niu, Sirish Nandyala, Won Joon Sohn, Terence D. Sanger. 37-45 [doi]
- Active Learning of Model Evidence Using Bayesian QuadratureMichael A. Osborne, David K. Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani. 46-54 [doi]
- Coupling Nonparametric Mixtures via Latent Dirichlet ProcessesDahua Lin, John W. Fisher. 55-63 [doi]
- Nonparametric Max-Margin Matrix Factorization for Collaborative PredictionMinjie Xu, Jun Zhu, Bo Zhang. 64-72 [doi]
- Bayesian Hierarchical Reinforcement LearningFeng Cao, Soumya Ray. 73-81 [doi]
- Dynamic Pruning of Factor Graphs for Maximum Marginal PredictionChristoph H. Lampert. 82-90 [doi]
- Local Supervised Learning through Space PartitioningJoseph Wang, Venkatesh Saligrama. 91-99 [doi]
- A Generative Model for Parts-based Object SegmentationS. M. Ali Eslami, Chris Williams. 100-107 [doi]
- Super-Bit Locality-Sensitive HashingJianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian. 108-116 [doi]
- The Bethe Partition Function of Log-supermodular Graphical ModelsNicholas Ruozzi. 117-125 [doi]
- Random Utility Theory for Social ChoiceHossein Azari Soufiani, David C. Parkes, Lirong Xia. 126-134 [doi]
- Putting Bayes to sleepWouter M. Koolen, Dmitry Adamskiy, Manfred K. Warmuth. 135-143 [doi]
- A new metric on the manifold of kernel matrices with application to matrix geometric meansSuvrit Sra. 144-152 [doi]
- Mandatory Leaf Node Prediction in Hierarchical Multilabel ClassificationWei Bi, James T. Kwok. 153-161 [doi]
- Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph EstimationTuo Zhao, Kathryn Roeder, Han Liu. 162-170 [doi]
- Semiparametric Principal Component AnalysisFang Han, Han Liu. 171-179 [doi]
- Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firingShinsuke Koyama. 180-188 [doi]
- The representer theorem for Hilbert spaces: a necessary and sufficient conditionFrancesco Dinuzzo, Bernhard Schölkopf. 189-196 [doi]
- "On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking"Clément Calauzènes, Nicolas Usunier, Patrick Gallinari. 197-205 [doi]
- Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning ProgressManuel Lopes, Tobias Lang, Marc Toussaint, Pierre-Yves Oudeyer. 206-214 [doi]
- Supervised Learning with Similarity FunctionsPurushottam Kar, Prateek Jain 0002. 215-223 [doi]
- Cocktail Party Processing via Structured PredictionYuxuan Wang, DeLiang Wang. 224-232 [doi]
- Robustness and risk-sensitivity in Markov decision processesTakayuki Osogami. 233-241 [doi]
- Dynamical And-Or Graph Learning for Object Shape Modeling and DetectionXiaolong Wang, Liang Lin. 242-250 [doi]
- Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functionsAlexandra Carpentier, Rémi Munos. 251-259 [doi]
- Distributed Non-Stochastic ExpertsVarun Kanade, Zhenming Liu, Bozidar Radunovic. 260-268 [doi]
- An Integer Optimization Approach to Associative ClassificationAllison Chang, Dimitris Bertsimas, Cynthia Rudin. 269-277 [doi]
- Learning Image Descriptors with the Boosting-TrickTomasz Trzcinski, C. Mario Christoudias, Vincent Lepetit, Pascal Fua. 278-286 [doi]
- Fast Resampling Weighted v-StatisticsChunxiao Zhou, Jiseong Park, Yun Fu. 287-295 [doi]
- Multi-task Vector Field LearningBinbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, Xiaofei He. 296-304 [doi]
- Memorability of Image RegionsAditya Khosla, Jianxiong Xiao, Antonio Torralba, Aude Oliva. 305-313 [doi]
- Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward FunctionsJaedeug Choi, Kee-Eung Kim. 314-322 [doi]
- Automatic Feature Induction for Stagewise Collaborative FilteringJoonseok Lee, Mingxuan Sun, Seungyeon Kim, Guy Lebanon. 323-331 [doi]
- Selective Labeling via Error Bound MinimizationQuanquan Gu, Tong Zhang 0001, Chris H. Q. Ding, Jiawei Han. 332-340 [doi]
- Volume Regularization for Binary ClassificationKoby Crammer, Tal Wagner. 341-349 [doi]
- Image Denoising and Inpainting with Deep Neural NetworksJunyuan Xie, Linli Xu, Enhong Chen. 350-358 [doi]
- Max-Margin Structured Output Regression for Spatio-Temporal Action LocalizationDu Tran, Junsong Yuan. 359-367 [doi]
- Transelliptical Component AnalysisFang Han, Han Liu. 368-376 [doi]
- Action-Model Based Multi-agent Plan RecognitionHankz Hankui Zhuo, Qiang Yang, Subbarao Kambhampati. 377-385 [doi]
- Visual Recognition using Embedded Feature Selection for Curvature Self-SimilarityAngela Eigenstetter, Björn Ommer. 386-394 [doi]
- Non-parametric Approximate Dynamic Programming via the Kernel MethodNikhil Bhat, Ciamac C. Moallemi, Vivek F. Farias. 395-403 [doi]
- Optimal Regularized Dual Averaging Methods for Stochastic OptimizationXi Chen, Qihang Lin, Javier Peña. 404-412 [doi]
- The variational hierarchical EM algorithm for clustering hidden Markov modelsEmanuele Coviello, Antoni B. Chan, Gert R. G. Lanckriet. 413-421 [doi]
- Truncation-free Online Variational Inference for Bayesian Nonparametric ModelsChong Wang, David M. Blei. 422-430 [doi]
- 3D Social Saliency from Head-mounted CamerasHyun Soo Park, Eakta Jain, Yaser Sheikh. 431-439 [doi]
- Context-Sensitive Decision Forests for Object DetectionPeter Kontschieder, Samuel Rota Bulò, Antonio Criminisi, Pushmeet Kohli, Marcello Pelillo, Horst Bischof. 440-448 [doi]
- Learning Invariant Representations of Molecules for Atomization Energy PredictionGrégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, Anatole von Lilienfeld, Klaus-Robert Müller. 449-457 [doi]
- Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled buttonJoan Fruitet, Alexandra Carpentier, Rémi Munos, Maureen Clerc. 458-466 [doi]
- Multiplicative Forests for Continuous-Time ProcessesJeremy C. Weiss, Sriraam Natarajan, David Page. 467-475 [doi]
- Patient Risk Stratification for Hospital-Associated C. diff as a Time-Series Classification TaskJenna Wiens, John V. Guttag, Eric Horvitz. 476-484 [doi]
- "Nystr{\""o}m Method vs Random Fourier Features: A Theoretical and Empirical Comparison"Tianbao Yang, Yu-Feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou. 485-493 [doi]
- Multiclass Learning Approaches: A Theoretical Comparison with ImplicationsAmit Daniely, Sivan Sabato, Shai Shalev-Shwartz. 494-502 [doi]
- Stochastic Gradient Descent with Only One ProjectionMehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi. 503-511 [doi]
- "Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter"Dmitri B. Chklovskii, Daniel Soudry. 512-520 [doi]
- Deep Spatio-Temporal Architectures and Learning for Protein Structure PredictionPietro di Lena, Pierre Baldi, Ken Nagata. 521-529 [doi]
- Assessing Blinding in Clinical TrialsOgnjen Arandjelovic. 530-538 [doi]
- Scalable nonconvex inexact proximal splittingSuvrit Sra. 539-547 [doi]
- Learning to Discover Social Circles in Ego NetworksJulian J. McAuley, Jure Leskovec. 548-556 [doi]
- A Conditional Multinomial Mixture Model for Superset Label LearningLi-Ping Liu, Thomas G. Dietterich. 557-565 [doi]
- Majorization for CRFs and Latent LikelihoodsTony Jebara, Anna Choromanska. 566-574 [doi]
- Ensemble weighted kernel estimators for multivariate entropy estimationKumar Sricharan, Alfred O. Hero III. 575-583 [doi]
- Efficient high dimensional maximum entropy modeling via symmetric partition functionsPaul Vernaza, Drew Bagnell. 584-592 [doi]
- Discriminatively Trained Sparse Code Gradients for Contour DetectionXiaofeng Ren, Liefeng Bo. 593-601 [doi]
- Analyzing 3D Objects in Cluttered ImagesMohsen Hejrati, Deva Ramanan. 602-610 [doi]
- Nonconvex Penalization Using Laplace Exponents and Concave ConjugatesZhihua Zhang, Bojun Tu. 611-619 [doi]
- 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid ModelSanja Fidler, Sven J. Dickinson, Raquel Urtasun. 620-628 [doi]
- Structured Learning of Gaussian Graphical ModelsKarthik Mohan, Michael Jae-Yoon Chung, Seungyeop Han, Daniela M. Witten, Su-In Lee, Maryam Fazel. 629-637 [doi]
- A Polylog Pivot Steps Simplex Algorithm for ClassificationElad Hazan, Zohar Shay Karnin. 638-646 [doi]
- Shifting Weights: Adapting Object Detectors from Image to VideoKevin D. Tang, Vignesh Ramanathan, Fei-Fei Li, Daphne Koller. 647-655 [doi]
- A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter BoundShusen Wang, Zhihua Zhang. 656-664 [doi]
- Convolutional-Recursive Deep Learning for 3D Object ClassificationRichard Socher, Brody Huval, Bharath Putta Bath, Christopher D. Manning, Andrew Y. Ng. 665-673 [doi]
- Semi-Supervised Domain Adaptation with Non-Parametric CopulasDavid López-Paz, José Miguel Hernández-Lobato, Bernhard Schölkopf. 674-682 [doi]
- Identification of Recurrent Patterns in the Activation of Brain NetworksFirdaus Janoos, Weichang Li, Niranjan A. Subrahmanya, István Ákos Mórocz, William M. Wells III. 683-691 [doi]
- Density-Difference EstimationMasashi Sugiyama, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu, Ichiro Takeuchi. 692-700 [doi]
- Variational Inference for CrowdsourcingQiang Liu, Jian Peng, Alexander T. Ihler. 701-709 [doi]
- MCMC for continuous-time discrete-state systemsVinayak Rao, Yee Whye Teh. 710-718 [doi]
- A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised SpellingPieter-Jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen. 719-727 [doi]
- Learning about Canonical Views from Internet Image CollectionsElad Mezuman, Yair Weiss. 728-736 [doi]
- Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional DataAssaf Glazer, Michael Lindenbaum, Shaul Markovitch. 737-745 [doi]
- Multiresolution Gaussian ProcessesEmily B. Fox, David B. Dunson. 746-754 [doi]
- Localizing 3D cuboids in single-view imagesJianxiong Xiao, Bryan C. Russell, Antonio Torralba. 755-763 [doi]
- Newton-Like Methods for Sparse Inverse Covariance EstimationPeder A. Olsen, Figen Öztoprak, Jorge Nocedal, Steven J. Rennie. 764-772 [doi]
- Learning to Align from ScratchGary B. Huang, Marwan A. Mattar, Honglak Lee, Erik G. Learned-Miller. 773-781 [doi]
- Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraintsStefan Habenschuss, Johannes Bill, Bernhard Nessler. 782-790 [doi]
- Clustering Aggregation as Maximum-Weight Independent SetNan Li, Longin Jan Latecki. 791-799 [doi]
- Topology Constraints in Graphical ModelsMarcelo Fiori, Pablo Musé, Guillermo Sapiro. 800-808 [doi]
- Transelliptical Graphical ModelsHan Liu, Fang Han, Cun-Hui Zhang. 809-817 [doi]
- Kernel Latent SVM for Visual RecognitionWeilong Yang, Yang Wang 0003, Arash Vahdat, Greg Mori. 818-826 [doi]
- Learning Partially Observable Models Using Temporally Abstract Decision TreesErik Talvitie. 827-835 [doi]
- Proximal Newton-type methods for convex optimizationJason D. Lee, Yuekai Sun, Michael A. Saunders. 836-844 [doi]
- Regularized Off-Policy TD-LearningBo Liu, Sridhar Mahadevan, Ji Liu 0002. 845-853 [doi]
- Multi-criteria Anomaly Detection using Pareto Depth AnalysisKo-Jen Hsiao, Kevin S. Xu 0001, Jeff Calder, Alfred O. Hero III. 854-862 [doi]
- Synchronization can Control Regularization in Neural Systems via Correlated Noise ProcessesJake V. Bouvrie, Jean-Jacques E. Slotine. 863-871 [doi]
- Calibrated Elastic Regularization in Matrix CompletionTingni Sun, Cun-Hui Zhang. 872-880 [doi]
- Predicting Action Content On-Line and in Real Time before Action Onset - an Intracranial Human StudyUri Maoz, Shengxuan Ye, Ian B. Ross, Adam N. Mamelak, Christof Koch. 881-889 [doi]
- Searching for objects driven by contextBogdan Alexe, Nicolas Heess, Yee Whye Teh, Vittorio Ferrari. 890-898 [doi]
- Timely Object RecognitionSergey Karayev, Tobias Baumgartner 0002, Mario Fritz, Trevor Darrell. 899-907 [doi]
- Nonparanormal Belief Propagation (NPNBP)Gal Elidan, Cobi Cario. 908-916 [doi]
- Deep Representations and Codes for Image Auto-AnnotationRyan Kiros, Csaba Szepesvári. 917-925 [doi]
- A Spectral Algorithm for Latent Dirichlet AllocationAnima Anandkumar, Dean P. Foster, Daniel Hsu, Sham Kakade, Yi-Kai Liu. 926-934 [doi]
- Learning Halfspaces with the Zero-One Loss: Time-Accuracy TradeoffsAharon Birnbaum, Shai Shalev-Shwartz. 935-943 [doi]
- Matrix reconstruction with the local max normRina Foygel, Nathan Srebro, Ruslan Salakhutdinov. 944-952 [doi]
- Analog readout for optical reservoir computersAnteo Smerieri, François Duport, Yvan Paquot, Benjamin Schrauwen, Marc Haelterman, Serge Massar. 953-961 [doi]
- Accuracy at the TopStephen P. Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic. 962-970 [doi]
- Minimizing Sparse High-Order Energies by Submodular Vertex-CoverAndrew Delong, Olga Veksler, Anton Osokin, Yuri Boykov. 971-979 [doi]
- Perfect Dimensionality Recovery by Variational Bayesian PCAShinichi Nakajima, Ryota Tomioka, Masashi Sugiyama, S. Derin Babacan. 980-988 [doi]
- Mirror Descent Meets Fixed Share (and feels no regret)Nicolò Cesa-Bianchi, Pierre Gaillard, Gábor Lugosi, Gilles Stoltz. 989-997 [doi]
- Near-optimal Differentially Private Principal ComponentsKamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha. 998-1006 [doi]
- Random function priors for exchangeable arrays with applications to graphs and relational dataJames Robert Lloyd, Peter Orbanz, Zoubin Ghahramani, Daniel M. Roy. 1007-1015 [doi]
- Inverse Reinforcement Learning through Structured ClassificationEdouard Klein, Matthieu Geist, Bilal Piot, Olivier Pietquin. 1016-1024 [doi]
- Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamicsAshwini Shukla, Aude Billard. 1025-1033 [doi]
- Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based SearchArthur Guez, David Silver, Peter Dayan. 1034-1042 [doi]
- Dimensionality Dependent PAC-Bayes Margin BoundChi Jin, Liwei Wang. 1043-1051 [doi]
- Latent Graphical Model Selection: Efficient Methods for Locally Tree-like GraphsAnimashree Anandkumar, Ragupathyraj Valluvan. 1052-1060 [doi]
- Learning Mixtures of Tree Graphical ModelsAnimashree Anandkumar, Daniel Hsu, Furong Huang, Sham Kakade. 1061-1069 [doi]
- Hamming Distance Metric LearningMohammad Norouzi 0002, David J. Fleet, Ruslan Salakhutdinov. 1070-1078 [doi]
- Spiking and saturating dendrites differentially expand single neuron computation capacityRomain Cazé, Mark D. Humphries, Boris S. Gutkin. 1079-1087 [doi]
- Clustering by Nonnegative Matrix Factorization Using Graph Random WalkZhirong Yang, Tele Hao, Onur Dikmen, Xi Chen, Erkki Oja. 1088-1096 [doi]
- Delay Compensation with Dynamical SynapsesC. C. Alan Fung, K. Y. Michael Wong, Si Wu. 1097-1105 [doi]
- ImageNet Classification with Deep Convolutional Neural NetworksAlex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton. 1106-1114 [doi]
- Recognizing Activities by Attribute DynamicsWeixin Li, Nuno Vasconcelos. 1115-1123 [doi]
- Compressive Sensing MRI with Wavelet Tree SparsityChen Chen, JunZhou Huang. 1124-1132 [doi]
- Training sparse natural image models with a fast Gibbs sampler of an extended state spaceLucas Theis, Jascha Sohl-Dickstein, Matthias Bethge. 1133-1141 [doi]
- A Bayesian Approach for Policy Learning from Trajectory Preference QueriesAaron Wilson, Alan Fern, Prasad Tadepalli. 1142-1150 [doi]
- GenDeR: A Generic Diversified Ranking AlgorithmJingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw K. Szymanski. 1151-1159 [doi]
- On Multilabel Classification and Ranking with Partial FeedbackClaudio Gentile, Francesco Orabona. 1160-1168 [doi]
- "The Lovasz $\theta$ function, SVMs and finding large dense subgraphs"Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt P. Dubhashi. 1169-1177 [doi]
- Multi-Task AveragingSergey Feldman, Maya R. Gupta, Bela A. Frigyik. 1178-1186 [doi]
- Unsupervised Structure Discovery for Semantic Analysis of AudioSourish Chaudhuri, Bhiksha Raj. 1187-1195 [doi]
- A Marginalized Particle Gaussian Process RegressionYali Wang, Brahim Chaib-draa. 1196-1204 [doi]
- Angular Quantization-based Binary Codes for Fast Similarity SearchYunchao Gong, Sanjiv Kumar, Vishal Verma, Svetlana Lazebnik. 1205-1213 [doi]
- Optimal kernel choice for large-scale two-sample testsArthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu. 1214-1222 [doi]
- Factoring nonnegative matrices with linear programsBen Recht, Christopher Re, Joel A. Tropp, Victor Bittorf. 1223-1231 [doi]
- Large Scale Distributed Deep NetworksJeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng. 1232-1240 [doi]
- Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability SpaceYanyan Lan, Jiafeng Guo, Xueqi Cheng, Tie-Yan Liu. 1241-1249 [doi]
- Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discriminationWon Hwa Kim, Deepti Pachauri, Charles Hatt, Moo K. Chung, Sterling C. Johnson, Vikas Singh. 1250-1258 [doi]
- A Convex Formulation for Learning Scale-Free Networks via Submodular RelaxationAaron Defazio, Tibério S. Caetano. 1259-1267 [doi]
- Fused sparsity and robust estimation for linear models with unknown varianceArnak S. Dalalyan, Yin Chen. 1268-1276 [doi]
- How Prior Probability Influences Decision Making: A Unifying Probabilistic ModelYanping Huang, Abram L. Friesen, Timothy D. Hanks, Michael N. Shadlen, Rajesh P. N. Rao. 1277-1285 [doi]
- High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression PredictionHua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen. 1286-1294 [doi]
- Symmetric Correspondence Topic Models for Multilingual Text AnalysisKosuke Fukumasu, Koji Eguchi, Eric P. Xing. 1295-1303 [doi]
- Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential DataMichael C. Hughes, Emily B. Fox, Erik B. Sudderth. 1304-1312 [doi]
- Efficient coding provides a direct link between prior and likelihood in perceptual Bayesian inferenceXue-Xin Wei, Alan A. Stocker. 1313-1321 [doi]
- Efficient Sampling for Bipartite Matching ProblemsMaksims Volkovs, Richard S. Zemel. 1322-1330 [doi]
- Learning visual motion in recurrent neural networksMarius Pachitariu, Maneesh Sahani. 1331-1339 [doi]
- Learned Prioritization for Trading Off Accuracy and SpeedJiarong Jiang, Adam R. Teichert, Hal Daumé III, Jason Eisner. 1340-1348 [doi]
- Value Pursuit IterationAmir Massoud Farahmand, Doina Precup. 1349-1357 [doi]
- "Compressive neural representation of sparse, high-dimensional probabilities"Xaq Pitkow. 1358-1366 [doi]
- Graphical Models via Generalized Linear ModelsEunho Yang, Pradeep D. Ravikumar, Genevera I. Allen, Zhandong Liu. 1367-1375 [doi]
- CPRL -- An Extension of Compressive Sensing to the Phase Retrieval ProblemHenrik Ohlsson, Allen Y. Yang, Roy Dong, S. Shankar Sastry. 1376-1384 [doi]
- Co-Regularized Hashing for Multimodal DataYi Zhen, Dit-Yan Yeung. 1385-1393 [doi]
- Convergence and Energy Landscape for Cheeger Cut ClusteringXavier Bresson, Thomas Laurent 0001, David Uminsky, James H. von Brecht. 1394-1402 [doi]
- Symbolic Dynamic Programming for Continuous State and Observation POMDPsZahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting. 1403-1411 [doi]
- Bayesian Probabilistic Co-Subspace AdditionLei Shi. 1412-1420 [doi]
- Scaled Gradients on Grassmann Manifolds for Matrix CompletionThanh T. Ngo, Yousef Saad. 1421-1429 [doi]
- Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to NeuroimagingChris Hinrichs, Vikas Singh, Jiming Peng, Sterling C. Johnson. 1430-1438 [doi]
- Privacy Aware LearningJohn C. Duchi, Michael I. Jordan, Martin J. Wainwright. 1439-1447 [doi]
- Finite Sample Convergence Rates of Zero-Order Stochastic Optimization MethodsJohn C. Duchi, Michael I. Jordan, Martin J. Wainwright, Andre Wibisono. 1448-1456 [doi]
- Hierarchical Optimistic Region Selection driven by CuriosityOdalric-Ambrym Maillard. 1457-1465 [doi]
- Sparse Prediction with the $k$-Support NormAndreas Argyriou, Rina Foygel, Nathan Srebro. 1466-1474 [doi]
- Active Learning of Multi-Index Function ModelsHemant Tyagi, Volkan Cevher. 1475-1483 [doi]
- Learning Multiple Tasks using Shared HypothesesKoby Crammer, Yishay Mansour. 1484-1492 [doi]
- On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic FactorizationAndré da Motta Salles Barreto, Doina Precup, Joelle Pineau. 1493-1501 [doi]
- Forward-Backward Activation Algorithm for Hierarchical Hidden Markov ModelsKei Wakabayashi, Takao Miura. 1502-1510 [doi]
- Communication-Efficient Algorithms for Statistical OptimizationYuchen Zhang, John C. Duchi, Martin J. Wainwright. 1511-1519 [doi]
- Identifiability and Unmixing of Latent Parse TreesDaniel Hsu, Sham M. Kakade, Percy Liang. 1520-1528 [doi]
- Bayesian nonparametric models for ranked dataFrancois Caron, Yee Whye Teh. 1529-1537 [doi]
- Feature-aware Label Space Dimension Reduction for Multi-label ClassificationYao-Nan Chen, Hsuan-Tien Lin. 1538-1546 [doi]
- Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensionsAlekh Agarwal, Sahand Negahban, Martin J. Wainwright. 1547-1555 [doi]
- Graphical Gaussian Vector for Image CategorizationTatsuya Harada, Yasuo Kuniyoshi. 1556-1564 [doi]
- Joint Modeling of a Matrix with Associated Text via Latent Binary FeaturesXianXing Zhang, Lawrence Carin. 1565-1573 [doi]
- Proper losses for learning from partial labelsJesús Cid-Sueiro. 1574-1582 [doi]
- Iterative Thresholding Algorithm for Sparse Inverse Covariance EstimationBenjamin T. Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki. 1583-1591 [doi]
- Selecting Diverse Features via Spectral RegularizationAbhimanyu Das, Anirban Dasgupta, Ravi Kumar. 1592-1600 [doi]
- Monte Carlo Methods for Maximum Margin Supervised Topic ModelsQixia Jiang, Jun Zhu, Maosong Sun, Eric P. Xing. 1601-1609 [doi]
- Parametric Local Metric Learning for Nearest Neighbor ClassificationJun Wang 0017, Alexandros Kalousis, Adam Woznica. 1610-1618 [doi]
- A Linear Time Active Learning Algorithm for Link ClassificationNicolò Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella. 1619-1627 [doi]
- Bayesian Warped Gaussian ProcessesMiguel Lázaro-Gredilla. 1628-1636 [doi]
- Nonparametric Reduced Rank RegressionRina Foygel, Michael Horrell, Mathias Drton, John D. Lafferty. 1637-1645 [doi]
- Multiresolution analysis on the symmetric groupRisi Kondor, Walter Dempsey. 1646-1654 [doi]
- Isotropic HashingWeihao Kong, Wu-Jun Li. 1655-1663 [doi]
- On Lifting the Gibbs Sampling AlgorithmDeepak Venugopal, Vibhav Gogate. 1664-1672 [doi]
- On the connections between saliency and trackingVijay Mahadevan, Nuno Vasconcelos. 1673-1681 [doi]
- Convex Multi-view Subspace LearningMartha White, Yaoliang Yu, Xinhua Zhang, Dale Schuurmans. 1682-1690 [doi]
- Spectral learning of linear dynamics from generalised-linear observations with application to neural population dataLars Buesing, Jakob H. Macke, Maneesh Sahani. 1691-1699 [doi]
- Mixability in Statistical LearningTim van Erven, Peter D. Grünwald, Mark D. Reid, Robert C. Williamson. 1700-1708 [doi]
- Waveform Driven Plasticity in BiFeO3 Memristive Devices: Model and ImplementationChristian Mayr, Paul Stärke, Johannes Partzsch, René Schüffny, Love Cederstroem, Yao Shuai, Nan Du, Heidemarie Schmidt. 1709-1717 [doi]
- A lattice filter model of the visual pathwayKarol Gregor, Dmitri B. Chklovskii. 1718-1726 [doi]
- Semantic Kernel Forests from Multiple TaxonomiesSung Ju Hwang, Kristen Grauman, Fei Sha. 1727-1735 [doi]
- Causal discovery with scale-mixture model for spatiotemporal variance dependenciesZhitang Chen, Kun Zhang, Laiwan Chan. 1736-1744 [doi]
- "Natural Images, Gaussian Mixtures and Dead Leaves"Daniel Zoran, Yair Weiss. 1745-1753 [doi]
- Dual-Space Analysis of the Sparse Linear ModelDavid P. Wipf, Yi Wu. 1754-1762 [doi]
- Active Comparison of Prediction ModelsChristoph Sawade, Niels Landwehr, Tobias Scheffer. 1763-1771 [doi]
- Online Regret Bounds for Undiscounted Continuous Reinforcement LearningRonald Ortner, Daniil Ryabko. 1772-1780 [doi]
- Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric LearningJinfeng Yi, Rong Jin, Anil K. Jain, Shaili Jain, Tianbao Yang. 1781-1789 [doi]
- Learning curves for multi-task Gaussian process regressionPeter Sollich, Simon R. F. Ashton. 1790-1798 [doi]
- Kernel HyperalignmentAlexander Lorbert, Peter J. Ramadge. 1799-1807 [doi]
- Multiple Choice Learning: Learning to Produce Multiple Structured OutputsAbner Guzmán-Rivera, Dhruv Batra, Pushmeet Kohli. 1808-1816 [doi]
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- Adaptive Learning of Smoothing Functions: Application to Electricity Load ForecastingAmadou Ba, Mathieu Sinn, Yannig Goude, Pascal Pompey. 2519-2527 [doi]
- Tensor Decomposition for Fast Parsing with Latent-Variable PCFGsShay B. Cohen, Michael Collins. 2528-2536 [doi]
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- Non-linear Metric LearningDor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, Gert R. G. Lanckriet. 2582-2590 [doi]
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- Expectation Propagation in Gaussian Process Dynamical SystemsMarc Peter Deisenroth, Shakir Mohamed. 2618-2626 [doi]
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- Efficient Reinforcement Learning for High Dimensional Linear Quadratic SystemsMorteza Ibrahimi, Adel Javanmard, Benjamin Van Roy. 2645-2653 [doi]
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