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Posters

 

Monday, December 13 -- Tuesday, December 14 --

Wednesday, December 15, 2004

 

7:30 pm – 12:00 midnight

 

The Poster Sessions, will take place on three evenings during the Conference, and will offer high-quality posters and an opportunity for researchers to share their work and exchange ideas in an collegial setting.  The majority of contributions accepted at NIPS are presented as posters.

 

 

Posters Sessions

 

Monday, December 13 -- Poster Layout   Download Printable Poster Layout in PDF

  1. The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees -- Shai Shalev-Shwartz, Ofer Dekel, Yoram Singer
  2. Variational Minimax Estimation of Discrete Distributions under KL Loss -- Liam Paninski
  3. Semi-supervised Learning via Gaussian Processes -- Neil Lawrence, Michael Jordan
  4. On Semi-Supervised Classification -- Balaji Krishnapuram, David Williams, Ya Xue, Alexander Hartemink, Lawrence Carin, Mario Figueiredo
  5. Joint Probabilistic Curve Clustering and Alignment -- Scott Gaffney, Padhraic Smyth
  6. Class-size Independent Generalization Analsysis of Some Discriminative Multi-Category Classification -- Tong Zhang
  7. Matrix Exponential Updates for On-line Learning and Bregman Projection -- Manfred Warmuth, Koji Tsuda, Gunnar Raetsch
  8. Generalization Error and Algorithmic Convergence of Median Boosting -- Balazs Kegl
  9. The Convergence of Contrastive Divergences -- Alan Yuille
  10. Outlier Detection with One-class Kernel Fisher Discriminants -- Volker Roth
  11. A Direct Formulation for Sparse PCA Using Semidefinite Programming -- Gert Lanckriet, Alexandre d'Aspremont, Laurent El Ghaoui, Michael Jordan
  12. Semi-parametric Exponential Family PCA -- Sajama Sajama, Alon Orlitsky
  13. A Second Order Cone Programming Formulation for Classifying Missing Data -- Chiranjib Bhattacharyya, K. S. Pannagadatta, Alex Smola
  14. Efficient Kernel Discriminant Analysis via QR Decomposition -- Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladimir Cherkassky
  15. Learning, Regularization and Ill-Posed Inverse Problems -- Rosasco Lorenzo, Caponnetto Andrea, De Vito Ernesto, Odone Francesca, De Giovannini Umberto
  16. Incremental Algorithms for Hierarchical Classification -- Nicolo Cesa-Bianchi, Claudio Gentile, Andrea Tironi, Luca Zaniboni
  17. Computing Regularization Paths for Learning Multiple Kernels -- Francis Bach, Romain Thibaux, Michael Jordan
  18. Tracking Curved Regularized Optimization Solution Paths -- Saharon Rosset
  19. Semi-supervised Learning on Directed Graphs -- Dengyong Zhou, Bernhard Schoelkopf, Thomas Hofmann
  20. A Topographic Support Vector Machine: Classification Using Local Label Configurations -- Johannes Mohr, Klaus Obermayer
  21. The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space -- Robert Jenssen, Deniz Erdogmus, Jose Principe, Torbjorn Eltoft
  22. Instance-Specific Bayesian Model Averaging for Classification -- Shyam Visweswaran, Gregory Cooper
  23. Optimal Sub-graphical Models -- Mukund Narasimhan, Jeff Bilmes
  24. Newscast EM -- Wojtek Kowalczyk, Nikos Vlassis
  25. Conditional Models of Identity Uncertainty with Application to Noun Coreference -- Andrew McCallum, Ben Wellner
  26. Probabilistic Inference of Alternative Splicing Events in Microarray Data -- Ofer Shai, Brendan Frey, Quaid Morris, Sandy Pan, Christine Misquitta, Benjamin Blencowe
  27. Markov Networks for Detecting Overalpping Elements in Sequence Data -- Joseph Bockhorst, Mark Craven
  28. Identifying Protein-protein Interaction Sites on a Genome-wide Scale -- Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koller, Douglas Brutlag
  29. Discrete Profile Alignment via Constrained Information Bottleneck -- Sean O'Rourke, Gal Chechik, Robin Friedman, Eskin Eleazar
  30. Generative Affine Localisation and Tracking -- John Winn, Andrew Blake
  31. Adaptive Discriminative Generative Model and Its Applications -- Ruei-Sung Lin, David Ross, Jongwoo Lim, Ming-Hsuan Yang
  32. Learning Hyper-Features for Visual Identification -- Andras Ferencz, Erik Learned-Miller, Jitendra Malik
  33. Face Detection, Efficient and Rank Deficient -- Wolf Kienzle, Gokhan BakIr, Matthias Franz, Bernhard Scholkopf
  34. Fast Object Rejection Using Image Segments -- Shai Avidan, Moshe Butman
  35. Efficient Out-of-Sample Extension of Dominant-set Clusters -- Massimiliano Pavan, Marcello Pelillo
  36. Surface Reconstruction Using Learned Shape Models -- Jan Erik Solem, Fredrik Kahl
  37. Common-Frame Model for Object Recognition -- Pierre Moreels, Pietro Perona
  38. The Cerebellum Chip -- Constanze Hofstoetter, Manuel Gil, Kynan Eng, Giacomo Indiveri, Matti Mintz, Joerg Kramer, Paul Verschure
  39. Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid -- Felix Schuermann, Karlheinz Meier, Johannes Schemmel
  40. On-Chip Compensation of Device-Mismatch Effects in Analog VLSI Neural Networks -- Miguel Figueroa, Seth Bridges, Chris Diorio
  41. Mass Meta-analysis in Talairach Space -- Finn Nielsen
  42. Detecting Significant Multidimensional Spatial Clusters -- Daniel Neill, Andrew Moore, Francisco Pereira, Tom Mitchell
  43. Sparse Coding of Natural Image Using an Overcomplete Set of Limited Capacity Units -- Doi Eizaburo, Michael Lewicki
  44. At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks -- Nils Bertschinger, Thomas Natschlaeger, Robert Legenstein
  45. Assignment of Multiplicative Mixtures in Natural Images -- Odelia Schwartz, Terrence Sejnowski, Peter Dayan
  46. Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis -- Tobias Blaschke, Laurenz Wiskott
  47. Linear Multilayer Independent Component Analysis for Large Natural Scenes -- Yoshitatsu Matsuda, Kazunori Yamaguchi
  48. Optimal Information Decoding from Neuronal Populations with Specific Stimulus selectivity -- Marcelo Montemurro, Stefano Panzeri
  49. Constraining a Bayesian Model of Human Visual Speed Perception -- Alan Stocker, Eero Simoncelli
  50. Implicit Wiener Series for Higher-order Image Analysis Matthias Franz, Bernhard Scholkopf
  51. Hierarchical Dirichlet Processes -- Yee Whye Teh, Michael Jordan, Matthew J. Beal, David Blei
  52. Mistake Bounds for Maximum Entropy Discrimination -- Phil Long, Xinyu Wu
  53. Experts in a Markov Decision Process -- Sham Kakade, Even-Dar Eyal, Yishay Mansour
  54. Nearly Tight Bounds for the Continuum-Armed Bandit Problem -- Robert Kleinberg
  55. Coarticulation in Markov Decision Processes -- Khashayar Rohanimanesh, Robert Platt, Sridhar Mahadevan, Roderic Grupen
  56. Convergence and No-Regret in Multiagent Learning -- Bowling Michael
  57. Intrinsically Motivated Reinforcement Learning -- Satinder Singh, Andrew G. Barto, Nuttapong Chentanez
  58. A Cost-Shaping LP for Bellman Error Minimization with Performance Guarantees -- Daniela Pucci de Farias, Benjamin Van Roy
  59. Resolving Perceptual Aliasing With Noisy Sensors -- Guy Shani, Ronen Brafman
  60. Exploration-Exploitation Tradeoffs for Experts Algorithms in Reactive Environments -- Daniela Pucci de Farias, Nimrod Megiddo
  61. Solitaire: Man Versus Machine -- Xiang Yan, Persi Diaconis, Paat Rusmevichientong, Benjamin Van Roy
  62. Multi-agent Cooperation in Diverse Population Games -- Kwok Yee Wong, Sze Wah Lim, Zhuo Gao
  63. VDCBPI: an Approximate Scalable Algorithm for Large Scale POMDPs -- Pascal Poupart, Craig Boutilier
  64. Brain Inspired Reinforcement Learning -- Francois Rivest, Yoshua Bengio, John Kalaska
  65. Planning for Markov Decision Processes with Sparse Stochasticity -- Maxim Likhachev, Geoff Gordon, Sebastian Thrun

Tuesday, December 14 – Poster Layout    Download Printable Poster Layout in PDF

  1. Theories Of Access Consciousness -- Michael Colagrosso, Michael Mozer
  2. Learning Syntactic Patterns for Automatic Hypernym Discovery -- Rion Snow, Daniel Jurafsky, Andrew Ng
  3. The Rescorla-Wagner Algorithm and Maximum Likelihood Estimation of Causal Parameters -- Alan Yuille
  4. Responding to Modalities with Different Latencies -- Fredrik Bissmarck, Hiroyuki Nakahara, Kenji Doya, Okihide Hikosaka
  5. Heuristics for Ordering Cue Search in Decision Making -- Peter Todd, Anja Dieckmann
  6. Machine Learning Applied to Perception: Decision Images for Classification -- Felix Wichmann, Arnulf Graf, Eero Simoncelli, Heinrich Bulthoff, Bernhard Schoelkopf
  7. Sampling Methods for Unsupervised Learning -- Robert Fergus, Pietro Perona, Andrew Zisserman
  8. Co-Validation: Using Model Disagreement to Validate Classification Algorithms -- Omid Madani, David Pennock, Gary Flake
  9. Self-Tuning Spectral Clustering -- Lihi Zelnik-Manor, Pietro Perona
  10. Penalized Probabilistic Clustering -- Zhengdong Lu, Todd Leen
  11. Metric Nearness: Problem Formulation and Algorithms -- Suvrit Sra, Inderjit Dhillon, Joel Tropp
  12. Proximity Graphs for Clustering and Manifold Learning -- Miguel Carreira-Perpinan, Richard Zemel
  13. Hierarchical Eigensolver for Transition Matrices in Spectral Methods -- Chakra Chennubhotla, Allan Jepson
  14. Adaptive Manifold Learning -- Jing Wang, Zhenyue Zhang, Hongyuan Zha
  15. A Machine Learning Approach to Conjoint Analysis -- Olivier Chapelle, Zaid Harchaoui
  16. Non-Local Manifold Tangent Learning -- Yoshua Bengio, Martin Monperrus
  17. Result Analysis of the NIPS 2003 Feature Selection Challenge -- Isabelle Guyon, Steve Gunn, Asa Ben Hur, Gideon Dror
  18. A Feature Selection Algorithm Based on the Global Minimization of a Generalization Error Bound -- Dori Peleg, Ron Meir
  19. Kernel Methods for Implicit Surface Modeling -- Bernhard Schoelkopf, Joachim Giesen, Simon Spalinger
  20. L-zero-norm Minimization for Basis Selection -- David Wipf, Bhaskar Rao
  21. Chemosensory Processing in a Spiking Model of the Olfactory Bulb -- Baranidharan Raman, Ricardo Gutierrez-Osuna
  22. Multiple Alignment of Continuous Time Series -- Jennifer Listgarten, Radford Neal, Sam Roweis, Andrew Emili
  23. A Harmonic Excitation State-space Approach to Blind Separation of Speech -- Rasmus Olsson, Lars Kai Hansen
  24. Bayesian Regularization and Nonnegative Deconvolution for Time Delay Estimation -- Lin Yuanqing, Daniel Lee
  25. Modeling Conversational Dynamics as a Mixed-Memory Markov Process -- Tanzeem Choudhury, Sumit Basu
  26. Unsupervised Variational Bayesian Learning of Nonlinear Models -- Antti Honkela, Harri Valpola
  27. Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization -- Fei Sha, Lawrence Saul
  28. Blind one-microphone speech separation: A spectral learning approach Francis Bach, Michael Jordan
  29. Dependent Gaussian Processes -- Phillip Boyle, Marcus Frean
  30. Distributed Information Regularization on Graphs -- Adrian Corduneanu, Tommi Jaakkola
  31. Maximum Margin Clustering Linli Xu, James Neufeld, Bryce Larson, Dale Schuurmans
  32. Breaking SVM Complexity with Cross-Training Gokhan BakIr, Leon Bottou, Jason Weston
  33. An Application of Boosting to Graph Classification Taku Kudo, Eisaku Maeda, Yuji Matsumoto
  34. Validity Estimates for Loopy Belief Propagation on Binary Real-world Networks -- Joris Mooij, Hilbert Kappen
  35. A Generalized Bradley-Terry Model: From Group Competition to Individual Skill -- Tzu-Kuo Huang, Chih-Jen Lin, Ruby Weng
  36. A Probabilistic Model for Online Document Clustering with Application to Novelty Detection -- Jian Zhang, Zoubin Ghahramani, Yiming Yang
  37. Hierarchical Bayesian Modelling with Gaussian Processes -- Anton Schwaighofer, Volker Tresp, Kai Yu
  38. An Information Maximization Model of Eye Movements -- L. Renninger, J. Coughlan, P. Verghese, J. Malik
  39. Similarity and Discrimination in Classical Conditioning: A Latent Variable Account -- A. Courville, N. Daw, D. Touretzky
  40. Approximately Efficient Online Mechanism Design -- D. Parkes, S. Singh, D. Yanovsky
  41. Stable Adaptive Control with Online Learning -- A. Ng, H. Kim
  42. TD Networks -- R. Sutton, B. Tanner
  43. Integrating Topics and Syntax -- T. Griffiths, M. Steyvers, D. Blei, J. Tenenbaum
  44. Economic Properties of Social Networks -- S. Kakade, M. Kearns, L. Ortiz, R. Pemantle, S. Suri
  45. Object Classification from a Single Example Utilizing Class Relevance Pseudo-Metrics -- M. Fink
  46. Schema Learning: Experience-Based Construction of Predictive Action Models -- M. Holmes, C. Isbell
  47. New Criteria and a New Algorithm for Learning in Multi-agent Systems -- R. Powers, S. Yoav
  48. Learning First Order Markov Models for Control -- P. Abbeel, A. Ng
  49. Maximum-Margin Matrix Factorization -- N. Srebro, J. Rennie, T. Jaakkola
  50. Parametric Embedding for Class Visualization -- S. Stromsten, T. Iwata, K. Saito, N. Ueda, T. Griffiths, J. Tenenbaum
  51. Euclidean Embedding of Co-occurrence Data -- A. Globerson, G. Chechik, F. Pereira, N. Tishby
  52. Limits of Spectral Clustering -- U. von Luxburg, O. Bousquet, M. Belkin
  53. Anomaly Dectection is Classification -- I. Steinwart, D. Hush, C. Scovel
  54. Active Learning for Anomaly and Rare-Category Detection -- D. Pelleg, A. Moore
  55. Maximum Likelihood Estimation of Intrinsic Dimension -- E. Levina, P. Bickel
  56. Multiple Relational Embedding -- R. Memisevic, G. Hinton
  57. Hierarchical Clustering of a Mixture Model -- J. Goldberger, S. Roweis
  58. An Investigation of Practical Approximate Nearest Neighbor Algorithms -- T. Liu, A. Moore, A. Gray, K. Yang
  59. Two-dimensional Linear Discriminant Analysis -- J. Ye, R. Janardan, Q. Li
  60. Harmonising Chorales by Probabilistic Inference -- M. Allan, C. Williams
  61. Using Random Forests in the Structured Language Model -- P. Xu, F. Jelinek
  62. Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation -- E. Sudderth, M. Mandel, W. Freeman, A. Willsky
  63. Contextual models for object detection using boosted random fields -- A. Torralba, K. Murphy, W. Freeman
  64. Expectation Consistent Free Energies for Approximate Inference -- M. Opper, O. Winther
  65. Comparing Beliefs, Surveys, and Random Walks -- S. Kirkpatrick, E. Aurell, U. Gordon
  66. A Hidden Markov Model for de Novo Peptide Sequencing -- B. Fischer, V. Roth, J. Buhmann, J. Grossmann, S. Baginsky, W. Gruissem, F. Roos, P. Widmayer
  67. Large-Scale Prediction of Disulphide Bond Connectivity -- P. Baldi, J. Cheng, A. Vullo
  68. Beat Tracking the Graphical Model Way -- D. Lang, N. de Freitas
  69. Hierarchical Distributed Representations for Statistical Language Modeling -- J. Blitzer, K. Weinberger, L. Saul, F. Pereira
  70. Exponentiated Gradient Algorithms for Large-margin Structured Classification -- P. Bartlett, M. Collins, B. Taskar, D. McAllester

Wednesday, December 15 – Poster Layout     Download Printable Poster Layout in PDF

  1. Synergistic Face Detection and Pose Estimation with Energy-Based Models Models -- Margarita Osadchy, Mathew Miller, Yann LeCun
  2. Making Latin Manuscripts Searchable using gHMM's -- Jaety Edwards, Yee Whye Teh, David Forsyth, Roger Bock, Michael Maire, Grace Vesom
  3. Incremental Learning for Visual Tracking -- Jongwoo Lim, David Ross, Ruei-Sung Lin, Ming-Hsuan Yang
  4. A Three Tiered Approach for Articulated Object Action Modeling and Recognition -- Le Lu, Gregory Hager
  5. Conditional Random Fields for Object Recognition -- Ariadna Quattoni, Michael Collins, Trevor Darrell
  6. Semi-Markov Conditional Random Fields for Information Extraction -- Sunita Sarawagi, William Cohen
  7. Instance-Based Relevance Feedback for Image Retrieval -- Giacinto Giorgio, Fabio Roli
  8. Pictorial Structures for Molecular Modeling: Interpreting Density Maps -- Frank DiMaio, Jude Shavlik, George Phillips
  9. Joint Tracking of Pose, Expression, and Texture -- Tim Marks, John Hershey, Javier R. Movellan, Cooper Roddey
  10. The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces -- Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung Pang, Daphne Koller, Sebastian Thrun, James Davis
  11. Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model -- Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner
  12. Spike Sorting: Bayesian Clustering of Non-Stationary Data -- Aharon Bar-Hillel, Adam Spiro, Eran Stark
  13. Dynamic Bayesian Networks for Brain-Computer Interfaces -- Pradeep Shenoy, Rajesh Rao
  14. Hierarchical Bayesian Inference in Networks of Spiking Neurons -- Rajesh Rao
  15. Theory of Localized Synfire Chain: Characteristic Propagation Speed of Stable Spike Pattern -- Hamaguchi Kosuke, Masato Okada, Kazuyuki Aihara
  16. Probabilistic Computation in Spiking Neurons -- Richard Zemel, Quentin Huys, Rama Natarajan, Peter Dayan
  17. Bayesian Inference in Spiking Neurons -- Sophie Deneve
  18. Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity -- Sander Bohte, Michael Mozer
  19. Maximising Information Yields Spike Timing Dependent Plasticity -- Anthony Bell, Lucas Parra
  20. Rate and Phase-coded Autoassociative Memory -- M. Lengyel, P. Dayan
  21. Methods Towards Invasive Human Brain Computer Interfaces -- Thomas Lal, Thilo Hinterberger, Guido Widman, Michael Schroeder, Jeremy Hill, Wolfgang Rosenstiel, Christian Elger, Bernhard Scholkopf, Niels Birbaumer
  22. An Auditory Paradigm for Brain-Computer Interfaces -- Jeremy Hill, Thomas Lal, Karin Bierig, Niels Birbaumer, Bernhard Scholkopf
  23. Threading Kernel Functions: on Bridging the Gap between Representations and Algorithms -- Amnon Shashua, Tamir Hazan
  24. Binet-Cauchy Kernels -- Vishwanathan S V N, Alex Smola
  25. Generalization Error Bounds for Collaborative Prediction with Low-Rank Matrices -- Nathan Srebro, Noga Alon, Tommi Jaakkola
  26. Parallel Support Vector Machines: The Cascade SVM -- Hans Peter Graf, Eric Cosatto, Leon Bottou, Igor Durdanovic
  27. Neighbourhood Components Analysis -- Jacob Goldberger, Sam Roweis, Geoffrey Hinton, Ruslan Salakhutdinov
  28. Maximal Margin Labeling for Multi-Topic Text Categorization -- Hideto Kazawa, Tomonori Izumitani, Hirotoshi Taira, Eisaku Maeda
  29. Support Vector Classification with Input Data Uncertainty -- Jinbo Bi, Tong Zhang
  30. Boosting on Manifolds: Adaptive Regularization of Base Classifiers -- Balazs Kegl, Ligen Wang
  31. Semi-supervised Learning by Entropy Minimization -- Yves Grandvalet, Yoshua Bengio
  32. Semi-Supervised Kernels via Convex Optimization with Order Constraints -- Xiaojin Zhu, Jaz Kandola, Zoubin Ghahramani, John Lafferty
  33. Fast Rates to Bayes for Kernel Machines -- Ingo Steinwart, Clint Scovel
  34. PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data -- Mario Marchand, Mohak Shah
  35. Using the Equivalent Kernel to Understand Gaussian Process Regression -- Peter Sollich, Chris Williams
  36. Analysis of a Greedy Active Learning Strategy -- Sanjoy Dasgupta
  37. Learning Preferences for Multiclass Problems -- Fabio Aiolli, Alessandro Sperduti
  38. Kernel Projection Machine: a New Tool for Pattern Recognition -- Laurent Zwald, regis vert, Pascal Massart, Gilles Blanchard
  39. A Large Deviation Bound for the Area Under an ROC Curve -- Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan Roth
  40. A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning -- Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie
  41. Discriminant Saliency for Visual Recognition from Cluttered Scenes -- D. Gao, N. Vasconcelos
  42. Who's in the Picture? -- T. Berg, A. Berg, J. Edwards, D. Forsyth
  43. Joint MRI Bias Removal Using Entropy Minimization Across Images -- E. Learned-Miller, P. Ahammad
  44. Saliency-Driven Image Acuity Modulation on a Reconfigurable Silicon Array of Spiking Neurons -- R. Vogelstein, U. Mallik, G. Cauwenberghs, E. Culurciello, R. Etienne-Cummings
  45. Seeing through Water -- A. Efros, V. Isler, J. Shi, M. Visontai
  46. The Variational Ising Classifier (VIC) Algorithm for Coherently Contaminated Data -- O. Williams, A. Blake, R. Cipolla
  47. Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) -- K. Chellapilla, P. Simard
  48. Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation -- C. Shantanu, G. Cauwenberghs
  49. Supervised Graph Inference -- J. Vert, Y. Yamanishi
  50. The Entire Regularization Path for the Support Vector Machine -- T. Hastie, S. Rosset, R. Tibshirani, J. Zhu
  51. Kernels for Multi--task Learning -- M. Pontil, C. Micchelli
  52. Semigroup Kernels on Finite Sets -- M. Cuturi, J. Vert
  53. Efficient Kernel Machines Using the Improved Fast Gauss Transform -- C. Yang, R. Duraiswami, L. Davis
  54. Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM -- J. Del Coz, G. Bayo'n, J. Di'ez, O. Luaces, A. Bahamonde, C. San~udo
  55. Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons -- J. Triesch
  56. Learning Efficient Auditory Codes Using Spikes -- E. Smith, M. Lewicki
  57. Inference, Attention, and Decision in a Bayesian Neural Architecture -- A. Yu, P. Dayan
  58. Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits -- W. Maass, R. Legenstein, N. Bertschinger
  59. Neural Network Computation by in vitro Transcriptional Circuits -- J. Kim, J. Hopfield, E. Winfree
  60. A Temporal Kernel-Based Model for Tracking Hand-Movements from Neural Activities -- L. Shpigelman, K. Crammer, R. Paz, E. Vaadia, Y. Singer
  61. Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution -- H. Park, T. Lee
  62. Synchronization of Neural Networks by Mutual Learning and Its Application to Cryptography -- E. Klein, R. Mislovaty, I. Kanter, A. Ruttor, W. Kinzel
  63. Optimal Aggregation of Classifiers and Boosting -- V. Koltchinskii, M. Martinez-Ramon, S. Posse
  64. Co-Training and Expansion: Towards Bridging Theory and Practice -- M. Balcan, A. Blum, K. Yang
  65. Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning -- L. Paninski
  66. Online Bounds for Bayesian Algorithms -- S. Kakade, A. Ng
  67. Confidence Intervals for the Area Under the ROC Curve -- C. Cortes, M. Mohri
  68. On the Adaptive Properties of Decision Trees -- C. Scott, R. Nowak
  69. Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms -- L. Zaniboni, N. Cesa-Bianchi, C. gentile
  70. Modelling Uncertainty in the Game of Go -- D. Stern, T. Graepel, D. MacKay
  71. Message Errors in Belief Propagation -- A. Ihler, J. Fisher, A. Willsky
  72. Exponential Family Harmoniums with an Application to Information Retrieval -- M. Welling, M. Rosen-Zvi, G. Hinton