Abstract is missing.
- Inferring Elapsed Time from Stochastic Neural ProcessesMisha Ahrens, Maneesh Sahani. 1-8 [doi]
- Fitted Q-iteration in continuous action-space MDPsAndrás Antos, Rémi Munos, Csaba Szepesvári. 9-16 [doi]
- Variational Inference for Diffusion ProcessesCédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford, John Shawe-Taylor. 17-24 [doi]
- A Spectral Regularization Framework for Multi-Task Structure LearningAndreas Argyriou, Charles A. Micchelli, Massimiliano Pontil, Yiming Ying. 25-32 [doi]
- Random Sampling of States in Dynamic ProgrammingChristopher G. Atkeson, Benjamin Stephens. 33-40 [doi]
- Progressive mixture rules are deviation suboptimalJean-Yves Audibert. 41-48 [doi]
- DIFFRAC: a discriminative and flexible framework for clusteringFrancis Bach, Zaïd Harchaoui. 49-56 [doi]
- Optimal ROC Curve for a Combination of ClassifiersMarco Barreno, Alvaro Cardenas, J. Doug Tygar. 57-64 [doi]
- Adaptive Online Gradient DescentPeter L. Bartlett, Elad Hazan, Alexander Rakhlin. 65-72 [doi]
- One-Pass BoostingZafer Barutçuoglu, Philip M. Long, Rocco A. Servedio. 73-80 [doi]
- Comparing Bayesian models for multisensory cue combination without mandatory integrationUlrik Beierholm, Konrad P. Körding, Ladan Shams, Wei Ji Ma. 81-88 [doi]
- On Sparsity and Overcompleteness in Image ModelsPietro Berkes, Richard Turner, Maneesh Sahani. 89-96 [doi]
- Near-Maximum Entropy Models for Binary Neural Representations of Natural ImagesMatthias Bethge, Philipp Berens. 97-104 [doi]
- Incremental Natural Actor-Critic AlgorithmsShalabh Bhatnagar, Richard S. Sutton, Mohammad Ghavamzadeh, Mark Lee. 105-112 [doi]
- Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer InterfacingBenjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike Hohlefeld, Vadim V. Nikulin, Klaus-Robert Müller. 113-120 [doi]
- Supervised Topic ModelsDavid M. Blei, Jon D. McAuliffe. 121-128 [doi]
- Learning Bounds for Domain AdaptationJohn Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman. 129-136 [doi]
- Feature Selection Methods for Improving Protein Structure Prediction with RosettaBen Blum, Michael I. Jordan, David Kim, Rhiju Das, Philip Bradley, David Baker. 137-144 [doi]
- A neural network implementing optimal state estimation based on dynamic spike train decodingOmer Bobrowski, Ron Meir, Shy Shoham, Yonina C. Eldar. 145-152 [doi]
- Multi-task Gaussian Process PredictionEdwin V. Bonilla, Kian Ming Chai, Chris Williams. 153-160 [doi]
- The Tradeoffs of Large Scale LearningLéon Bottou, Olivier Bousquet. 161-168 [doi]
- A Probabilistic Approach to Language ChangeAlexandre Bouchard-Côté, Percy Liang, Thomas L. Griffiths, Dan Klein. 169-176 [doi]
- Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image DataSabri Boutemedjet, Djemel Ziou, Nizar Bouguila. 177-184 [doi]
- FilterBoost: Regression and Classification on Large DatasetsJoseph K. Bradley, Robert E. Schapire. 185-192 [doi]
- Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking NeuronsLars Buesing, Wolfgang Maass. 193-200 [doi]
- The Distribution Family of Similarity DistancesGertjan J. Burghouts, Arnold W. M. Smeulders, Jan-Mark Geusebroek. 201-208 [doi]
- Discriminative Keyword Selection Using Support Vector MachinesWilliam Campbell, Fred Richardson. 209-216 [doi]
- Evaluating Search Engines by Modeling the Relationship Between Relevance and ClicksBen Carterette, Rosie Jones. 217-224 [doi]
- Subspace-Based Face Recognition in Analog VLSIGonzalo Carvajal, Waldo Valenzuela, Miguel Figueroa. 225-232 [doi]
- A learning framework for nearest neighbor searchLawrence Cayton, Sanjoy Dasgupta. 233-240 [doi]
- Predicting human gaze using low-level saliency combined with face detectionMoran Cerf, Jonathan Harel, Wolfgang Einhäuser, Christof Koch. 241-248 [doi]
- Adaptive Embedded Subgraph Algorithms using Walk-Sum AnalysisVenkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky. 249-256 [doi]
- Parallelizing Support Vector Machines on Distributed ComputersEdward Y. Chang, Kaihua Zhu, Hao Wang, Hongjie Bai, Jian Li, Zhihuan Qiu, Hang Cui. 257-264 [doi]
- Augmented Functional Time Series Representation and Forecasting with Gaussian ProcessesNicolas Chapados, Yoshua Bengio. 265-272 [doi]
- Efficient Principled Learning of Thin Junction TreesAnton Chechetka, Carlos Guestrin. 273-280 [doi]
- Regularized Boost for Semi-Supervised LearningKe Chen, Shihai Wang. 281-288 [doi]
- Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and ParsingYuanhao Chen, Long Zhu, Chenxi Lin, Alan L. Yuille, HongJiang Zhang. 289-296 [doi]
- Cooled and Relaxed Survey Propagation for MRFsHai Leong Chieu, Wee Sun Lee, Yee Whye Teh. 297-304 [doi]
- How SVMs can estimate quantiles and the medianAndreas Christmann, Ingo Steinwart. 305-312 [doi]
- Second Order Bilinear Discriminant Analysis for single trial EEG analysisChristoforos Christoforou, Paul Sajda, Lucas C. Parra. 313-320 [doi]
- An online Hebbian learning rule that performs Independent Component AnalysisClaudia Clopath, André Longtin, Wulfram Gerstner. 321-328 [doi]
- Inferring Neural Firing Rates from Spike Trains Using Gaussian ProcessesJohn P. Cunningham, Byron M. Yu, Krishna V. Shenoy, Maneesh Sahani. 329-336 [doi]
- TrueSkill Through Time: Revisiting the History of ChessPierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel. 337-344 [doi]
- The Price of Bandit Information for Online OptimizationVarsha Dani, Thomas P. Hayes, Sham Kakade. 345-352 [doi]
- A general agnostic active learning algorithmSanjoy Dasgupta, Daniel Hsu, Claire Monteleoni. 353-360 [doi]
- Measuring Neural Synchrony by Message PassingJustin Dauwels, François B. Vialatte, Tomasz M. Rutkowski, Andrzej Cichocki. 361-368 [doi]
- The rat as particle filterNathaniel Daw, Aaron Courville. 369-376 [doi]
- Efficient multiple hyperparameter learning for log-linear modelsChuong B. Do, Chuan-Sheng Foo, Andrew Y. Ng. 377-384 [doi]
- Automatic Generation of Social Tags for Music RecommendationDouglas Eck, Paul Lamere, Thierry Bertin-Mahieux, Stephen Green. 385-392 [doi]
- Bayesian binning beats approximate alternatives: estimating peri-stimulus time histogramsDominik Endres, Mike W. Oram, Johannes Schindelin, Peter Földiák. 393-400 [doi]
- A probabilistic model for generating realistic lip movements from speechGwenn Englebienne, Tim Cootes, Magnus Rattray. 401-408 [doi]
- Active Preference Learning with Discrete Choice DataEric Brochu, Nando de Freitas, Abhijeet Ghosh. 409-416 [doi]
- Catching Up Faster in Bayesian Model Selection and Model AveragingTim van Erven, Peter Grunwald, Steven de Rooij. 417-424 [doi]
- Anytime Induction of Cost-sensitive TreesSaher Esmeir, Shaul Markovitch. 425-432 [doi]
- Learning Visual AttributesVittorio Ferrari, Andrew Zisserman. 433-440 [doi]
- EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error DetectionPierre W. Ferrez, José del R. Millán. 441-448 [doi]
- Optimal models of sound localization by barn owlsBrian Fischer. 449-456 [doi]
- A Bayesian Framework for Cross-Situational Word-LearningMichael Frank, Noah Goodman, Joshua B. Tenenbaum. 457-464 [doi]
- Sequential Hypothesis Testing under Stochastic DeadlinesPeter Frazier, Angela Yu. 465-472 [doi]
- Learning the structure of manifolds using random projectionsYoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma. 473-480 [doi]
- Discovering Weakly-Interacting Factors in a Complex Stochastic ProcessCharlie Frogner, Avi Pfeffer. 481-488 [doi]
- Kernel Measures of Conditional DependenceKenji Fukumizu, Arthur Gretton, Xiaohai Sun, Bernhard Schölkopf. 489-496 [doi]
- The discriminant center-surround hypothesis for bottom-up saliencyDashan Gao, Vijay Mahadevan, Nuno Vasconcelos. 497-504 [doi]
- Learning Horizontal Connections in a Sparse Coding Model of Natural ImagesPierre Garrigues, Bruno Olshausen. 505-512 [doi]
- Iterative Non-linear Dimensionality Reduction with Manifold SculptingMichael Gashler, Dan Ventura, Tony R. Martinez. 513-520 [doi]
- On higher-order perceptron algorithmsClaudio Gentile, Fabio Vitale, Cristian Brotto. 521-528 [doi]
- Bayesian Inference for Spiking Neuron Models with a Sparsity PriorSebastian Gerwinn, Jakob Macke, Matthias Seeger, Matthias Bethge. 529-536 [doi]
- Predicting Brain States from fMRI Data: Incremental Functional Principal Component RegressionSennay Ghebreab, Arnold W. M. Smeulders, Pieter W. Adriaans. 537-544 [doi]
- A configurable analog VLSI neural network with spiking neurons and self-regulating plastic synapses Massimiliano Giulioni, Mario Pannunzi, Davide Badoni, Vittorio Dante, Paolo Del Giudice. 545-552 [doi]
- Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-RelaxationsAmir Globerson, Tommi Jaakkola. 553-560 [doi]
- Competition Adds ComplexityJudy Goldsmith, Martin Mundhenk. 561-568 [doi]
- Expectation Maximization and Posterior ConstraintsJoão Graça, Kuzman Ganchev, Ben Taskar. 569-576 [doi]
- Unconstrained On-line Handwriting Recognition with Recurrent Neural NetworksAlex Graves, Santiago Fernández, Marcus Liwicki, Horst Bunke, Jürgen Schmidhuber. 577-584 [doi]
- A Kernel Statistical Test of IndependenceArthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alex J. Smola. 585-592 [doi]
- Discriminative Batch Mode Active LearningYuhong Guo, Dale Schuurmans. 593-600 [doi]
- Convex Relaxations of Latent Variable TrainingYuhong Guo, Dale Schuurmans. 601-608 [doi]
- Testing for Homogeneity with Kernel Fisher Discriminant AnalysisZaïd Harchaoui, Francis Bach, Eric Moulines. 609-616 [doi]
- Catching Change-points with LassoZaïd Harchaoui, Céline Lévy-Leduc. 617-624 [doi]
- Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to EquilibriaElad Hazan, Satyen Kale. 625-632 [doi]
- Nearest-Neighbor-Based Active Learning for Rare Category DetectionJingrui He, Jaime G. Carbonell. 633-640 [doi]
- Random Projections for Manifold LearningChinmay Hegde, Michael B. Wakin, Richard G. Baraniuk. 641-648 [doi]
- Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical ApproachJosé Miguel Hernández-Lobato, Tjeerd Dijkstra, Tom Heskes. 649-656 [doi]
- Modeling homophily and stochastic equivalence in symmetric relational dataPeter Hoff. 657-664 [doi]
- Bayesian Policy Learning with Trans-Dimensional MCMCMatthew Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra. 665-672 [doi]
- Ultrafast Monte Carlo for Statistical SummationsMichael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.. 673-680 [doi]
- Learning Monotonic Transformations for ClassificationAndrew Howard, Tony Jebara. 681-688 [doi]
- What makes some POMDP problems easy to approximate?David Hsu, Wee Sun Lee, Nan Rong. 689-696 [doi]
- Efficient Inference for Distributions on PermutationsJonathan Huang, Carlos Guestrin, Leonidas J. Guibas. 697-704 [doi]
- Temporal Difference Updating without a Learning RateMarcus Hutter, Shane Legg. 705-712 [doi]
- Density Estimation under Independent Similarly Distributed Sampling AssumptionsTony Jebara, Yingbo Song, Kapil Thadani. 713-720 [doi]
- Computing Robust Counter-StrategiesMichael Johanson, Martin Zinkevich, Michael H. Bowling. 721-728 [doi]
- Local Algorithms for Approximate Inference in Minor-Excluded GraphsKyomin Jung, Devavrat Shah. 729-736 [doi]
- Multi-Task Learning via Conic ProgrammingTsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai. 737-744 [doi]
- Privacy-Preserving Belief Propagation and SamplingMichael Kearns, Jinsong Tan, Jennifer Wortman. 745-752 [doi]
- Learning and using relational theoriesCharles Kemp, Noah Goodman, Joshua B. Tenenbaum. 753-760 [doi]
- Learning with Tree-Averaged Densities and DistributionsSergey Kirshner. 761-768 [doi]
- Hierarchical Apprenticeship Learning with Application to Quadruped LocomotionJ. Zico Kolter, Pieter Abbeel, Andrew Y. Ng. 769-776 [doi]
- Selecting Observations against Adversarial ObjectivesAndreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta. 777-784 [doi]
- Structured Learning with Approximate InferenceAlex Kulesza, Fernando Pereira. 785-792 [doi]
- A Randomized Algorithm for Large Scale Support Vector LearningKrishnan Kumar, Chiru Bhattacharyya, Ramesh Hariharan. 793-800 [doi]
- Statistical Analysis of Semi-Supervised RegressionJohn D. Lafferty, Larry A. Wasserman. 801-808 [doi]
- Extending position/phase-shift tuning to motion energy neurons improves velocity discriminationYiu Man Lam, Bertram Shi. 809-816 [doi]
- The Epoch-Greedy Algorithm for Multi-armed Bandits with Side InformationJohn Langford, Tong Zhang. 817-824 [doi]
- Convex Clustering with Exemplar-Based ModelsDanial Lashkari, Polina Golland. 825-832 [doi]
- Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo MethodsAlessandro Lazaric, Marcello Restelli, Andrea Bonarini. 833-840 [doi]
- Learning the 2-D Topology of ImagesNicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl. 841-848 [doi]
- Topmoumoute Online Natural Gradient AlgorithmNicolas Le Roux, Pierre-Antoine Manzagol, Yoshua Bengio. 849-856 [doi]
- Non-parametric Modeling of Partially Ranked DataGuy Lebanon, Yi Mao. 857-864 [doi]
- Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domainsAndrea Lecchini-Visintini, John Lygeros, Jan M. Maciejowski. 865-872 [doi]
- Sparse deep belief net model for visual area V2Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng. 873-880 [doi]
- Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent PlasticityRobert A. Legenstein, Dejan Pecevski, Wolfgang Maass. 881-888 [doi]
- Hippocampal Contributions to Control: The Third WayMáté Lengyel, Peter Dayan. 889-896 [doi]
- McRank: Learning to Rank Using Multiple Classification and Gradient BoostingPing Li, Christopher J. C. Burges, Qiang Wu. 897-904 [doi]
- A Unified Near-Optimal Estimator For Dimension Reduction in l::alpha::(0 < alpha <= 2) Using Stable Random ProjectionsPing Li, Trevor Hastie. 905-912 [doi]
- Agreement-Based LearningPercy Liang, Dan Klein, Michael I. Jordan. 913-920 [doi]
- Blind channel identification for speech dereverberation using l1-norm sparse learningYuanqing Lin, Jingdong Chen, Youngmoo Kim, Daniel Lee. 921-928 [doi]
- Mining Internet-Scale Software RepositoriesErik Linstead, Paul Rigor, Sushil Krishna Bajracharya, Cristina Videira Lopes, Pierre Baldi. 929-936 [doi]
- Semi-Supervised Multitask LearningQiuhua Liu, Xuejun Liao, Lawrence Carin. 937-944 [doi]
- Boosting the Area under the ROC CurvePhilip M. Long, Rocco A. Servedio. 945-952 [doi]
- Support Vector Machine Classification with Indefinite KernelsRonny Luss, Alexandre d Aspremont. 953-960 [doi]
- Consistent Minimization of Clustering Objective FunctionsUlrike von Luxburg, Sébastien Bubeck, Stefanie Jegelka, Michael Kaufmann. 961-968 [doi]
- Receptive Fields without Spike-TriggeringJakob Macke, Guenther Zeck, Matthias Bethge. 969-976 [doi]
- Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity RecognitionMaryam Mahdaviani, Tanzeem Choudhury. 977-984 [doi]
- Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical EvaluationsM. M. Mahmud, Sylvian R. Ray. 985-992 [doi]
- Scan Strategies for Meteorological RadarsVictoria Manfredi, Jim Kurose. 993-1000 [doi]
- Locality and low-dimensions in the prediction of natural experience from fMRIFrancois Meyer, Greg Stephens. 1001-1008 [doi]
- Learning to classify complex patterns using a VLSI network of spiking neuronsSrinjoy Mitra, Giacomo Indiveri, Stefano Fusi. 1009-1016 [doi]
- The Infinite Markov ModelDaichi Mochihashi, Eiichiro Sumita. 1017-1024 [doi]
- Stability Bounds for Non-i.i.d. ProcessesMehryar Mohri, Afshin Rostamizadeh. 1025-1032 [doi]
- Experience-Guided Search: A Theory of Attentional ControlMichael Mozer, David Baldwin. 1033-1040 [doi]
- An Analysis of Convex Relaxations for MAP EstimationPawan Mudigonda, Vladimir Kolmogorov, Philip H. S. Torr. 1041-1048 [doi]
- Continuous Time Particle Filtering for fMRILawrence Murray, Amos J. Storkey. 1049-1056 [doi]
- The Generalized FITC ApproximationAndrew Naish-Guzman, Sean B. Holden. 1057-1064 [doi]
- Robust Regression with Twinned Gaussian ProcessesAndrew Naish-Guzman, Sean B. Holden. 1065-1072 [doi]
- Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking NeuronsEmre Neftci, Elisabetta Chicca, Giacomo Indiveri, Jean-Jacques E. Slotine, Rodney J. Douglas. 1073-1080 [doi]
- Distributed Inference for Latent Dirichlet AllocationDavid Newman, Arthur Asuncion, Padhraic Smyth, Max Welling. 1081-1088 [doi]
- Estimating divergence functionals and the likelihood ratio by penalized convex risk minimizationXuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan. 1089-1096 [doi]
- Heterogeneous Component AnalysisShigeyuki Oba, Motoaki Kawanabe, Klaus-Robert Müller, Shin Ishii. 1097-1104 [doi]
- Variational inference for Markov jump processesManfred Opper, Guido Sanguinetti. 1105-1112 [doi]
- CPR for CSPs: A Probabilistic Relaxation of Constraint PropagationLuis E. Ortiz. 1113-1120 [doi]
- Modeling image patches with a directed hierarchy of Markov random fieldsSimon Osindero, Geoffrey E. Hinton. 1121-1128 [doi]
- Kernels on Attributed Pointsets with ApplicationsMehul Parsana, Sourangshu Bhattacharya, Chiru Bhattacharyya, K. R. Ramakrishnan. 1129-1136 [doi]
- A Risk Minimization Principle for a Class of Parzen EstimatorsKristiaan Pelckmans, Johan A. K. Suykens, Bart De Moor. 1137-1144 [doi]
- Congruence between model and human attention reveals unique signatures of critical visual eventsRobert J. Peters, Laurent Itti. 1145-1152 [doi]
- Discriminative Log-Linear Grammars with Latent VariablesSlav Petrov, Dan Klein. 1153-1160 [doi]
- Neural characterization in partially observed populations of spiking neuronsJonathan Pillow, Peter E. Latham. 1161-1168 [doi]
- Fast Variational Inference for Large-scale Internet DiagnosisJohn C. Platt, Emre Kiciman, David A. Maltz. 1169-1176 [doi]
- Random Features for Large-Scale Kernel MachinesAli Rahimi, Benjamin Recht. 1177-1184 [doi]
- Sparse Feature Learning for Deep Belief NetworksMarc Aurelio Ranzato, Y-Lan Boureau, Yann LeCun. 1185-1192 [doi]
- Retrieved context and the discovery of semantic structureVinayak Rao, Marc Howard. 1193-1200 [doi]
- SpAM: Sparse Additive ModelsPradeep D. Ravikumar, Han Liu, John D. Lafferty, Larry A. Wasserman. 1201-1208 [doi]
- On Ranking in Survival Analysis: Bounds on the Concordance IndexVikas C. Raykar, Harald Steck, Balaji Krishnapuram, Cary Dehing-Oberije, Philippe Lambin. 1209-1216 [doi]
- GRIFT: A graphical model for inferring visual classification features from human dataMichael Ross, Andrew Cohen. 1217-1224 [doi]
- Bayes-Adaptive POMDPsStéphane Ross, Brahim Chaib-draa, Joelle Pineau. 1225-1232 [doi]
- Theoretical Analysis of Heuristic Search Methods for Online POMDPsStéphane Ross, Joelle Pineau, Brahim Chaib-draa. 1233-1240 [doi]
- Object Recognition by Scene AlignmentBryan C. Russell, Antonio B. Torralba, Ce Liu, Robert Fergus, William T. Freeman. 1241-1248 [doi]
- Using Deep Belief Nets to Learn Covariance Kernels for Gaussian ProcessesRuslan Salakhutdinov, Geoffrey E. Hinton. 1249-1256 [doi]
- Probabilistic Matrix FactorizationRuslan Salakhutdinov, Andriy Mnih. 1257-1264 [doi]
- Markov Chain Monte Carlo with PeopleAdam Sanborn, Thomas L. Griffiths. 1265-1272 [doi]
- Linear programming analysis of loopy belief propagation for weighted matchingSujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky. 1273-1280 [doi]
- Message Passing for Max-weight Independent SetSujay Sanghavi, Devavrat Shah, Alan S. Willsky. 1281-1288 [doi]
- Multiple-Instance Active LearningBurr Settles, Mark Craven, Soumya Ray. 1289-1296 [doi]
- Cluster Stability for Finite SamplesOhad Shamir, Naftali Tishby. 1297-1304 [doi]
- Better than least squares: comparison of objective functions for estimating linear-nonlinear modelsTatyana Sharpee. 1305-1312 [doi]
- Sparse Overcomplete Latent Variable Decomposition of Counts DataMadhusudana V. S. Shashanka, Bhiksha Raj, Paris Smaragdis. 1313-1320 [doi]
- Collective Inference on Markov Models for Modeling Bird MigrationDaniel Sheldon, M. A. Saleh Elmohamed, Dexter Kozen. 1321-1328 [doi]
- A Constraint Generation Approach to Learning Stable Linear Dynamical SystemsSajid Siddiqi, Byron Boots, Geoffrey Gordon. 1329-1336 [doi]
- Combined discriminative and generative articulated pose and non-rigid shape estimationLeonid Sigal, Alexandru O. Balan, Michael J. Black. 1337-1344 [doi]
- Hidden Common Cause Relations in Relational LearningRicardo Silva, Wei Chu, Zoubin Ghahramani. 1345-1352 [doi]
- Ensemble Clustering using Semidefinite ProgrammingVikas Singh, Lopamudra Mukherjee, Jiming Peng, Jinhui Xu. 1353-1360 [doi]
- The Value of Labeled and Unlabeled Examples when the Model is ImperfectKaushik Sinha, Mikhail Belkin. 1361-1368 [doi]
- An Analysis of Inference with the UniversumFabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf. 1369-1376 [doi]
- Bundle Methods for Machine LearningAlex J. Smola, S. V. N. Vishwanathan, Quoc V. Le. 1377-1384 [doi]
- Colored Maximum Variance UnfoldingLe Song, Alex J. Smola, Karsten M. Borgwardt, Arthur Gretton. 1385-1392 [doi]
- New Outer Bounds on the Marginal PolytopeDavid Sontag, Tommi Jaakkola. 1393-1400 [doi]
- An in-silico Neural Model of Dynamic Routing through Neuronal CoherenceDevarajan Sridharan, Brian Percival, John Arthur, Kwabena Boahen. 1401-1408 [doi]
- A Bayesian Model of Conditioned PerceptionAlan Stocker, Eero P. Simoncelli. 1409-1416 [doi]
- Online Linear Regression and Its Application to Model-Based Reinforcement LearningAlexander L. Strehl, Michael L. Littman. 1417-1424 [doi]
- Loop Series and Bethe Variational Bounds in Attractive Graphical ModelsErik B. Sudderth, Martin J. Wainwright, Alan S. Willsky. 1425-1432 [doi]
- Direct Importance Estimation with Model Selection and Its Application to Covariate Shift AdaptationMasashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bünau, Motoaki Kawanabe. 1433-1440 [doi]
- Efficient Bayesian Inference for Dynamically Changing GraphsÖzgür Sümer, Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu. 1441-1448 [doi]
- A Game-Theoretic Approach to Apprenticeship LearningUmar Syed, Robert E. Schapire. 1449-1456 [doi]
- Hierarchical PenalizationMarie Szafranski, Yves Grandvalet, Pierre Morizet-Mahoudeaux. 1457-1464 [doi]
- Receding Horizon Differential Dynamic ProgrammingYuval Tassa, Tom Erez, William D. Smart. 1465-1472 [doi]
- Bayesian Agglomerative Clustering with CoalescentsYee Whye Teh, Hal Daumé III, Daniel M. Roy. 1473-1480 [doi]
- Collapsed Variational Inference for HDPYee Whye Teh, Kenichi Kurihara, Max Welling. 1481-1488 [doi]
- Convex Learning with InvariancesChoon Hui Teo, Amir Globerson, Sam T. Roweis, Alex J. Smola. 1489-1496 [doi]
- Managing Power Consumption and Performance of Computing Systems Using Reinforcement LearningGerald Tesauro, Rajarshi Das, Hoi Chan, Jeffrey O. Kephart, David Levine, Freeman L. Rawson III, Charles Lefurgy. 1497-1504 [doi]
- Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPsAmbuj Tewari, Peter L. Bartlett. 1505-1512 [doi]
- The Infinite Gamma-Poisson Feature ModelMichalis K. Titsias. 1513-1520 [doi]
- A Bayesian LDA-based model for semi-supervised part-of-speech taggingKristina Toutanova, Mark Johnson. 1521-1528 [doi]
- Configuration Estimates Improve Pedestrian FindingDuan Tran, David Forsyth. 1529-1536 [doi]
- Estimating disparity with confidence from energy neuronsEric K. C. Tsang, Bertram Emil Shi. 1537-1544 [doi]
- Modeling Natural Sounds with Modulation Cascade ProcessesRichard Turner, Maneesh Sahani. 1545-1552 [doi]
- Scene Segmentation with CRFs Learned from Partially Labeled ImagesJakob J. Verbeek, Bill Triggs. 1553-1560 [doi]
- Learning with Transformation Invariant KernelsChristian Walder, Olivier Chapelle. 1561-1568 [doi]
- Stable Dual Dynamic ProgrammingTao Wang, Daniel J. Lizotte, Michael H. Bowling, Dale Schuurmans. 1569-1576 [doi]
- Spatial Latent Dirichlet AllocationXiaogang Wang, Eric Grimson. 1577-1584 [doi]
- Boosting Algorithms for Maximizing the Soft MarginManfred K. Warmuth, Karen A. Glocer, Gunnar Rätsch. 1585-1592 [doi]
- COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alex J. Smola. 1593-1600 [doi]
- Infinite State Bayes-Nets for Structured DomainsMax Welling, Ian Porteous, Evgeniy Bart. 1601-1608 [doi]
- Modelling motion primitives and their timing in biologically executed movementsBen Williams, Marc Toussaint, Amos J. Storkey. 1609-1616 [doi]
- Exponential Family Predictive Representations of StateDavid Wingate, Satinder Singh Baveja. 1617-1624 [doi]
- A New View of Automatic Relevance DeterminationDavid P. Wipf, Srikantan Nagarajan. 1625-1632 [doi]
- Classification via Minimum Incremental Coding Length (MICL)John Wright, Yangyu Tao, Zhouchen Lin, Yi Ma, Heung-Yeung Shum. 1633-1640 [doi]
- Efficient Convex Relaxation for Transductive Support Vector MachineZenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu. 1641-1648 [doi]
- Discriminative K-means for ClusteringJieping Ye, Zheng Zhao, Mingrui Wu. 1649-1656 [doi]
- Gaussian Process Models for Link Analysis and Transfer LearningKai Yu, Wei Chu. 1657-1664 [doi]
- Bayesian Co-TrainingShipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, R. Bharat Rao. 1665-1672 [doi]
- The Noisy-Logical Distribution and its Application to Causal InferenceAlan L. Yuille, Hongjing Lu. 1673-1680 [doi]
- Multiple-Instance Pruning For Learning Efficient Cascade DetectorsCha Zhang, Paul A. Viola. 1681-1688 [doi]
- HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and TranslationBing Zhao, Eric P. Xing. 1689-1696 [doi]
- A General Boosting Method and its Application to Learning Ranking Functions for Web SearchZhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun. 1697-1704 [doi]
- People Tracking with the Laplacian Eigenmaps Latent Variable ModelZhengdong Lu, Miguel Á. Carreira-Perpiñán, Cristian Sminchisescu. 1705-1712 [doi]
- Compressed RegressionShuheng Zhou, John D. Lafferty, Larry A. Wasserman. 1713-1720 [doi]
- Predictive Matrix-Variate t ModelsShenghuo Zhu, Kai Yu, Yihong Gong. 1721-1728 [doi]
- Regret Minimization in Games with Incomplete InformationMartin Zinkevich, Michael Johanson, Michael H. Bowling, Carmelo Piccione. 1729-1736 [doi]