Abstract is missing.
- An Application of Reinforcement Learning to Aerobatic Helicopter FlightPieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng. 1-8 [doi]
- Tighter PAC-Bayes BoundsAmiran Ambroladze, Emilio Parrado-Hernández, John Shawe-Taylor. 9-16 [doi]
- Online Classification for Complex Problems Using Simultaneous ProjectionsYonatan Amit, Shai Shalev-Shwartz, Yoram Singer. 17-24 [doi]
- Learning on Graph with Laplacian RegularizationRie Kubota Ando, Tong Zhang. 25-32 [doi]
- Sparse Kernel Orthonormalized PLS for feature extraction in large data setsJerónimo Arenas-García, Kaare Brandt Petersen, Lars Kai Hansen. 33-40 [doi]
- Multi-Task Feature LearningAndreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil. 41-48 [doi]
- Logarithmic Online Regret Bounds for Undiscounted Reinforcement LearningPeter Auer, Ronald Ortner. 49-56 [doi]
- Efficient Methods for Privacy Preserving Face DetectionShai Avidan, Moshe Butman. 57-64 [doi]
- Active learning for misspecified generalized linear modelsFrancis R. Bach. 65-72 [doi]
- Subordinate class recognition using relational object modelsAharon Bar-Hillel, Daphna Weinshall. 73-80 [doi]
- Unified Inference for Variational Bayesian Linear Gaussian State-Space ModelsDavid Barber, Silvia Chiappa. 81-88 [doi]
- A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical SystemsDavid Barber, Bertrand Mesot. 89-96 [doi]
- Sample Complexity of Policy Search with Known DynamicsPeter L. Bartlett, Ambuj Tewari. 97-104 [doi]
- AdaBoost is ConsistentPeter L. Bartlett, Mikhail Traskin. 105-112 [doi]
- A selective attention multi--chip system with dynamic synapses and spiking neuronsChiara Bartolozzi, Giacomo Indiveri. 113-120 [doi]
- Temporal and Cross-Subject Probabilistic Models for fMRI Prediction TasksAlexis Battle, Gal Chechik, Daphne Koller. 121-128 [doi]
- Convergence of Laplacian EigenmapsMikhail Belkin, Partha Niyogi. 129-136 [doi]
- Analysis of Representations for Domain AdaptationShai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira. 137-144 [doi]
- An Approach to Bounded RationalityEli Ben-Sasson, Adam Tauman Kalai, Ehud Kalai. 145-152 [doi]
- Greedy Layer-Wise Training of Deep NetworksYoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle. 153-160 [doi]
- Dirichlet-Enhanced Spam Filtering based on Biased SamplesSteffen Bickel, Tobias Scheffer. 161-168 [doi]
- Detecting Humans via Their PoseAlessandro Bissacco, Ming-Hsuan Yang, Stefano Soatto. 169-176 [doi]
- Similarity by CompositionOren Boiman, Michal Irani. 177-184 [doi]
- Denoising and Dimension Reduction in Feature SpaceMikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller. 185-192 [doi]
- Learning to Rank with Nonsmooth Cost FunctionsChristopher J. C. Burges, Robert Ragno, Quoc Viet Le. 193-200 [doi]
- Conditional mean fieldPeter Carbonetto, Nando de Freitas. 201-208 [doi]
- Sparse Multinomial Logistic Regression via Bayesian L1 RegularisationGavin C. Cawley, Nicola L. C. Talbot, Mark Girolami. 209-216 [doi]
- Branch and Bound for Semi-Supervised Support Vector MachinesOlivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi. 217-224 [doi]
- Automated Hierarchy Discovery for Planning in Partially Observable EnvironmentsLaurent Charlin, Pascal Poupart, Romy Shioda. 225-232 [doi]
- Max-margin classification of incomplete dataGal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller. 233-240 [doi]
- Modeling General and Specific Aspects of Documents with a Probabilistic Topic ModelChaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers. 241-248 [doi]
- implicit Online Learning with KernelsLi Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli. 249-256 [doi]
- Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neuronsElisabetta Chicca, Giacomo Indiveri, Rodney J. Douglas. 257-264 [doi]
- Bayesian Ensemble LearningHugh A. Chipman, Edward I. George, Robert E. McCulloch. 265-272 [doi]
- Implicit Surfaces with Globally Regularised and Compactly Supported Basis FunctionsChristian Walder, Bernhard Schölkopf, Olivier Chapelle. 273-280 [doi]
- Map-Reduce for Machine Learning on MulticoreCheng-Tao Chu, Sang-Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary R. Bradski, Andrew Y. Ng, Kunle Olukotun. 281-288 [doi]
- Relational Learning with Gaussian ProcessesWei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi. 289-296 [doi]
- Recursive Attribute FactoringDavid Cohn, Deepak Verma, Karl Pfleger. 297-304 [doi]
- On Transductive RegressionCorinna Cortes, Mehryar Mohri. 305-312 [doi]
- Balanced Graph MatchingTimothée Cour, Praveen Srinivasan, Jianbo Shi. 313-320 [doi]
- Learning from Multiple SourcesKoby Crammer, Michael J. Kearns, Jennifer Wortman. 321-328 [doi]
- Kernels on Structured Objects Through Nested HistogramsMarco Cuturi, Kenji Fukumizu. 329-336 [doi]
- Differential Entropic Clustering of Multivariate GaussiansJason V. Davis, Inderjit S. Dhillon. 337-344 [doi]
- Support Vector Machines on a BudgetOfer Dekel, Yoram Singer. 345-352 [doi]
- A Theory of Retinal Population CodingEizaburo Doi, Michael S. Lewicki. 353-360 [doi]
- Learning to Traverse Image ManifoldsPiotr Dollár, Serge Belongie, Vincent Rabaud. 361-368 [doi]
- Using Combinatorial Optimization within Max-Product Belief PropagationJohn Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller. 369-376 [doi]
- Optimal Single-Class Classification StrategiesRan El-Yaniv, Mordechai Nisenson. 377-384 [doi]
- A Small World Threshold for Economic Network FormationEyal Even-Dar, Michael J. Kearns. 385-392 [doi]
- PG-means: learning the number of clusters in dataYu Feng, Greg Hamerly. 393-400 [doi]
- Clustering Under Prior Knowledge with Application to Image SegmentationMário A. T. Figueiredo, Dong Seon Cheng, Vittorio Murino. 401-408 [doi]
- Multi-dynamic Bayesian NetworksKarim Filali, Jeff A. Bilmes. 409-416 [doi]
- Image Retrieval and Classification Using Local Distance FunctionsAndrea Frome, Yoram Singer, Jitendra Malik. 417-424 [doi]
- Multiple Instance Learning for Computer Aided DiagnosisGlenn Fung, Murat Dundar, Balaji Krishnapuram, R. Bharat Rao. 425-432 [doi]
- Distributed Inference in Dynamical SystemsStanislav Funiak, Carlos Guestrin, Mark A. Paskin, Rahul Sukthankar. 433-440 [doi]
- iLSTD: Eligibility Traces and Convergence AnalysisAlborz Geramifard, Michael H. Bowling, Martin Zinkevich, Richard S. Sutton. 441-448 [doi]
- A PAC-Bayes Risk Bound for General Loss FunctionsPascal Germain, Alexandre Lacasse, François Laviolette, Mario Marchand. 449-456 [doi]
- Bayesian Policy Gradient AlgorithmsMohammad Ghavamzadeh, Yaakov Engel. 457-464 [doi]
- Data Integration for Classification Problems Employing Gaussian Process PriorsMark Girolami, Mingjun Zhong. 465-472 [doi]
- Approximate inference using planar graph decompositionAmir Globerson, Tommi Jaakkola. 473-480 [doi]
- Near-Uniform Sampling of Combinatorial Spaces Using XOR ConstraintsCarla P. Gomes, Ashish Sabharwal, Bart Selman. 481-488 [doi]
- No-regret Algorithms for Online Convex ProgramsGeoffrey J. Gordon. 489-496 [doi]
- Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural ProsthesisAmit Gore, Shantanu Chakrabartty. 497-504 [doi]
- Approximate Correspondences in High DimensionsKristen Grauman, Trevor Darrell. 505-512 [doi]
- A Kernel Method for the Two-Sample-ProblemArthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola. 513-520 [doi]
- Learning Nonparametric Models for Probabilistic ImitationDavid B. Grimes, Daniel R. Rashid, Rajesh P. N. Rao. 521-528 [doi]
- Training Conditional Random Fields for Maximum Labelwise AccuracySamuel S. Gross, Olga Russakovsky, Chuong B. Do, Serafim Batzoglou. 529-536 [doi]
- Adaptive Spatial Filters with predefined Region of Interest for EEG based Brain-Computer-InterfacesMoritz Grosse-Wentrup, Klaus Gramann, Martin Buss. 537-544 [doi]
- Graph-Based Visual SaliencyJonathan Harel, Christof Koch, Pietro Perona. 545-552 [doi]
- Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point CloudsGloria Haro, Gregory Randall, Guillermo Sapiro. 553-560 [doi]
- Manifold DenoisingMatthias Hein, Markus Maier. 561-568 [doi]
- TrueSkill:::TM:::: A Bayesian Skill Rating SystemRalf Herbrich, Tom Minka, Thore Graepel. 569-576 [doi]
- Prediction on a Graph with a PerceptronMark Herbster, Massimiliano Pontil. 577-584 [doi]
- Geometric entropy minimization (GEM) for anomaly detection and localizationAlfred O. Hero III. 585-592 [doi]
- Single Channel Speech Separation Using Factorial DynamicsJohn R. Hershey, Trausti T. Kristjansson, Steven J. Rennie, Peder A. Olsen. 593-600 [doi]
- Correcting Sample Selection Bias by Unlabeled DataJiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf. 601-608 [doi]
- Sparse Representation for Signal ClassificationKe Huang, Selin Aviyente. 609-616 [doi]
- In-Network PCA and Anomaly DetectionLing Huang, XuanLong Nguyen, Minos N. Garofalakis, Michael I. Jordan, Anthony D. Joseph, Nina Taft. 617-624 [doi]
- Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian ModelsAlexander T. Ihler, Padhraic Smyth. 625-632 [doi]
- Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering AlgorithmRobert Jenssen, Torbjørn Eltoft, Mark Girolami, Deniz Erdogmus. 633-640 [doi]
- Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian ModelsMark Johnson, Thomas L. Griffiths, Sharon Goldwater. 641-648 [doi]
- A Humanlike Predictor of Facial AttractivenessAmit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-Or, Eytan Ruppin. 649-656 [doi]
- Clustering appearance and shape by learning jigsawsAnitha Kannan, John M. Winn, Carsten Rother. 657-664 [doi]
- A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical SystemsYoshinobu Kawahara, Takehisa Yairi, Kazuo Machida. 665-672 [doi]
- An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM ModelsS. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle. 673-680 [doi]
- Combining causal and similarity-based reasoningCharles Kemp, Patrick Shafto, Allison Berke, Joshua B. Tenenbaum. 681-688 [doi]
- A Nonparametric Approach to Bottom-Up Visual SaliencyWolf Kienzle, Felix A. Wichmann, Bernhard Schölkopf, Matthias O. Franz. 689-696 [doi]
- Hierarchical Dirichlet Processes with Random EffectsSeyoung Kim, Padhraic Smyth. 697-704 [doi]
- An Information Theoretic Framework for Eukaryotic Gradient SensingJoseph M. Kimmel, Richard M. Salter, Peter J. Thomas. 705-712 [doi]
- Information Bottleneck Optimization and Independent Component Extraction with Spiking NeuronsStefan Klampfl, Robert A. Legenstein, Wolfgang Maass. 713-720 [doi]
- Predicting spike times from subthreshold dynamics of a neuronRyota Kobayashi, Shigeru Shinomoto. 721-728 [doi]
- Gaussian and Wishart HyperkernelsRisi Imre Kondor, Tony Jebara. 729-736 [doi]
- Causal inference in sensorimotor integrationKonrad P. Körding, Joshua B. Tenenbaum. 737-744 [doi]
- Multiple timescales and uncertainty in motor adaptationKonrad P. Körding, Joshua B. Tenenbaum, Reza Shadmehr. 745-752 [doi]
- Reducing Calibration Time For Brain-Computer Interfaces: A Clustering ApproachMatthias Krauledat, Michael Schröder 0002, Benjamin Blankertz, Klaus-Robert Müller. 753-760 [doi]
- Accelerated Variational Dirichlet Process MixturesKenichi Kurihara, Max Welling, Nikos A. Vlassis. 761-768 [doi]
- PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs ClassifierAlexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier. 769-776 [doi]
- Inducing Metric Violations in Human Similarity JudgementsJulian Laub, Jakob Macke, Klaus-Robert Müller, Felix A. Wichmann. 777-784 [doi]
- Modelling transcriptional regulation using Gaussian ProcessesNeil D. Lawrence, Guido Sanguinetti, Magnus Rattray. 785-792 [doi]
- Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random FieldsChi-Hoon Lee, Shaojun Wang, Feng Jiao, Dale Schuurmans, Russell Greiner. 793-800 [doi]
- Efficient sparse coding algorithmsHonglak Lee, Alexis Battle, Rajat Raina, Andrew Y. Ng. 801-808 [doi]
- A Bayesian Approach to Diffusion Models of Decision-Making and Response TimeMichael D. Lee, Ian G. Fuss, Daniel J. Navarro. 809-816 [doi]
- Efficient Structure Learning of Markov Networks using L_1 -RegularizationSu-In Lee, Varun Ganapathi, Daphne Koller. 817-824 [doi]
- Aggregating Classification Accuracy across Time: Application to Single Trial EEGSteven Lemm, Christin Schäfer, Gabriel Curio. 825-832 [doi]
- Uncertainty, phase and oscillatory hippocampal recallMáté Lengyel, Peter Dayan. 833-840 [doi]
- Blind Motion Deblurring Using Image StatisticsAnat Levin. 841-848 [doi]
- Speakers optimize information density through syntactic reductionRoger Levy, T. Florian Jaeger. 849-856 [doi]
- Real-time adaptive information-theoretic optimization of neurophysiology experimentsJeremy Lewi, Robert J. Butera, Liam Paninski. 857-864 [doi]
- Ordinal Regression by Extended Binary ClassificationLing Li, Hsuan-Tien Lin. 865-872 [doi]
- Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse DataPing Li, Kenneth Ward Church, Trevor Hastie. 873-880 [doi]
- Generalized Regularized Least-Squares Learning with Predefined Features in a Hilbert SpaceWenye Li, Kin-Hong Lee, Kwong-Sak Leung. 881-888 [doi]
- Learnability and the doubling dimensionYi Li, Philip M. Long. 889-896 [doi]
- Emergence of conjunctive visual features by quadratic independent component analysisJussi T. Lindgren, Aapo Hyvärinen. 897-904 [doi]
- Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared StructureJennifer Listgarten, Radford M. Neal, Sam T. Roweis, Rachel Puckrin, Sean Cutler. 905-912 [doi]
- Analysis of Contour MotionsCe Liu, William T. Freeman, Edward H. Adelson. 913-920 [doi]
- Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributionsPhilip M. Long, Rocco A. Servedio. 921-928 [doi]
- Dynamic Foreground/Background Extraction from Images and Videos using Random PatchesLe Lu, Gregory D. Hager. 929-936 [doi]
- Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement LearningGediminas Luksys, Jérémie Knüsel, Denis Sheynikhovich, Carmen Sandi, Wulfram Gerstner. 937-944 [doi]
- Statistical Modeling of Images with Fields of Gaussian Scale MixturesSiwei Lyu, Eero P. Simoncelli. 945-952 [doi]
- An EM Algorithm for Localizing Multiple Sound Sources in Reverberant EnvironmentsMichael I. Mandel, Daniel P. W. Ellis, Tony Jebara. 953-960 [doi]
- Isotonic Conditional Random Fields and Local Sentiment FlowYi Mao, Guy Lebanon. 961-968 [doi]
- Part-based Probabilistic Point Matching using Equivalence ConstraintsGraham McNeill, Sethu Vijayakumar. 969-976 [doi]
- Modeling Dyadic Data with Binary Latent FactorsEdward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis. 977-984 [doi]
- Fast Discriminative Visual Codebooks using Randomized Clustering ForestsFrank Moosmann, Bill Triggs, Frédéric Jurie. 985-992 [doi]
- Context Effects in Category Learning: An Investigation of Four Probabilistic ModelsMichael C. Mozer, Michael Jones, Michael Shettel. 993-1000 [doi]
- Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic GamesChris Murray, Geoffrey J. Gordon. 1001-1008 [doi]
- Non-rigid point set registration: Coherent Point DriftAndriy Myronenko, Xubo B. Song, Miguel Á. Carreira-Perpiñán. 1009-1016 [doi]
- Fundamental Limitations of Spectral ClusteringBoaz Nadler, Meirav Galun. 1017-1024 [doi]
- On the Relation Between Low Density Separation, Spectral Clustering and Graph CutsHariharan Narayanan, Mikhail Belkin, Partha Niyogi. 1025-1032 [doi]
- A Nonparametric Bayesian Method for Inferring Features From Similarity JudgmentsDaniel J. Navarro, Thomas L. Griffiths. 1033-1040 [doi]
- Temporal dynamics of information content carried by neurons in the primary visual cortexDanko Nikolic, Stefan Häusler, Wolf Singer, Wolfgang Maass. 1041-1048 [doi]
- Blind source separation for over-determined delayed mixturesLars Omlor, Martin A. Giese. 1049-1056 [doi]
- The Neurodynamics of Belief Propagation on Binary Markov Random FieldsThomas Ott, Ruedi Stoop. 1057-1064 [doi]
- Handling Advertisements of Unknown Quality in Search AdvertisingSandeep Pandey, Christopher Olston. 1065-1072 [doi]
- Bayesian Model Scoring in Markov Random FieldsSridevi Parise, Max Welling. 1073-1080 [doi]
- Game Theoretic Algorithms for Protein-DNA bindingLuis Pérez-Breva, Luis E. Ortiz, Chen-Hsiang Yeang, Tommi Jaakkola. 1081-1088 [doi]
- Bayesian Image Super-resolution, ContinuedLyndsey C. Pickup, David P. Capel, Stephen J. Roberts, Andrew Zisserman. 1089-1096 [doi]
- Parameter Expanded Variational Bayesian MethodsYuan (Alan) Qi, Tommi Jaakkola. 1097-1104 [doi]
- Inferring Network Structure from Co-OccurrencesMichael Rabbat, Mário A. T. Figueiredo, Robert D. Nowak. 1105-1112 [doi]
- Unsupervised Regression with Applications to Nonlinear System IdentificationAli Rahimi, Ben Recht. 1113-1120 [doi]
- Stability of K -Means ClusteringAlexander Rakhlin, Andrea Caponnetto. 1121-1128 [doi]
- Learning to parse images of articulated bodiesDeva Ramanan. 1129-1136 [doi]
- Efficient Learning of Sparse Representations with an Energy-Based ModelMarc Aurelio Ranzato, Christopher S. Poultney, Sumit Chopra, Yann LeCun. 1137-1144 [doi]
- Learning to be Bayesian without SupervisionMartin Raphan, Eero P. Simoncelli. 1145-1152 [doi]
- Boosting Structured Prediction for Imitation LearningNathan D. Ratliff, David M. Bradley, J. Andrew Bagnell, Joel Chestnutt. 1153-1160 [doi]
- Large Scale Hidden Semi-Markov SVMsGunnar Rätsch, Sören Sonnenburg. 1161-1168 [doi]
- Natural Actor-Critic for Road Traffic OptimisationSilvia Richter, Douglas Aberdeen, Jin Yu. 1169-1176 [doi]
- Computation of Similarity Measures for Sequential Data using Generalized Suffix TreesKonrad Rieck, Pavel Laskov, Sören Sonnenburg. 1177-1184 [doi]
- Learning annotated hierarchies from relational dataDaniel M. Roy, Charles Kemp, Vikash K. Mansinghka, Joshua B. Tenenbaum. 1185-1192 [doi]
- Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk BoundsBenjamin I. P. Rubinstein, Peter L. Bartlett, J. Hyam Rubinstein. 1193-1200 [doi]
- Neurophysiological Evidence of Cooperative Mechanisms for Stereo ComputationJason M. Samonds, Brian Potetz, Tai Sing Lee. 1201-1208 [doi]
- Robotic Grasping of Novel ObjectsAshutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y. Ng. 1209-1216 [doi]
- Theory and Dynamics of Perceptual BistabilityPaul R. Schrater, Rashmi Sundareswara. 1217-1224 [doi]
- Fast Iterative Kernel PCANicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan. 1225-1232 [doi]
- Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel MethodsMatthias Seeger. 1233-1240 [doi]
- Information Bottleneck for Non Co-Occurrence DataYevgeny Seldin, Noam Slonim, Naftali Tishby. 1241-1248 [doi]
- Large Margin Hidden Markov Models for Automatic Speech RecognitionFei Sha, Lawrence K. Saul. 1249-1256 [doi]
- Nonlinear physically-based models for decoding motor-cortical population activityGregory Shakhnarovich, Sung-Phil Kim, Michael J. Black. 1257-1264 [doi]
- Convex Repeated Games and Fenchel DualityShai Shalev-Shwartz, Yoram Singer. 1265-1272 [doi]
- Recursive ICAHonghao Shan, Lingyun Zhang, Garrison W. Cottrell. 1273-1280 [doi]
- Chained BoostingChristian R. Shelton, Wesley Huie, Kin Fai Kan. 1281-1288 [doi]
- A recipe for optimizing a time-histogramHideaki Shimazaki, Shigeru Shinomoto. 1289-1296 [doi]
- Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotypeTobias Sing, Niko Beerenwinkel. 1297-1304 [doi]
- Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral SpaceKyung-Ah Sohn, Eric P. Xing. 1305-1312 [doi]
- Learning Dense 3D CorrespondenceFlorian Steinke, Bernhard Schölkopf, Volker Blanz. 1313-1320 [doi]
- An Oracle Inequality for Clipped Regularized Risk MinimizersIngo Steinwart, Don R. Hush, Clint Scovel. 1321-1328 [doi]
- Learning Structural Equation Models for fMRIAmos J. Storkey, Enrico Simonotto, Heather Whalley, Stephen Lawrie, Lawrence Murray, David McGonigle. 1329-1336 [doi]
- Mixture Regression for Covariate ShiftAmos J. Storkey, Masashi Sugiyama. 1337-1344 [doi]
- Modeling Human Motion Using Binary Latent VariablesGraham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis. 1345-1352 [doi]
- A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet AllocationYee Whye Teh, David Newman, Max Welling. 1353-1360 [doi]
- Towards a general independent subspace analysisFabian J. Theis. 1361-1368 [doi]
- Linearly-solvable Markov decision problemsEmanuel Todorov. 1369-1376 [doi]
- Logistic Regression for Single Trial EEG ClassificationRyota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller. 1377-1384 [doi]
- Large Margin Component AnalysisLorenzo Torresani, Kuang-Chih Lee. 1385-1392 [doi]
- Learning Motion Style Synthesis from Perceptual ObservationsLorenzo Torresani, Peggy Hackney, Christoph Bregler. 1393-1400 [doi]
- Large-Scale Sparsified Manifold RegularizationIvor W. Tsang, James T. Kwok. 1401-1408 [doi]
- Scalable Discriminative Learning for Natural Language Parsing and TranslationJoseph P. Turian, Benjamin Wellington, I. Dan Melamed. 1409-1416 [doi]
- Generalized Maximum Margin Clustering and Unsupervised Kernel LearningHamed Valizadegan, Rong Jin. 1417-1424 [doi]
- A Complexity-Distortion Approach to Joint Pattern AlignmentAndrea Vedaldi, Stefano Soatto. 1425-1432 [doi]
- Online Clustering of Moving HyperplanesRené Vidal. 1433-1440 [doi]
- Comparative Gene Prediction using Conditional Random FieldsJade P. Vinson, David DeCaprio, Matthew D. Pearson, Stacey Luoma, James E. Galagan. 1441-1448 [doi]
- Fast Computation of Graph KernelsS. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph. 1449-1456 [doi]
- Temporal Coding using the Response Properties of Spiking NeuronsThomas Voegtlin. 1457-1464 [doi]
- High-Dimensional Graphical Model Selection Using /ell_1 -Regularized Logistic RegressionMartin J. Wainwright, Pradeep D. Ravikumar, John D. Lafferty. 1465-1472 [doi]
- Attentional Processing on a Spike-Based VLSI Neural NetworkYingxue Wang, Rodney J. Douglas, Shih-Chii Liu. 1473-1480 [doi]
- Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the DimensionManfred K. Warmuth, Dima Kuzmin. 1481-1488 [doi]
- Graph Laplacian Regularization for Large-Scale Semidefinite ProgrammingKilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul. 1489-1496 [doi]
- A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular StereoOliver Williams. 1497-1504 [doi]
- Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source LocalizationDavid P. Wipf, Rey Ramírez, Jason A. Palmer, Scott Makeig, Bhaskar D. Rao. 1505-1512 [doi]
- Particle Filtering for Nonparametric Bayesian Matrix FactorizationFrank Wood, Thomas L. Griffiths. 1513-1520 [doi]
- A Scalable Machine Learning Approach to GoLin Wu, Pierre Baldi. 1521-1528 [doi]
- A Local Learning Approach for ClusteringMingrui Wu, Bernhard Schölkopf. 1529-1536 [doi]
- The Robustness-Performance Tradeoff in Markov Decision ProcessesHuan Xu, Shie Mannor. 1537-1544 [doi]
- Optimal Change-Detection and Spiking NeuronsAngela J. Yu. 1545-1552 [doi]
- Stochastic Relational Models for Discriminative Link PredictionKai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu. 1553-1560 [doi]
- Nonnegative Sparse PCARon Zass, Amnon Shashua. 1561-1568 [doi]
- Doubly Stochastic Normalization for Spectral ClusteringRon Zass, Amnon Shashua. 1569-1576 [doi]
- Simplifying Mixture Models through Function ApproximationKai Zhang, James T. Kwok. 1577-1584 [doi]
- Hyperparameter Learning for Graph Based Semi-supervised Learning AlgorithmsXinhua Zhang, Wee Sun Lee. 1585-1592 [doi]
- MLLE: Modified Locally Linear Embedding Using Multiple WeightsZhenyue Zhang, Jing Wang. 1593-1600 [doi]
- Learning with Hypergraphs: Clustering, Classification, and EmbeddingDengyong Zhou, Jiayuan Huang, Bernhard Schölkopf. 1601-1608 [doi]
- Multi-Instance Multi-Label Learning with Application to Scene ClassificationZhi-Hua Zhou, Min-Ling Zhang. 1609-1616 [doi]
- Unsupervised Learning of a Probabilistic Grammar for Object Detection and ParsingLong Zhu, Yuanhao Chen, Alan L. Yuille. 1617-1624 [doi]
- A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG dataJohanna M. Zumer, Hagai Thomas Attias, Kensuke Sekihara, Srikantan S. Nagarajan. 1625-1632 [doi]