Advances in Neural Information Processing Systems 18 (NIPS 2005)
The papers below appear in Advances in Neural Information Processing Systems 18 edited by Y. Weiss and B. Schölkopf and J.C. Platt.They are proceedings from the conference, "Neural Information Processing Systems 2005."
- Learning vehicular dynamics, with application to modeling helicopters Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng
- Policy-Gradient Methods for Planning Douglas Aberdeen
- Kernelized Infomax Clustering David Barber, Felix V. Agakov
- Large-scale biophysical parameter estimation in single neurons via constrained linear regression Misha Ahrens, Liam Paninski, Quentin J. Huys
- Maximum Margin Semi-Supervised Learning for Structured Variables Y. Altun, D. McAllester, M. Belkin
- Large scale networks fingerprinting and visualization using the k-core decomposition J. I. Alvarez-hamelin, Luca Dall'asta, Alain Barrat, Alessandro Vespignani
- Fast Information Value for Graphical Models Brigham S. Anderson, Andrew W. Moore
- A Cortically-Plausible Inverse Problem Solving Method Applied to Recognizing Static and Kinematic 3D Objects David Arathorn
- Combining Graph Laplacians for Semi--Supervised Learning Andreas Argyriou, Mark Herbster, Massimiliano Pontil
- Learning in Silicon: Timing is Everything John V. Arthur, Kwabena Boahen
- Learning Topology with the Generative Gaussian Graph and the EM Algorithm Michaël Aupetit
- On Local Rewards and Scaling Distributed Reinforcement Learning Drew Bagnell, Andrew Y. Ng
- Bayesian models of human action understanding Chris Baker, Rebecca Saxe, Joshua B. Tenenbaum
- The Curse of Highly Variable Functions for Local Kernel Machines Yoshua Bengio, Olivier Delalleau, Nicolas L. Roux
- Non-Local Manifold Parzen Windows Yoshua Bengio, Hugo Larochelle, Pascal Vincent
- Convex Neural Networks Yoshua Bengio, Nicolas L. Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte
- Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir Spokoiny, Klaus-Robert Müller
- From Weighted Classification to Policy Search Doron Blatt, Alfred O. Hero
- Correlated Topic Models John D. Lafferty, David M. Blei
- Saliency Based on Information Maximization Neil Bruce, John Tsotsos
- Active Learning For Identifying Function Threshold Boundaries Brent Bryan, Robert C. Nichol, Christopher R. Genovese, Jeff Schneider, Christopher J. Miller, Larry Wasserman
- Subsequence Kernels for Relation Extraction Raymond J. Mooney, Razvan C. Bunescu
- Faster Rates in Regression via Active Learning Rebecca Willett, Robert Nowak, Rui M. Castro
- Gradient Flow Independent Component Analysis in Micropower VLSI Abdullah Celik, Milutin Stanacevic, Gert Cauwenberghs
- Improved risk tail bounds for on-line algorithms Nicolò Cesa-bianchi, Claudio Gentile
- Layered Dynamic Textures Antoni B. Chan, Nuno Vasconcelos
- Size Regularized Cut for Data Clustering Yixin Chen, Ya Zhang, Xiang Ji
- Learning from Data of Variable Quality Koby Crammer, Michael Kearns, Jennifer Wortman
- Efficient estimation of hidden state dynamics from spike trains Marton G. Danoczy, Richard H. R. Hahnloser
- Coarse sample complexity bounds for active learning Sanjoy Dasgupta
- Norepinephrine and Neural Interrupts Peter Dayan, Angela J. Yu
- Fast Krylov Methods for N-Body Learning Nando D. Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang
- The Forgetron: A Kernel-Based Perceptron on a Fixed Budget Ofer Dekel, Shai Shalev-shwartz, Yoram Singer
- Data-Driven Online to Batch Conversions Ofer Dekel, Yoram Singer
- Beyond Gaussian Processes: On the Distributions of Infinite Networks Ricky Der, Daniel D. Lee
- Generalized Nonnegative Matrix Approximations with Bregman Divergences Suvrit Sra, Inderjit S. Dhillon
- An Application of Markov Random Fields to Range Sensing James Diebel, Sebastian Thrun
- Transfer learning for text classification Chuong B. Do, Andrew Y. Ng
- A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels Eizaburo Doi, Doru C. Balcan, Michael S. Lewicki
- Optimizing spatio-temporal filters for improving Brain-Computer Interfacing Guido Dornhege, Benjamin Blankertz, Matthias Krauledat, Florian Losch, Gabriel Curio, Klaus-Robert Müller
- Correcting sample selection bias in maximum entropy density estimation Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
- Searching for Character Models Jaety Edwards, David Forsyth
- Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps Austin I. Eliazar, Ronald Parr
- Learning to Control an Octopus Arm with Gaussian Process Temporal Difference Methods Yaakov Engel, Peter Szabo, Dmitry Volkinshtein
- Two view learning: SVM-2K, Theory and Practice Jason Farquhar, David Hardoon, Hongying Meng, John S. Shawe-taylor, Sándor Szedmák
- Robust design of biological experiments Patrick Flaherty, Adam Arkin, Michael I. Jordan
- Pattern Recognition from One Example by Chopping Francois Fleuret, Gilles Blanchard
- Mixture Modeling by Affinity Propagation Brendan J. Frey, Delbert Dueck
- Statistical Convergence of Kernel CCA Kenji Fukumizu, Arthur Gretton, Francis R. Bach
- Learning Rankings via Convex Hull Separation Glenn Fung, Rómer Rosales, Balaji Krishnapuram
- A Connectionist Model for Constructive Modal Reasoning Artur Garcez, Luis C. Lamb, Dov M. Gabbay
- Large-Scale Multiclass Transduction Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan
- Products of ``Edge-perts Max Welling, Peter V. Gehler
- Fast biped walking with a reflexive controller and real-time policy searching Tao Geng, Bernd Porr, Florentin Wörgötter
- Bayesian Sets Zoubin Ghahramani, Katherine A. Heller
- Query by Committee Made Real Ran Gilad-bachrach, Amir Navot, Naftali Tishby
- Metric Learning by Collapsing Classes Amir Globerson, Sam T. Roweis
- Interpolating between types and tokens by estimating power-law generators Sharon Goldwater, Mark Johnson, Thomas L. Griffiths
- A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification Yves Grandvalet, Johnny Mariethoz, Samy Bengio
- Infinite latent feature models and the Indian buffet process Zoubin Ghahramani, Thomas L. Griffiths
- Computing the Solution Path for the Regularized Support Vector Regression Lacey Gunter, Ji Zhu
- Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs Firas Hamze, Nando de Freitas
- Tensor Subspace Analysis Xiaofei He, Deng Cai, Partha Niyogi
- Laplacian Score for Feature Selection Xiaofei He, Deng Cai, Partha Niyogi
- Inferring Motor Programs from Images of Handwritten Digits Vinod Nair, Geoffrey E. Hinton
- Response Analysis of Neuronal Population with Synaptic Depression Wentao Huang, Licheng Jiao, Shan Tan, Maoguo Gong
- Non-iterative Estimation with Perturbed Gaussian Markov Processes Yunsong Huang, B. Keith Jenkins
- Learning Cue-Invariant Visual Responses Jarmo Hurri
- Bayesian Surprise Attracts Human Attention Laurent Itti, Pierre F. Baldi
- Efficient Estimation of OOMs Herbert Jaeger, Mingjie Zhao, Andreas Kolling
- Representing Part-Whole Relationships in Recurrent Neural Networks Viren Jain, Valentin Zhigulin, H. S. Seung
- A Probabilistic Approach for Optimizing Spectral Clustering Rong Jin, Feng Kang, Chris H. Ding
- Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation Dmitry Malioutov, Alan S. Willsky, Jason K. Johnson
- Using ``epitomes'' to model genetic diversity: Rational design of HIV vaccine cocktails Nebojsa Jojic, Vladimir Jojic, Christopher Meek, David Heckerman, Brendan J. Frey
- Integrate-and-Fire models with adaptation are good enough Renaud Jolivet, Alexander Rauch, Hans-rudolf Lüscher, Wulfram Gerstner
- Generalization Error Bounds for Aggregation by Mirror Descent with Averaging Anatoli Juditsky, Alexander Nazin, Alexandre Tsybakov, Nicolas Vayatis
- From Batch to Transductive Online Learning Sham Kakade, Adam Tauman Kalai
- Worst-Case Bounds for Gaussian Process Models Sham M. Kakade, Matthias W. Seeger, Dean P. Foster
- Hyperparameter and Kernel Learning for Graph Based Semi-Supervised Classification Ashish Kapoor, Hyungil Ahn, Yuan Qi, Rosalind W. Picard
- Is Early Vision Optimized for Extracting Higher-order Dependencies? Yan Karklin, Michael S. Lewicki
- A matching pursuit approach to sparse Gaussian process regression Sathiya Keerthi, Wei Chu
- Benchmarking Non-Parametric Statistical Tests Mikaela Keller, Samy Bengio, Siew Y. Wong
- Robust Fisher Discriminant Analysis Seung-jean Kim, Alessandro Magnani, Stephen Boyd
- Measuring Shared Information and Coordinated Activity in Neuronal Networks Kristina Klinkner, Cosma Shalizi, Marcelo Camperi
- Inference with Minimal Communication: a Decision-Theoretic Variational Approach O. P. Kreidl, Alan S. Willsky
- Generalization in Clustering with Unobserved Features Eyal Krupka, Naftali Tishby
- Variable KD-Tree Algorithms for Spatial Pattern Search and Discovery Jeremy Kubica, Joseph Masiero, Robert Jedicke, Andrew Connolly, Andrew W. Moore
- Assessing Approximations for Gaussian Process Classification Malte Kuss, Carl E. Rasmussen
- Rodeo: Sparse Nonparametric Regression in High Dimensions Larry Wasserman, John D. Lafferty
- Fixing two weaknesses of the Spectral Method Kevin Lang
- Fusion of Similarity Data in Clustering Tilman Lange, Joachim M. Buhmann
- A PAC-Bayes approach to the Set Covering Machine François Laviolette, Mario Marchand, Mohak Shah
- Off-Road Obstacle Avoidance through End-to-End Learning Urs Muller, Jan Ben, Eric Cosatto, Beat Flepp, Yann L. Cun
- Dual-Tree Fast Gauss Transforms Dongryeol Lee, Andrew W. Moore, Alexander G. Gray
- CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits Jung Hoon Lee, Xiaolong Ma, Konstantin K. Likharev
- A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity Robert A. Legenstein, Wolfgang Maass
- Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches Anna Levina, Michael Herrmann
- From Lasso regression to Feature vector machine Fan Li, Yiming Yang, Eric P. Xing
- Location-based activity recognition Lin Liao, Dieter Fox, Henry Kautz
- Radial Basis Function Network for Multi-task Learning Xuejun Liao, Lawrence Carin
- Asymptotics of Gaussian Regularized Least Squares Ross Lippert, Ryan Rifkin
- Efficient Unsupervised Learning for Localization and Detection in Object Categories Nicolas Loeff, Himanshu Arora, Alexander Sorokin, David Forsyth
- Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
- Ideal Observers for Detecting Motion: Correspondence Noise Hongjing Lu, Alan L. Yuille
- Principles of real-time computing with feedback applied to cortical microcircuit models Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
- Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Sridhar Mahadevan, Mauro Maggioni
- Noise and the two-thirds power Law Uri Maoz, Elon Portugaly, Tamar Flash, Yair Weiss
- Modeling Memory Transfer and Saving in Cerebellar Motor Learning Naoki Masuda, Shun-ichi Amari
- An exploration-exploitation model based on norepinepherine and dopamine activity Samuel M. McClure, Mark S. Gilzenrat, Jonathan D. Cohen
- Online Discovery and Learning of Predictive State Representations Peter Mccracken, Michael Bowling
- An Alternative Infinite Mixture Of Gaussian Process Experts Edward Meeds, Simon Osindero
- Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments Keiji Miura, Masato Okada, Shun-ichi Amari
- Consensus Propagation Benjamin V. Roy, Ciamac C. Moallemi
- Context as Filtering Daichi Mochihashi, Yuji Matsumoto
- Spectral Bounds for Sparse PCA: Exact and Greedy Algorithms Baback Moghaddam, Yair Weiss, Shai Avidan
- Top-Down Control of Visual Attention: A Rational Account Michael Shettel, Shaun Vecera, Michael C. Mozer
- Rate Distortion Codes in Sensor Networks: A System-level Analysis Tatsuto Murayama, Peter Davis
- Gaussian Processes for Multiuser Detection in CDMA receivers Juan J. Murillo-fuentes, Sebastian Caro, Fernando Pérez-Cruz
- Nested sampling for Potts models Iain Murray, David MacKay, Zoubin Ghahramani, John Skilling
- Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators Boaz Nadler, Stephane Lafon, Ioannis Kevrekidis, Ronald R. Coifman
- Stimulus Evoked Independent Factor Analysis of MEG Data with Large Background Activity Kenneth Hild, Kensuke Sekihara, Hagai T. Attias, Srikantan S. Nagarajan
- An Analog Visual Pre-Processing Processor Employing Cyclic Line Access in Only-Nearest-Neighbor-Interconnects Architecture Yusuke Nakashita, Yoshio Mita, Tadashi Shibata
- Q-Clustering Mukund Narasimhan, Nebojsa Jojic, Jeff A. Bilmes
- Optimal cue selection strategy Vidhya Navalpakkam, Laurent Itti
- Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity Amir Navot, Lavi Shpigelman, Naftali Tishby, Eilon Vaadia
- A Bayesian Spatial Scan Statistic Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper
- Divergences, surrogate loss functions and experimental design XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
- How fast to work: Response vigor, motivation and tonic dopamine Yael Niv, Nathaniel D. Daw, Peter Dayan
- Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction Guido Nolte, Andreas Ziehe, Frank Meinecke, Klaus-Robert Müller
- An Approximate Inference Approach for the PCA Reconstruction Error Manfred Opper
- Bayesian model learning in human visual perception Gergő Orbán, Jozsef Fiser, Richard N. Aslin, Máté Lengyel
- Spiking Inputs to a Winner-take-all Network Matthias Oster, Shih-Chii Liu
- Variational EM Algorithms for Non-Gaussian Latent Variable Models Jason Palmer, Kenneth Kreutz-Delgado, Bhaskar D. Rao, David P. Wipf
- Nonparametric inference of prior probabilities from Bayes-optimal behavior Liam Paninski
- Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI Ofer Pasternak, Nathan Intrator, Nir Sochen, Yaniv Assaf
- Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects Jean-pascal Pfister, Wulfram Gerstner
- Scaling Laws in Natural Scenes and the Inference of 3D Shape Tai-sing Lee, Brian R. Potetz
- Off-policy Learning with Options and Recognizers Doina Precup, Cosmin Paduraru, Anna Koop, Richard S. Sutton, Satinder P. Singh
- Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization Maxim Raginsky, Svetlana Lazebnik
- Preconditioner Approximations for Probabilistic Graphical Models John D. Lafferty, Pradeep K. Ravikumar
- Cue Integration for Figure/Ground Labeling Xiaofeng Ren, Jitendra Malik, Charless C. Fowlkes
- Generalization to Unseen Cases Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
- Visual Encoding with Jittering Eyes Michele Rucci
- Dynamic Social Network Analysis using Latent Space Models Purnamrita Sarkar, Andrew W. Moore
- Logic and MRF Circuitry for Labeling Occluding and Thinline Visual Contours Eric Saund
- Learning Depth from Single Monocular Images Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng
- Identifying Distributed Object Representations in Human Extrastriate Visual Cortex Rory Sayres, David Ress, Kalanit Grill-spector
- On the Accuracy of Bounded Rationality: How Far from Optimal Is Fast and Frugal? Michael Schmitt, Laura Martignon
- Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation Jin Yu, Douglas Aberdeen, Nicol N. Schraudolph
- The Information-Form Data Association Filter Brad Schumitsch, Sebastian Thrun, Gary Bradski, Kunle Olukotun
- A Bayesian Framework for Tilt Perception and Confidence Odelia Schwartz, Peter Dayan, Terrence J. Sejnowski
- Learning Minimum Volume Sets Clayton Scott, Robert Nowak
- AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems R. Serrano-Gotarredona, M. Oster, P. Lichtsteiner, A. Linares-Barranco, R. Paz-Vicente, F. Gomez-Rodriguez, H. Kolle Riis, T. Delbruck, S. C. Liu, S. Zahnd, A. M. Whatley, R. Douglas, P. Hafliger, G. Jimenez-Moreno, A. Civit, T. Serrano-Gotarredona, A. Acosta-Jimenez, B. Linares-Barranco
- Fast Gaussian Process Regression using KD-Trees Yirong Shen, Matthias Seeger, Andrew Y. Ng
- Learning Shared Latent Structure for Image Synthesis and Robotic Imitation Aaron Shon, Keith Grochow, Aaron Hertzmann, Rajesh PN Rao
- Selecting Landmark Points for Sparse Manifold Learning Jorge Silva, Jorge Marques, João Lemos
- Conditional Visual Tracking in Kernel Space Cristian Sminchisescu, Atul Kanujia, Zhiguo Li, Dimitris Metaxas
- Sparse Gaussian Processes using Pseudo-inputs Edward Snelson, Zoubin Ghahramani
- Phase Synchrony Rate for the Recognition of Motor Imagery in Brain-Computer Interface Le Song, Evian Gordon, Elly Gysels
- A General and Efficient Multiple Kernel Learning Algorithm Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer
- Prediction and Change Detection Mark Steyvers, Scott Brown
- Sensory Adaptation within a Bayesian Framework for Perception Alan A. Stocker, Eero P. Simoncelli
- Describing Visual Scenes using Transformed Dirichlet Processes Antonio Torralba, Alan S. Willsky, Erik B. Sudderth, William T. Freeman
- Active Learning for Misspecified Models Masashi Sugiyama
- Temporal Abstraction in Temporal-difference Networks Eddie Rafols, Anna Koop, Richard S. Sutton
- Sequence and Tree Kernels with Statistical Feature Mining Jun Suzuki, Hideki Isozaki
- Silicon growth cones map silicon retina Brian Taba, Kwabena Boahen
- Temporally changing synaptic plasticity Minija Tamosiunaite, Bernd Porr, Florentin Wörgötter
- Structured Prediction via the Extragradient Method Ben Taskar, Simon Lacoste-Julien, Michael I. Jordan
- Affine Structure From Sound Sebastian Thrun
- Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares Jo-anne Ting, Aaron D'souza, Kenji Yamamoto, Toshinori Yoshioka, Donna Hoffman, Shinji Kakei, Lauren Sergio, John Kalaska, Mitsuo Kawato
- Generalization error bounds for classifiers trained with interdependent data Nicolas Usunier, Massih-reza Amini, Patrick Gallinari
- TD(0) Leads to Better Policies than Approximate Value Iteration Benjamin V. Roy
- An aVLSI Cricket Ear Model Andre V. Schaik, Richard Reeve, Craig Jin, Tara Hamilton
- Goal-Based Imitation as Probabilistic Inference over Graphical Models Deepak Verma, Rajesh PN Rao
- Kernels for gene regulatory regions Jean-philippe Vert, Robert Thurman, William S. Noble
- Consistency of one-class SVM and related algorithms Régis Vert, Jean-philippe Vert
- Multiple Instance Boosting for Object Detection Cha Zhang, John C. Platt, Paul A. Viola
- Estimating the wrong Markov random field: Benefits in the computation-limited setting Martin J. Wainwright
- Recovery of Jointly Sparse Signals from Few Random Projections Michael B. Wakin, Marco F. Duarte, Shriram Sarvotham, Dror Baron, Richard G. Baraniuk
- Gaussian Process Dynamical Models Jack Wang, Aaron Hertzmann, David J. Fleet
- Group and Topic Discovery from Relations and Their Attributes Xuerui Wang, Natasha Mohanty, Andrew McCallum
- A Bayes Rule for Density Matrices Manfred K. K. Warmuth
- Variational Bayesian Stochastic Complexity of Mixture Models Kazuho Watanabe, Sumio Watanabe
- Distance Metric Learning for Large Margin Nearest Neighbor Classification Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul
- Analyzing Auditory Neurons by Learning Distance Functions Inna Weiner, Tomer Hertz, Israel Nelken, Daphna Weinshall
- Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games Gabriel Y. Weintraub, Lanier Benkard, Benjamin Van Roy
- Active Bidirectional Coupling in a Cochlear Chip Bo Wen, Kwabena A. Boahen
- Neural mechanisms of contrast dependent receptive field size in V1 Jim Wielaard, Paul Sajda
- Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care Christopher Williams, John Quinn, Neil Mcintosh
- Comparing the Effects of Different Weight Distributions on Finding Sparse Representations Bhaskar D. Rao, David P. Wipf
- Message passing for task redistribution on sparse graphs K. Y. Michael Wong, David Saad, Zhuo Gao
- Modeling Neural Population Spiking Activity with Gibbs Distributions Frank Wood, Stefan Roth, Michael J. Black
- Extracting Dynamical Structure Embedded in Neural Activity Byron M. Yu, Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Krishna V. Shenoy, Maneesh Sahani
- Soft Clustering on Graphs Kai Yu, Shipeng Yu, Volker Tresp
- Augmented Rescorla-Wagner and Maximum Likelihood Estimation Alan L. Yuille
- The Role of Top-down and Bottom-up Processes in Guiding Eye Movements during Visual Search Gregory Zelinsky, Wei Zhang, Bing Yu, Xin Chen, Dimitris Samaras
- Learning Influence among Interacting Markov Chains Dong Zhang, Daniel Gatica-perez, Samy Bengio, Deb Roy
- Learning Multiple Related Tasks using Latent Independent Component Analysis Jian Zhang, Zoubin Ghahramani, Yiming Yang
- Modeling Neuronal Interactivity using Dynamic Bayesian Networks Lei Zhang, Dimitris Samaras, Nelly Alia-klein, Nora Volkow, Rita Goldstein
- Analysis of Spectral Kernel Design based Semi-supervised Learning Tong Zhang, Rie Kubota Ando
- A Computational Model of Eye Movements during Object Class Detection Wei Zhang, Hyejin Yang, Dimitris Samaras, Gregory J. Zelinsky
- Separation of Music Signals by Harmonic Structure Modeling Yun-gang Zhang, Chang-shui Zhang
- A Domain Decomposition Method for Fast Manifold Learning Zhenyue Zhang, Hongyuan Zha
- A Hierarchical Compositional System for Rapid Object Detection Long Zhu, Alan L. Yuille
- Cyclic Equilibria in Markov Games Martin Zinkevich, Amy Greenwald, Michael L. Littman
- On the Convergence of Eigenspaces in Kernel Principal Component Analysis Laurent Zwald, Gilles Blanchard