Poster
Sessions
Tuesday, December 9
and
Wednesday, December 10, 2003
7:30 pm –
12:00 midnight
The Poster Sessions, which take place on two evenings
during
the Conference, 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.
TUESDAY – December 9,
2003
AA 01
Alexander T. Ihler, Erik B. Sudderth, William T.
Freeman, Alan S. Willsky
Efficient Multiscale Sampling from Products of Gaussian Mixtures
AA 02
Mark Girolami, Ata Kaban
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
AA 03
David M. Blei, Thomas L. Griffiths, Michael I.
Jordan,
Joshua B. Tenenbaum
Hierarchical Topic Models and the Nested Chinese Restaurant Process
AA 04
Ben Taskar, Carlos Guestrin, Daphne
Koller
Max-Margin Markov Networks
AA 05
Thore Graepel, Ralf
Herbrich
Invariant Pattern Recognition by Semidefinite Programming Machines
AA 06
Matthew Schultz, Thorsten
Joachims
Learning a Distance Metric from Relative Comparison
AA 07
Ji Zhu, Saharon Rosset, Trevor Hastie, Rob
Tibshirani
1-norm Support Vector
Machines
AA 08
Koji Tsuda, Gunnar Ratsch
Image Reconstruction by Linear Programming
AA 09
Stuart Andrews, Thomas
Hofmann
Disjunctive Programming Boosting
AA 10
Tijl De Bie, Nello
Cristianini
Convex Methods for Transduction
AA 11
Kenji Fukumizu, Francis R. Bach, Michael I.
Jordan
Kernel Dimensionality Reduction for Supervised Learning
AA 12
Bernd Fischer, Volker Roth, Joachim M.
Buhmann
Clustering with the Connectivity Kernel
AA 13
Haifeng Li, Tao Jiang, Keshu
Zhang
Efficient and Robust Feature Extraction by Maximum Margin Criterion
AA 14
Thomas R. Strohmann, Andrei Belitski, Gregory Z.
Grudic,
Dennis DeCoste
Sparse Greedy Minimax Probability Machine Classification
AA 15
Jaco Vermaak, Simon J. Godsill, Arnaud
Doucet
Sequential Bayesian Kernel Regression
AA 16
Claudio Gentile
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms
AA 17
Liva Ralaivola, Florence
d'Alche-Buc,
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
AA 18
Max Welling, Felix Agakov, Christopher K. I.
Williams
Extreme Components Analysis
AA 19
Nathan Srebro, Tommi
Jaakkola
Linear Dependent Dimensionality Reduction
AA 20
Xiaofei He, Partha Niyogi
Locality Preserving Projections
AA 21
Denis V. Chigirev, William S.
Bialek
Optimal Manifold Representation of Data: An Information Theoretic Approach
AA 22
Dengyong Zhou, Jason Weston, Arthur Gretton,
Olivier
Bousquet, Bernhard Schölkopf
Ranking on Data Manifolds
AA 23
Yoshua Bengio, Jean-Francois Paiement, Pascal
Vincent
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering
AA 24
Noam Shental, Assaf Zomet, Tomer Hertz, Yair
Weiss
Pairwise Clustering and Graphical Models
AA 25
Thomas Minka, Yuan Qi
Tree-structured Approximations by Expectation Propagation
AA 26
David Barber, Felix Agakov
Information Maximization in Noisy Channels : A Variational Approach
AA 27
Eiji Mizutani, James W.
Demmel
Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian
AA 28
Leon Bottou, Yann LeCun
Large Scale Online Learning
AA 29
Koby Crammer, Jaz Kandola, Yoram
Singer
Online Classification on a Budget
AA 30
Xavier Carreras, Lluis
Marquez
Online Learning with Global Feedback for Phrase Recognition
AA 31
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari,
Sergei
Shishkin, Jianting Cao, Fanji Gu
Sparse Representation and Its Applications in Blind Source Separation
AA 32
David Wipf, Bhaskar Rao
Perspectives on Sparse Bayesian Learning
AA 33
Charles C. Kemp, Thomas L. Griffiths, Sean
Stromsten,
Joshua B. Tenenbaum
Semi-Supervised Learning with Trees
AA 34
Ting Liu, Andrew W. Moore, Alex
Gray
New Algorithms for Efficient High Dimensional Non-parametric Classification
AA 35
Christopher J. Paciorek, Mark J.
Schervish
Nonstationary Covariance Functions for Gaussian Process Regression
AA 36
Gregory Hamerly, Charles
Elkan
Learning the k in k-means
AP 01
John C. Platt
Fast Embedding of Sparse Similarity Graphs
AP 02
Anton Schwaighofer, Marian Grigoras, Volker
Tresp, Clemens Hoffmann
GPPS: A Gaussian Process Positioning System for Cellular Networks
AP 03
David Ferguson, Aaron Morris, Dirk Haehnel,
Christopher
Baker, Zachary Omohundro, Carlos Reverte, Scott Thayer, Charles
Whittaker,
William Whittaker, Wolfram Burgard, Sebastian
Thrun
An Autonomous Robotic System for Mapping Abandoned Mines
AP 04
Jason Weston, Christina Leslie, Dengyong Zhou,
Andre
Elisseeff, William S. Noble
Semi-supervised Protein Classification Using Cluster Kernels
AP 05
Alice X. Zheng, Michael I. Jordan, Ben Liblit,
Alex
Aiken
Statistical Debugging of Sampled Programs
AP 06
Nicholas P. Hughes, Lionel Tarassenko, Stephen J.
Roberts
Markov Models for Automated ECG Interval Analysis
AP 07
Cynthia Archer, Todd K. Leen, Antonio
Baptista
Parameterized Novelty Detection for Environmental Sensor Monitoring
AP 08
Benjamin Marlin
Modeling User Rating Profiles For Collaborative Filtering
AP 09
Michael J. Quinlan, Stephan K. Chalup, Richard H.
Middleton
Application of SVMs for Colour Classification and Collision Detection with AIBO Robots
AP 10
Jun Suzuki, Yutaka Sasaki, Eisaku
Maeda
Kernels for Structured Natural Language Data
CN 01
Carl E. Rasmussen, Malte
Kuss
Gaussian Processes in Reinforcement Learning
CN 02
Joelle Pineau, Geoff Gordon, Sebastian
Thrun
Applying Metric-Trees to Belief-Point POMDPs
CN 03
Maxim Likhachev, Geoff Gordon, Sebastian
Thrun
ARA*: Anytime A* with Provable Bounds on Sub-Optimality
CN 04
Georgios Theocharous, Leslie Pack
Kaelbling
Approximate Planning in POMDPs with Macro-Actions
CN 05
Natalia H. Gardiol, Leslie Pack
Kaelbling
Envelope-based Planning in Relational MDPs
CN 06
David C. Parkes, Satinder
Singh
An MDP-Based Approach to Online Mechanism Design
CN 07
Andrew Y. Ng, H. Jin Kim, Michael I. Jordan,
Shankar
Sastry
Autonomous Helicopter Flight via Reinforcement Learning
CS 01
Arnulf B. A. Graf, Felix A.
Wichmann
Insights from Machine Learning Applied to Human Visual Classification
CS 02
Virginia R. de Sa
Sensory Modality Segregation
CS 03
Artur S. d'Avila Garcez, Luis C.
Lamb
Reasoning about Time and Knowledge in Neural-Symbolic Learning Systems
CS 04
Marc Toussaint
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
ET 01
Reid R. Harrison
A Low-Power Analog VLSI Visual Collision Detector
ET 02
Paul Merolla, Kwabena
Boahen
A Recurrent Model of Orientation Maps with Simple and Complex Cells
ET 03
Rock Z. Shi, Timothy
Horiuchi
A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems
ET 04
Hsin Chen, Patrice Fleury, Alan F.
Murray
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons
ET 05
Bob Ricks, Dan Ventura
Training a Quantum Neural Network
LT 01
Ingo Steinwart
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
LT 02
Tong Zhang
An Infinity-sample Theory for Multi-category Large Margin Classification
LT 03
Philip Derbeko, Ran El-Yaniv, Ron
Meir
Error Bounds for Transductive Learning via Compression and Clustering
LT 04
Claire Monteleoni, Tommi
Jaakkola
Online Learning of Non-stationary Sequences
LT 05
Cynthia Rudin, Ingrid Daubechies, Robert E.
Schapire
On the Dynamics of Boosting
LT 06
Kohei Hatano, Manfred K.
Warmuth
Boosting versus Covering
LT 07
Clayton Scott, Robert Nowak
Near-Minimax Optimal Classification with Dyadic Classification Trees
LT 08
Jean-Yves Audibert, Olivier
Bousquet
PAC-Bayesian Generic Chaining
LT 09
Vladimir Vovk, Glenn Shafer, Ilia
Nouretdinov
Self-calibrating Probability Forecasting
NS 01
Yuval Aviel, David Horn
The Doubly Balanced Network of Spiking Neurons: a Memory Model with High Capacity
NS 02
Thomas Natschlaeger, Wolfgang Maass
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons
NS 03
Peter J. Thomas, Donald J. Spencer, Sierra K.
Hampton,
Peter Park, Joseph P. Zurkus
The Diffusion-Limited Biochemical Signal-Relay Channel
NS 04
Aaron J. Gruber, Peter Dayan, Boris S. Gutkin,
Sara A.
Solla
Dopamine Modulation in a Basal Ganglio-Cortical Network of Working Memory
NS 05
Nathan A. Dunn, John S. Conery, Shawn R.
Lockery
Circuit Optimization Predicts Dynamic Network for Chemosensory Orientation in C. elegans
NS 06
Maneesh Sahani
A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning
NS 07
Yoichi Miyawaki, Masato
Okada
Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron?
SP 01
William M. Campbell, Joseph P. Campbell, Douglas
A.
Reynolds, Douglas A. Jones, Timothy R. Leek
Phonetic Speaker Recognition with Support Vector Machines
SP 02
Pedro J. Moreno, Purdy P. Ho, Nuno
Vasconcelos
A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications
SP 03
Kannan Achan, Sam T. Roweis, Brendan J.
Frey
Probabilistic Inference of Speech Signals from Phaseless Spectrograms
SP 04
James Kwok, Brian Mak, Simon
Ho
Eigenvoice Speaker Adaptation via Composite Kernel Principal Component Analysis
VB 01
Zhou Wang, Eero P.
Simoncelli
Local Phase Coherence and the Perception of Blur
VB 02
Vincent Bonin, Valerio Mante, Matteo
Carandini
Nonlinear Processing in LGN Neurons
VB 03
Scott A. Beardsley, Lucia M.
Vaina
A Functional Architecture for Motion Pattern Processing in MSTd
VB 04
Alan Yuille, Fang Fang, Paul Schrater, Daniel
Kersten
Human and Ideal Observers for Detecting Image Curves
VB 05
Nathan Sprague, Dana
Ballard
Eye Movements for Reward Maximization
VB 06
Matthias H. Hennig, Florentin
Woergoetter
Eye Micro-movements Improve Stimulus Detection beyond the Nyquist Limit in the Peripheral Retina
VB 07
Reto Wyss, Paul F. M. J.
Verschure
Bounded Invariance and the Formation of Place Fields
VM 01
Salvador Ruiz-Correa, Linda G. Shapiro, Marina
Meila,
Gabriel Berson
Discriminating deformable shape classes
VM 02
Kevin Murphy, Antonio Torralba, William T.
Freeman
Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes
VM 03
Amit Gruber, Yair Weiss
Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence
VM 04
Michael Fink, Pietro Perona
Mutual Boosting for Contextual Inference
VM 05
Jianxin Wu, James M. Rehg, Matthew D.
Mullin
Learning a Rare Event Detection Cascade by Direct Feature Selection
VM 06
Sanjiv Kumar, Martial
Hebert
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
VM 07
Leonid Sigal, Michael Isard, Benjamin H.
Sigelman,
Michael J. Black
Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation
VM 08
Deva Ramanan, David A.
Forsyth
Automatic Annotation of Everyday Movements
VM 09
Lorenzo Torresani, Aaron Hertzmann, Christoph
Bregler
Learning Non-Rigid 3D Shape from 2D Motion
VM 10
Marian S. Bartlett, Gwen Litttlewort, Ian Fasel,
Joel
Chenu, Takayuki Kanda, Hiroshi Ishiguro, Javier R.
Movellan
Towards Social Robots: Automatic Evaluation of Human-Robot Interaction by Facial Expression Classification
WEDNESDAY –
December 10, 2003
AA 37
Chen Yanover, Yair Weiss
Finding the M Most Probable Configurations Using Loopy Belief Propagation
AA 38
Jakob J. Verbeek, Sam T. Roweis, Nikos
Vlassis
Non-linear CCA and PCA by Alignment of Local Models
AA 39
Francis R. Bach, Michael I.
Jordan
Learning Spectral Clustering
AA 40
Corinna Cortes, Mehryar
Mohri
AUC Optimization vs. Error Rate Minimization
AA 41
Dengyong Zhou, Olivier Bousquet, Thomas N. Lal,
Jason
Weston, Bernhard Schölkopf
Learning with Local and Global Consistency
AA 42
Neil D. Lawrence
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
AA 43
Edward Snelson, Carl E. Rasmussen, Zoubin
Ghahramani
Warped Gaussian Processes
AA 44
Allan Borodin, Ran El-Yaniv, Vincent
Gogan
Can We Learn to Beat the Best Stock
AA 45
Tom Heskes, Onno Zoeter, Wim
Wiegerinck
Approximate Expectation Maximization
AA 46
Max Welling, Yee Whye Teh
Linear Response for Approximate Inference
AA 47
Martin J. Wainwright, Michael I.
Jordan
Semidefinite Relaxations for Approximate Inference on Graphs with Cycles
AA 48
Alina Beygelzimer, Irina
Rish
Approximability of Probability Distributions
AA 49
Quaid Morris, Brendan Frey
Denoising and Untangling Graphs using Degree Priors
AA 50
XuanLong Nguyen, Michael I.
Jordan
On the Concentration of Expectation and Approximate Inference in Layered Networks
AA 51
Radford M. Neal, Matthew J. Beal, Sam T.
Roweis
Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models
AA 52
Pedro F. Felzenszwalb, Daniel P. Huttenlocher,
Jon
Kleinberg
Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis
AA 53
Geoffrey Hinton, Max
Welling
Wormholes Improve Contrastive Divergence
AA 54
Mark A. Paskin
Sample Propagation
AA 55
Amos J. Storkey
Generalised Propagation for Fast Fourier
Transforms with
Partial or Missing Data
AA 56
Alex J. Smola, S. V. N. Vishwanathan, Eleazar
Eskin
Laplace Propagation
AA 57
Goekhan H. Bakir, Jason Weston, Bernhard
Schölkopf
Learning to Find Pre-Images
AA 58
Thore Graepel, Ralf Herbrich, Andriy Kharechko,
John
Shawe-Taylor
Semidefinite Programming by Perceptron Learning
AA 59
Noam Shental, Aharon Bar-Hillel, Tomer Hertz,
Daphna
Weinshall
Computing Gaussian Mixture Models with EM using Equivalence Constraints
AA 60
Volker Roth, Tilman Lange
Feature Selection in Clustering Problems
AA 61
David Kauchak, Sanjoy
Dasgupta
An Iterative Improvement Procedure for Hierarchical Clustering
AA 62
Zvika Marx, Ido Dagan, Eli
Shamir
Identifying Structure across Pre-partitioned Data
AA 63
Ofer Dekel, Christopher D. Manning, Yoram
Singer
Log-Linear Models for Label Ranking
AA 64
Matthew Brand
Minimax Embeddings
AA 65
Yoshua Bengio, Yves
Grandvalet
No Unbiased Estimator of the Variance of K-Fold Cross-Validation
AA 66
Harald Steck, Tommi S.
Jaakkola
Bias-Corrected Bootstrap and Model Uncertainty
AA 67
Ting-Fan Wu, Chih-Jen Lin, Ruby C.
Weng
Probability Estimates for Multi-class Classification by Pairwise Coupling
AA 68
Gang Ji, Jeff Bilmes
Necessary Intransitive Likelihood-Ratio Classifiers
AA 69
Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew
McCallum
Classification with Hybrid Generative/Discriminative Models
AA 70
Victor Lavrenko, Raghavan Manmatha, Jiwoon
Jeon
A Model for Learning the Semantics of Pictures
AA 71
Michael Kearns, Luis E.
Ortiz
Algorithms for Interdependent Security Games
AP 11
Daniel B. Neill, Andrew W.
Moore
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters
AP 12
Ben Taskar, Ming-Fai Wong, Pieter Abbeel, Daphne
Koller
Link Prediction in Relational Data
AP 13
Andrew Rabinovich, Sameer Agarwal, Casey A.
Laris,
Jeffrey H. Price, Serge J. Belongie
Unsupervised Color Decomposition of Histologically Stained Tissue Samples
AP 14
Su-In Lee, Serafim
Batzoglou
ICA-based Clustering of Genes from Microarray Expression Data
AP 15
Darya Chudova, Christopher Hart, Eric Mjolsness,
Padhraic Smyth
Gene Expression Clustering with Functional Mixture Models
BI 01
Maneesh Sahani, Srikantan S.
Nagarajan
Reconstructing MEG Sources with Unknown Correlations
BI 02
Saori Tanaka, Kenji Doya, Go Okada, Kazutaka
Ueda,
Yasumasa Okamoto, Shigeto Yamawaki
Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction on Different Time Scales
BI 03
Xuerui Wang, Rebecca Hutchinson, Tom M.
Mitchell
Training fMRI Classifiers to Detect Cognitive
States
across Multiple Human Subjects
BI 04
Roland Vollgraf, Michael Scholz, Ian A.
Meinertzhagen,
Klaus Obermayer
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
BI 05
Zhou Yu, Steven G. Mason, Gary E.
Birch
Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interfac
BI 06
Guido Dornhege, Benjamin Blankertz, Gabriel
Curio,
Klaus-Robert Muller
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class
BI 07
Sung C. Jun, Barak A.
Pearlmutter
Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron
CN 08
Yu-Han Chang, Tracey Ho, Leslie Pack
Kaelbling
All Learning is Local: Multi-agent Learning in Global Reward Games
CN 09
Daniela Pucci de Farias, Nimrod
Megiddo
How to Combine Expert (or Novice) Advice when Actions Impact the Environment?
CN 10
Pascal Poupart, Craig
Boutilier
Bounded Finite State Controllers
CN 11
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng,
Jeff
Schneider
Policy Search by Dynamic Programming
CN 12
Arnab Nilim, Laurent El
Ghaoui
Robust Markov Decision Problems with Uncertain Transition Matrices
CN 13
Alan Fern, SungWook Yoon, Robert
Givan
Approximate Policy Iteration with a Policy Language Bias
CN 14
Matthew R. Rudary, Satinder
Singh
A Nonlinear Predictive State Representation
CN 15
Xiaofeng Wang, Tuomas
Sandholm
Learning Near-Pareto-Optimal Conventions in Polynomial Time
CN 16
Gerald Tesauro
Extending Q-Learning to General Adaptive Multi-Agent Systems
CN 17
Curt Bererton, Geoff Gordon, Sebastian
Thrun
Auction Mechanism Design for Multi-Robot Coordination
CN 18
Ciamac C. Moallemi, Benjamin Van
Roy
Distributed Optimization in Adaptive Networks
CN 19
Milos Hauskrecht, Branislav
Kveton
Linear Program Approximations for Factored Continuous-State Markov Decision Processes
CS 05
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In
Jae
Myung
An MCMC-based Method of Comparing Connectionist Models in Cognitive Science
CS 06
David Philipona, J. Kevin O'Regan, Jean-Pierre
Nadal,
Olivier J.-M. D. Coenen
Perception of the Structure of the Physical World using Unknown Multimodal Sensors and Effectors
CS 07
Thomas L. Griffiths, Joshua B.
Tenenbaum
From Algorithmic to Subjective Randomness
CS 08
Zach Solan, David Horn, Eytan Ruppin, Shimon
Edelman
Unsupervised Context Sensitive Language Acquisition from a Large
Corpus
CS 09
Yuuya Sugita, Jun Tani
A Holistic Approach to Compositional Semantics
CS 10
Aaron C. Courville, Nathaniel D. Daw, Geoff
Gordon,
David S. Touretzky
Model Uncertainty in Classical Conditioning
ET 06
Adria Bofill-i-Petit, Alan
Murray
Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses
ET 07
Masakazu Yagi, Hideo Yamasaki, Tadashi
Shibata
A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image Vectors
ET 08
Francesco Tenore, Ralph Etienne-Cummings, M.
Anthony
Lewis
Entrainment of Silicon Central Pattern Generators for Legged Locomotory Control
ET 09
Eric T. K. Chau, Bertram
Shi
A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell
LT 10
David Donoho, Victoria
Stodden
When Does Non-Negative Matrix Factorization Give a Correct Decomposition Into Parts?
LT 11
Tong Zhang
Learning Bounds for a Generalized Family of Bayesian Posterior Distributions
LT 12
Manfred Opper, Ole Winther
Variational Linear Response
LT 13
Susanne Still, William Bialek, Leon
Bottou
Geometric Clustering using the Information Bottleneck Method
LT 14
Peter L. Bartlett, Michael I. Jordan, Jon M.
McAuliffe
Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates
LT 15
David C. Hoyle, Magnus
Rattray
Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA
LT 16
Doerthe Malzahn, Manfred
Opper
Approximate Analytical Bootstrap Averages for Support Vector Classifiers
LT 17
Justin Werfel, Xiaohui Xie, H. Sebastian
Seung
Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks
LT 18
Gurinder S. Atwal, William
Bialek
Ambiguous Model Learning Made Unambiguous with 1/f Priors
LT 19
Gal Chechik, Amir Globerson, Naftali Tishby,
Yair Weiss
Information Bottleneck for Gaussian Variables
LT 20
Olivier Bousquet, Olivier Chapelle, Matthias
Hein
Measure Based Regularization
LT 21
Koby Crammer, Ofer Dekel, Shai Shalev-Shwartz,
Yoram
Singer
Online Passive-Aggressive Algorithms
LT 22
Saharon Rosset, Ji Zhu, Trevor
Hastie
Margin Maximizing Loss Functions
NS 08
Peter Dayan, Michael Hausser, Michael
London
Plasticity Kernels and Temporal Statistics
NS 09
Jonathan W. Pillow, Liam Paninski, Eero P.
Simoncelli
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
NS 10
Liam Paninski
Design of Experiments via Information Theory
NS 11
Konrad P. Koerding, Daniel M.
Wolpert
Probabilistic Inference in Human Sensorimotor Learning
NS 12
Kazuyuki Samejima, Kenji Doya, Yasumasa Ueda,
Minoru
Kimura
Estimating Internal Variables and Parameters of a Learning Agent by a Particle Filter
NS 13
Bernd Porr, Ausra Saudargiene, Florentin
Woergoetter
Analytical Solution of Spike-Timing Dependent Plasticity based on Synaptic Biophysics
NS 14
Brian J. Fischer, Charles H.
Anderson
A Probabilistic Model of Auditory Space Representation in the Barn Owl
NS 15
Ryan Kelly, Tai S. Lee
Decording V1 Neuronal Activity using Particle Filtering with Volterra Kernels
NS 16
Jan Eichhorn, Andreas Tolias, Alexander Zien,
Malte
Kuss, Carl Rasmussen, Jason Weston, Nikos Logothetis, Bernhard
Schölkopf
Prediction on Spike Data using Kernel Algorithms
SP 05
Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon
Haykin
Predicting Speech Intelligibility from a Population of Neurons
SP 06
Tomohiro Nakatani, Masato Miyoshi, Keisuke
Kinoshita
One Microphone Blind Dereverberation based on Quasi-Periodicity of Speech Signals
SP 07
Nicoleta Roman, DeLiang Wang, Guy J.
Brown
A Classification-based Cocktail-party Processor
VM 11
Song Wang, Toshiro Kubota, Jeffrey M.
Siskind
Salient Boundary Detection using Ratio Contour
VM 12
Anuj Srivastava, Washington Mio, Xiuwen Liu, Eric
Klassen
Geometric Analysis of Constrained Curves
VM 13
Lyndsey C. Pickup, Stephen J. Roberts, Andrew
Zisserman
A Sampled Texture Prior for Image Super-Resolution
VM 14
Charles Rosenberg, Thomas Minka, Alok
Ladsariya
Bayesian Color Constancy with Non-Gaussian Models
VM 15
Claudio Fanti, Marzia Polito, Pietro
Perona
An Improved Scheme for Detection and Labeling in Johansson's Displays