Abstract is missing.
- Efficient Multiscale Sampling from Products of Gaussian MixturesAlexander T. Ihler, Erik B. Sudderth, William T. Freeman, Alan S. Willsky. 1-8 [doi]
- Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User ProfilesMark Girolami, Ata Kabán. 9-16 [doi]
- Hierarchical Topic Models and the Nested Chinese Restaurant ProcessDavid M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum. 17-24 [doi]
- Max-Margin Markov NetworksBenjamin Taskar, Carlos Guestrin, Daphne Koller. 25-32 [doi]
- Invariant Pattern Recognition by Semi-Definite Programming MachinesThore Graepel, Ralf Herbrich. 33-40 [doi]
- Learning a Distance Metric from Relative ComparisonsMatthew Schultz, Thorsten Joachims. 41-48 [doi]
- 1-norm Support Vector MachinesJi Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani. 49-56 [doi]
- Image Reconstruction by Linear ProgrammingKoji Tsuda, Gunnar Rätsch. 57-64 [doi]
- Multiple-Instance Learning via Disjunctive Programming BoostingStuart Andrews, Thomas Hofmann. 65-72 [doi]
- Convex Methods for TransductionTijl De Bie, Nello Cristianini. 73-80 [doi]
- Kernel Dimensionality Reduction for Supervised LearningKenji Fukumizu, Francis R. Bach, Michael I. Jordan. 81-88 [doi]
- Clustering with the Connectivity KernelBernd Fischer, Volker Roth, Joachim M. Buhmann. 89-96 [doi]
- Efficient and Robust Feature Extraction by Maximum Margin CriterionHaifeng Li, Tao Jiang, Keshu Zhang. 97-104 [doi]
- Sparse Greedy Minimax Probability Machine ClassificationThomas Strohmann, Andrei Belitski, Gregory Z. Grudic, Dennis DeCoste. 105-112 [doi]
- Sequential Bayesian Kernel RegressionJaco Vermaak, Simon J. Godsill, Arnaud Doucet. 113-120 [doi]
- Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin AlgorithmsClaudio Gentile. 121-128 [doi]
- Dynamical Modeling with Kernels for Nonlinear Time Series PredictionLiva Ralaivola, Florence d Alché-Buc. 129-136 [doi]
- Extreme Components AnalysisMax Welling, Felix V. Agakov, Christopher K. I. Williams. 137-144 [doi]
- Linear Dependent Dimensionality ReductionNathan Srebro, Tommi Jaakkola. 145-152 [doi]
- Locality Preserving ProjectionsXiaofei He, Partha Niyogi. 153-160 [doi]
- Optimal Manifold Representation of Data: An Information Theoretic ApproachDenis V. Chigirev, William Bialek. 161-168 [doi]
- Ranking on Data ManifoldsDengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf. 169-176 [doi]
- Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral ClusteringYoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet. 177-184 [doi]
- Pairwise Clustering and Graphical ModelsNoam Shental, Assaf Zomet, Tomer Hertz, Yair Weiss. 185-192 [doi]
- Tree-structured Approximations by Expectation PropagationThomas P. Minka, Yuan (Alan) Qi. 193-200 [doi]
- The IM Algorithm: A Variational Approach to Information MaximizationDavid Barber, Felix V. Agakov. 201-208 [doi]
- Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter s Implicit Sparse Hessian-Vector MultiplyEiji Mizutani, James Demmel. 209-216 [doi]
- Large Scale Online LearningLéon Bottou, Yann LeCun. 217-224 [doi]
- Online Classification on a BudgetKoby Crammer, Jaz S. Kandola, Yoram Singer. 225-232 [doi]
- Online Learning via Global Feedback for Phrase RecognitionXavier Carreras, Lluís Màrquez. 233-240 [doi]
- Sparse Representation and Its Applications in Blind Source SeparationYuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Sergei L. Shishkin, Jianting Cao, Fanji Gu. 241-248 [doi]
- Perspectives on Sparse Bayesian LearningDavid P. Wipf, Jason A. Palmer, Bhaskar D. Rao. 249-256 [doi]
- Semi-Supervised Learning with TreesCharles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum. 257-264 [doi]
- Efficient Exact k-NN and Nonparametric Classification in High DimensionsTing Liu, Andrew W. Moore, Alexander G. Gray. 265-272 [doi]
- Nonstationary Covariance Functions for Gaussian Process RegressionChristopher J. Paciorek, Mark J. Schervish. 273-280 [doi]
- Learning the k in k-meansGreg Hamerly, Charles Elkan. 281-288 [doi]
- Finding the M Most Probable Configurations in Arbitrary Graphical ModelsChen Yanover, Yair Weiss. 289-296 [doi]
- Non-linear CCA and PCA by Alignment of Local ModelsJakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis. 297-304 [doi]
- Learning Spectral ClusteringFrancis R. Bach, Michael I. Jordan. 305-312 [doi]
- AUC Optimization vs. Error Rate MinimizationCorinna Cortes, Mehryar Mohri. 313-320 [doi]
- Learning with Local and Global ConsistencyDengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf. 321-328 [doi]
- Gaussian Process Latent Variable Models for Visualisation of High Dimensional DataNeil D. Lawrence. 329-336 [doi]
- Warped Gaussian ProcessesEdward Snelson, Carl Edward Rasmussen, Zoubin Ghahramani. 337-344 [doi]
- Can We Learn to Beat the Best StockAllan Borodin, Ran El-Yaniv, Vincent Gogan. 345-352 [doi]
- Approximate Expectation MaximizationTom Heskes, Onno Zoeter, Wim Wiegerinck. 353-360 [doi]
- Linear Response for Approximate InferenceMax Welling, Yee Whye Teh. 361-368 [doi]
- Semidefinite Relaxations for Approximate Inference on Graphs with CyclesMartin J. Wainwright, Michael I. Jordan. 369-376 [doi]
- Approximability of Probability DistributionsAlina Beygelzimer, Irina Rish. 377-384 [doi]
- Denoising and Untangling Graphs Using Degree PriorsQuaid Morris, Brendan J. Frey. 385-392 [doi]
- On the Concentration of Expectation and Approximate Inference in Layered NetworksXuanLong Nguyen, Michael I. Jordan. 393-400 [doi]
- Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov ModelsRadford M. Neal, Matthew J. Beal, Sam T. Roweis. 401-408 [doi]
- Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage AnalysisPedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon M. Kleinberg. 409-416 [doi]
- Wormholes Improve Contrastive DivergenceGeoffrey E. Hinton, Max Welling, Andriy Mnih. 417-424 [doi]
- Sample PropagationMark A. Paskin. 425-432 [doi]
- Generalised Propagation for Fast Fourier Transforms with Partial or Missing DataAmos J. Storkey. 433-440 [doi]
- Laplace PropagationAlexander J. Smola, Vishy Vishwanathan, Eleazar Eskin. 441-448 [doi]
- Learning to Find Pre-ImagesGökhan H. Bakir, Jason Weston, Bernhard Schölkopf. 449-456 [doi]
- Semi-Definite Programming by Perceptron LearningThore Graepel, Ralf Herbrich, Andriy Kharechko, John Shawe-Taylor. 457-464 [doi]
- Computing Gaussian Mixture Models with EM Using Equivalence ConstraintsNoam Shental, Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall. 465-472 [doi]
- Feature Selection in Clustering ProblemsVolker Roth, Tilman Lange. 473-480 [doi]
- An Iterative Improvement Procedure for Hierarchical ClusteringDavid Kauchak, Sanjoy Dasgupta. 481-488 [doi]
- Identifying Structure across Pre-partitioned DataZvika Marx, Ido Dagan, Eli Shamir. 489-496 [doi]
- Log-Linear Models for Label RankingOfer Dekel, Christopher D. Manning, Yoram Singer. 497-504 [doi]
- Minimax EmbeddingsMatthew Brand. 505-512 [doi]
- No Unbiased Estimator of the Variance of K-Fold Cross-ValidationYoshua Bengio, Yves Grandvalet. 513-520 [doi]
- Bias-Corrected Bootstrap and Model UncertaintyHarald Steck, Tommi Jaakkola. 521-528 [doi]
- Probability Estimates for Multi-Class Classification by Pairwise CouplingTing-Fan Wu, Chih-Jen Lin, Ruby C. Weng. 529-536 [doi]
- Necessary Intransitive Likelihood-Ratio ClassifiersGang Ji, Jeff A. Bilmes. 537-544 [doi]
- Classification with Hybrid Generative/Discriminative ModelsRajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum. 545-552 [doi]
- A Model for Learning the Semantics of PicturesVictor Lavrenko, R. Manmatha, Jiwoon Jeon. 553-560 [doi]
- Algorithms for Interdependent Security GamesMichael J. Kearns, Luis E. Ortiz. 561-568 [doi]
- Fast Embedding of Sparse Similarity GraphsJohn C. Platt. 571-578 [doi]
- GPPS: A Gaussian Process Positioning System for Cellular NetworksAnton Schwaighofer, Marian Grigoras, Volker Tresp, Clemens Hoffmann. 579-586 [doi]
- An Autonomous Robotic System for Mapping Abandoned MinesDavid I. Ferguson, Aaron Morris, Dirk Hähnel, Christopher R. Baker, Zachary Omohundro, Carlos F. Reverte, Scott Thayer, Charles Whittaker, William Whittaker, Wolfram Burgard, Sebastian Thrun. 587-594 [doi]
- Semi-supervised Protein Classification Using Cluster KernelsJason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble. 595-602 [doi]
- Statistical Debugging of Sampled ProgramsAlice X. Zheng, Michael I. Jordan, Ben Liblit, Alexander Aiken. 603-610 [doi]
- Markov Models for Automated ECG Interval AnalysisNicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts. 611-618 [doi]
- Parameterized Novelty Detectors for Environmental Sensor MonitoringCynthia Archer, Todd K. Leen, António M. Baptista. 619-626 [doi]
- Modeling User Rating Profiles For Collaborative FilteringBenjamin Marlin. 627-634 [doi]
- Application of SVMs for Colour Classification and Collision Detection with AIBO RobotsMichael J. Quinlan, Stephan K. Chalup, Richard H. Middleton. 635-642 [doi]
- Kernels for Structured Natural Language DataJun Suzuki, Yutaka Sasaki, Eisaku Maeda. 643-650 [doi]
- A Fast Multi-Resolution Method for Detection of Significant Spatial Disease ClustersDaniel B. Neill, Andrew W. Moore. 651-658 [doi]
- Link Prediction in Relational DataBenjamin Taskar, Ming Fai Wong, Pieter Abbeel, Daphne Koller. 659-666 [doi]
- Unsupervised Color Decomposition Of Histologically Stained Tissue SamplesAndrew Rabinovich, Sameer Agarwal, Casey Laris, Jeffrey H. Price, Serge Belongie. 667-674 [doi]
- ICA-based Clustering of Genes from Microarray Expression DataSu-In Lee, Serafim Batzoglou. 675-682 [doi]
- Gene Expression Clustering with Functional Mixture ModelsDarya Chudova, Christopher Hart, Eric Mjolsness, Padhraic Smyth. 683-690 [doi]
- Reconstructing MEG Sources with Unknown CorrelationsManeesh Sahani, Srikantan S. Nagarajan. 693-700 [doi]
- Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time ScalesSaori C. Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto, Shigeto Yamawaki. 701-708 [doi]
- Training fMRI Classifiers to Discriminate Cognitive States across Multiple SubjectsXuerui Wang, Rebecca Hutchinson, Tom M. Mitchell. 709-716 [doi]
- Nonlinear Filtering of Electron Micrographs by Means of Support Vector RegressionRoland Vollgraf, Michael Scholz, Ian A. Meinertzhagen, Klaus Obermayer. 717-724 [doi]
- Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer InterfaceYu Zhou, Steven G. Mason, Gary E. Birch. 725-732 [doi]
- Increase Information Transfer Rates in BCI by CSP Extension to Multi-classGuido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller. 733-740 [doi]
- Subject-Independent Magnetoencephalographic Source Localization by a Multilayer PerceptronSung C. Jun, Barak A. Pearlmutter. 741-748 [doi]
- Gaussian Processes in Reinforcement LearningCarl Edward Rasmussen, Malte Kuss. 751-758 [doi]
- Applying Metric-Trees to Belief-Point POMDPsJoelle Pineau, Geoffrey J. Gordon, Sebastian Thrun. 759-766 [doi]
- ARA*: Anytime A* with Provable Bounds on Sub-OptimalityMaxim Likhachev, Geoffrey J. Gordon, Sebastian Thrun. 767-774 [doi]
- Approximate Planning in POMDPs with Macro-ActionsGeorgios Theocharous, Leslie Pack Kaelbling. 775-782 [doi]
- Envelope-based Planning in Relational MDPsNatalia Hernandez-Gardiol, Leslie Pack Kaelbling. 783-790 [doi]
- An MDP-Based Approach to Online Mechanism DesignDavid C. Parkes, Satinder P. Singh. 791-798 [doi]
- Autonomous Helicopter Flight via Reinforcement LearningAndrew Y. Ng, H. Jin Kim, Michael I. Jordan, Shankar Sastry. 799-806 [doi]
- All learning is Local: Multi-agent Learning in Global Reward GamesYu-Han Chang, Tracey Ho, Leslie Pack Kaelbling. 807-814 [doi]
- How to Combine Expert (and Novice) Advice when Actions Impact the Environment?Daniela Pucci de Farias, Nimrod Megiddo. 815-822 [doi]
- Bounded Finite State ControllersPascal Poupart, Craig Boutilier. 823-830 [doi]
- Policy Search by Dynamic ProgrammingJ. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff G. Schneider. 831-838 [doi]
- Robustness in Markov Decision Problems with Uncertain Transition MatricesArnab Nilim, Laurent El Ghaoui. 839-846 [doi]
- Approximate Policy Iteration with a Policy Language BiasAlan Fern, Sung Wook Yoon, Robert Givan. 847-854 [doi]
- A Nonlinear Predictive State RepresentationMatthew R. Rudary, Satinder P. Singh. 855-862 [doi]
- Learning Near-Pareto-Optimal Conventions in Polynomial TimeXiao Feng Wang, Tuomas Sandholm. 863-870 [doi]
- Extending Q-Learning to General Adaptive Multi-Agent SystemsGerald Tesauro. 871-878 [doi]
- Auction Mechanism Design for Multi-Robot CoordinationCurt A. Bererton, Geoffrey J. Gordon, Sebastian Thrun. 879-886 [doi]
- Distributed Optimization in Adaptive NetworksCiamac Cyrus Moallemi, Benjamin Van Roy. 887-894 [doi]
- Linear Program Approximations for Factored Continuous-State Markov Decision ProcessesMilos Hauskrecht, Branislav Kveton. 895-902 [doi]
- Insights from Machine Learning Applied to Human Visual ClassificationArnulf B. A. Graf, Felix A. Wichmann. 905-912 [doi]
- Sensory Modality SegregationVirginia R. de Sa. 913-920 [doi]
- Reasoning about Time and Knowledge in Neural Symbolic Learning SystemsArtur S. d Avila Garcez, Luís C. Lamb. 921-928 [doi]
- Learning a World Model and Planning with a Self-Organizing, Dynamic Neural SystemMarc Toussaint. 926-936 [doi]
- An MCMC-Based Method of Comparing Connectionist Models in Cognitive ScienceWoojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung. 937-944 [doi]
- Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and EffectorsDavid Philipona, J. K. O Regan, Jean-Pierre Nadal, Olivier J. M. D. Coenen. 945-952 [doi]
- From Algorithmic to Subjective RandomnessThomas L. Griffiths, Joshua B. Tenenbaum. 953-960 [doi]
- Unsupervised Context Sensitive Language Acquisition from a Large CorpusZach Solan, David Horn, Eytan Ruppin, Shimon Edelman. 961-968 [doi]
- A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot ExperimentsYuuya Sugita, Jun Tani. 969-976 [doi]
- Model Uncertainty in Classical ConditioningAaron C. Courville, Nathaniel D. Daw, Geoffrey J. Gordon, David S. Touretzky. 977-984 [doi]
- A Low-Power Analog VLSI Visual Collision DetectorReid R. Harrison. 987-994 [doi]
- A Recurrent Model of Orientation Maps with Simple and Complex CellsPaul Merolla, Kwabena Boahen. 995-1002 [doi]
- A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural SystemsRock Z. Shi, Timothy K. Horiuchi. 1003-1010 [doi]
- Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI NeuronsHsin Chen, Patrice Fleury, Alan F. Murray. 1011-1018 [doi]
- Training a Quantum Neural NetworkBob Ricks, Dan Ventura. 1019-1026 [doi]
- Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP SynapsesAdria Bofill-i-Petit, Alan F. Murray. 1027-1034 [doi]
- A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image VectorsMasakazu Yagi, Hideo Yamasaki, Tadashi Shibata. 1035-1042 [doi]
- Entrainment of Silicon Central Pattern Generators for Legged Locomotory ControlFrancesco Tenore, Ralph Etienne-Cummings, M. Anthony Lewis. 1043-1050 [doi]
- A Neuromorphic Multi-chip Model of a Disparity Selective Complex CellEric K. C. Tsang, Bertram Emil Shi. 1051-1058 [doi]
- Sparseness of Support Vector Machines---Some Asymptotically Sharp BoundsIngo Steinwart. 1069-1076 [doi]
- An Infinity-sample Theory for Multi-category Large Margin ClassificationTong Zhang. 1077-1084 [doi]
- Error Bounds for Transductive Learning via Compression and ClusteringPhilip Derbeko, Ran El-Yaniv, Ron Meir. 1085-1092 [doi]
- Online Learning of Non-stationary SequencesClaire Monteleoni, Tommi Jaakkola. 1093-1100 [doi]
- On the Dynamics of BoostingCynthia Rudin, Ingrid Daubechies, Robert E. Schapire. 1101-1108 [doi]
- Boosting versus CoveringKohei Hatano, Manfred K. Warmuth. 1109-1116 [doi]
- Near-Minimax Optimal Classification with Dyadic Classification TreesClayton Scott, Robert Nowak. 1117-1124 [doi]
- PAC-Bayesian Generic ChainingJean-Yves Audibert, Olivier Bousquet. 1125-1132 [doi]
- Self-calibrating Probability ForecastingVladimir Vovk, Glenn Shafer, Ilia Nouretdinov. 1133-1140 [doi]
- When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts?David L. Donoho, Victoria Stodden. 1141-1148 [doi]
- Learning Bounds for a Generalized Family of Bayesian Posterior DistributionsTong Zhang. 1149-1156 [doi]
- Variational Linear ResponseManfred Opper, Ole Winther. 1157-1164 [doi]
- Geometric Clustering Using the Information Bottleneck MethodSusanne Still, William Bialek, Léon Bottou. 1165-1172 [doi]
- Large Margin Classifiers: Convex Loss, Low Noise, and Convergence RatesPeter L. Bartlett, Michael I. Jordan, Jon D. McAuliffe. 1173-1180 [doi]
- Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCADavid C. Hoyle, Magnus Rattray. 1181-1188 [doi]
- Approximate Analytical Bootstrap Averages for Support Vector ClassifiersDörthe Malzahn, Manfred Opper. 1189-1196 [doi]
- Learning Curves for Stochastic Gradient Descent in Linear Feedforward NetworksJustin Werfel, Xiaohui Xie, H. Sebastian Seung. 1197-1204 [doi]
- Ambiguous Model Learning Made Unambiguous with 1/f PriorsGurinder S. Atwal, William Bialek. 1205-1212 [doi]
- Information Bottleneck for Gaussian VariablesGal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss. 1213-1220 [doi]
- Measure Based RegularizationOlivier Bousquet, Olivier Chapelle, Matthias Hein. 1221-1228 [doi]
- Online Passive-Aggressive AlgorithmsShai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer. 1229-1236 [doi]
- Margin Maximizing Loss FunctionsSaharon Rosset, Ji Zhu, Trevor Hastie. 1237-1244 [doi]
- The Doubly Balanced Network of Spiking Neurons: A Memory Model with High CapacityYuval Aviel, David Horn, Moshe Abeles. 1247-1254 [doi]
- Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking NeuronsThomas Natschläger, Wolfgang Maass. 1255-1262 [doi]
- The Diffusion-Limited Biochemical Signal-Relay ChannelPeter J. Thomas, Donald J. Spencer, Sierra K. Hampton, Peter Park, Joseph P. Zurkus. 1263-1270 [doi]
- Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working MemoryAaron J. Gruber, Peter Dayan, Boris S. Gutkin, Sara A. Solla. 1271-1278 [doi]
- Circuit Optimization Predicts Dynamic Network for Chemosensory Orientation in the Nematode C. elegansNathan A. Dunn, John S. Conery, Shawn R. Lockery. 1279-1286 [doi]
- A Biologically Plausible Algorithm for Reinforcement-shaped Representational LearningManeesh Sahani. 1287-1294 [doi]
- Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron?Yoichi Miyawaki, Masato Okada. 1295-1302 [doi]
- Plasticity Kernels and Temporal StatisticsPeter Dayan, Michael Häusser. 1303-1310 [doi]
- Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural ModelJonathan Pillow, Liam Paninski, Eero P. Simoncelli. 1311-1318 [doi]
- Design of Experiments via Information TheoryLiam Paninski. 1319-1326 [doi]
- Probabilistic Inference in Human Sensorimotor ProcessingKonrad P. Körding, Daniel M. Wolpert. 1327-1334 [doi]
- Estimating Internal Variables and Paramters of a Learning Agent by a Particle FilterKazuyuki Samejima, Kenji Doya, Yasumasa Ueda, Minoru Kimura. 1335-1342 [doi]
- Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic BiophysicsBernd Porr, Ausra Saudargiene, Florentin Wörgötter. 1343-1350 [doi]
- A Probabilistic Model of Auditory Space Representation in the Barn OwlBrian J. Fischer, Charles H. Anderson. 1351-1358 [doi]
- Decoding V1 Neuronal Activity using Particle Filtering with Volterra KernelsRyan Kelly, Tai Sing Lee. 1359-1366 [doi]
- Prediction on Spike Data Using Kernel AlgorithmsJan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf. 1367-1374 [doi]
- Phonetic Speaker Recognition with Support Vector MachinesWilliam M. Campbell, Joseph P. Campbell, Douglas A. Reynolds, Douglas A. Jones, Timothy R. Leek. 1377-1384 [doi]
- A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia ApplicationsPedro J. Moreno, Purdy Ho, Nuno Vasconcelos. 1385-1392 [doi]
- Probabilistic Inference of Speech Signals from Phaseless SpectrogramsKannan Achan, Sam T. Roweis, Brendan J. Frey. 1393-1400 [doi]
- Eigenvoice Speaker Adaptation via Composite Kernel PCAJames T. Kwok, Brian Mak, Simon Ho. 1401-1408 [doi]
- Predicting Speech Intelligibility from a Population of NeuronsJeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Haykin. 1409-1416 [doi]
- One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech SignalsTomohiro Nakatani, Masato Miyoshi, Keisuke Kinoshita. 1417-1424 [doi]
- A Classification-based Cocktail-party ProcessorNicoleta Roman, DeLiang L. Wang, Guy J. Brown. 1425-1432 [doi]
- Local Phase Coherence and the Perception of BlurZhou Wang, Eero P. Simoncelli. 1435-1442 [doi]
- Nonlinear Processing in LGN NeuronsVincent Bonin, Valerio Mante, Matteo Carandini. 1443-1450 [doi]
- A Functional Architecture for Motion Pattern Processing in MSTdScott A. Beardsley, Lucia M. Vaina. 1451-1458 [doi]
- Human and Ideal Observers for Detecting Image CurvesAlan L. Yuille, Fang Fang, Paul R. Schrater, Daniel Kersten. 1459-1466 [doi]
- Eye Movements for Reward MaximizationNathan Sprague, Dana H. Ballard. 1467-1474 [doi]
- Eye Micro-movements Improve Stimulus Detection Beyond the Nyquist Limit in the Peripheral RetinaMatthias H. Hennig, Florentin Wörgötter. 1475-1482 [doi]
- Bounded Invariance and the Formation of Place Fields.Reto Wyss, Paul F. M. J. Verschure. 1483-1490 [doi]
- Discriminating Deformable Shape ClassesSalvador Ruiz-Correa, Linda G. Shapiro, Marina Meila, Gabriel Berson. 1491-1498 [doi]
- Graphical Model For Recognizing Scenes and ObjectsKevin P. Murphy, Antonio B. Torralba, William T. Freeman. 1499-1506 [doi]
- Factorization with Uncertainty and Missing Data: Exploiting Temporal CoherenceAmit Gruber, Yair Weiss. 1507-1514 [doi]
- Mutual Boosting for Contextual InferenceMichael Fink 0002, Pietro Perona. 1515-1522 [doi]
- Learning a Rare Event Detection Cascade by Direct Feature SelectionJianxin Wu, James M. Rehg, Matthew D. Mullin. 1523-1530 [doi]
- Discriminative Fields for Modeling Spatial Dependencies in Natural ImagesSanjiv Kumar, Martial Hebert. 1531-1538 [doi]
- Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief PropagationLeonid Sigal, Michael Isard, Benjamin H. Sigelman, Michael J. Black. 1539-1546 [doi]
- Automatic Annotation of Everyday MovementsDeva Ramanan, David A. Forsyth. 1547-1554 [doi]
- Learning Non-Rigid 3D Shape from 2D MotionLorenzo Torresani, Aaron Hertzmann, Christoph Bregler. 1555-1562 [doi]
- Towards Social Robots: Automatic Evaluation of Human-robot Interaction by Face Detection and Expression ClassificationGwen Littlewort, Marian Stewart Bartlett, Ian R. Fasel, Joel Chenu, Takayuki Kanda, Hiroshi Ishiguro, Javier R. Movellan. 1563-1570 [doi]
- Salient Boundary Detection using Ratio ContourSong Wang, Toshiro Kubota, Jeffrey Mark Siskind. 1571-1578 [doi]
- A Computational Geometric Approach to Shape Analysis in ImagesAnuj Srivastava, Xiuwen Liu, Washington Mio, Eric Klassen. 1579-1586 [doi]
- A Sampled Texture Prior for Image Super-ResolutionLyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman. 1587-1594 [doi]
- Bayesian Color Constancy with Non-Gaussian ModelsCharles R. Rosenberg, Thomas P. Minka, Alok Ladsariya. 1595-1602 [doi]
- An Improved Scheme for Detection and Labelling in Johansson DisplaysClaudio Fanti, Marzia Polito, Pietro Perona. 1603-1610 [doi]