Advances in Neural Information Processing Systems 18 (2005)
The papers below appear in Advances in Neural Information Processing Systems 18 edited by
Y. Weiss and
B. Schölkopf and
J.C. Platt (2005).
- Learning vehicular dynamics, with application to modeling helicopters Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng
- 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
- Large scale networks fingerprinting and visualization using the k-core decomposition J. I. Alvarez-hamelin, Luca Dall'asta, Alain Barrat, Alessandro Vespignani
- 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 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
- 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
- Size Regularized Cut for Data Clustering Yixin Chen, Ya Zhang, Xiang Ji
- Coarse sample complexity bounds for active learning Sanjoy Dasgupta
- 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
- A Theoretical Analysis of Robust Coding over Noisy Overcomplete Channels Eizaburo Doi, Doru C. Balcan, Michael S. Lewicki
- Correcting sample selection bias in maximum entropy density estimation Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
- 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
- Statistical Convergence of Kernel CCA Kenji Fukumizu, Arthur Gretton, Francis R. Bach
- 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
- 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
- Infinite latent feature models and the Indian buffet process Zoubin Ghahramani, Thomas L. Griffiths
- 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
- 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
- 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
- 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
- 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
- Asymptotics of Gaussian Regularized Least Squares Ross Lippert, Ryan Rifkin
- Ideal Observers for Detecting Motion: Correspondence Noise Hongjing Lu, Alan L. Yuille
- 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
- Online Discovery and Learning of Predictive State Representations Peter Mccracken, Michael Bowling
- 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
- 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
- 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
- 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
- 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
- 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
- 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 P. Rao
- Selecting Landmark Points for Sparse Manifold Learning Jorge Silva, Jorge Marques, João Lemos
- 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
- Prediction and Change Detection Mark Steyvers, Scott Brown
- 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
- Temporally changing synaptic plasticity Minija Tamosiunaite, Bernd Porr, Florentin Wörgötter
- 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 P. 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
- Gaussian Process Dynamical Models Jack Wang, Aaron Hertzmann, David M. Blei
- A Bayes Rule for Density Matrices Manfred 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
- 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. Wong, Zhuo Gao, David Tax
- Modeling Neural Population Spiking Activity with Gibbs Distributions Frank Wood, Stefan Roth, Michael J. Black
- Extracting Dynamical Structure Embedded in Neural Activity Afsheen Afshar, Gopal Santhanam, Stephen I. Ryu, Maneesh Sahani, Byron M. Yu, Krishna V. Shenoy
- 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
- 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
- On the Convergence of Eigenspaces in Kernel Principal Component Analysis Laurent Zwald, Gilles Blanchard
- A Bayesian Spatial Scan Statistic
- A Computational Model of Eye Movements during Object Class Detection
- A Connectionist Model for Constructive Modal Reasoning
- A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity
- Active Learning For Identifying Function Threshold Boundaries
- AER Building Blocks for Multi-Layer Multi-Chip Neuromorphic Vision Systems
- A General and Efficient Multiple Kernel Learning Algorithm
- An Alternative Infinite Mixture Of Gaussian Process Experts
- Analysis of Spectral Kernel Design based Semi-supervised Learning
- Analyzing Auditory Neurons by Learning Distance Functions
- An exploration-exploitation model based on norepinepherine and dopamine activity
- A Probabilistic Interpretation of SVMs with an Application to Unbalanced Classification
- Bayesian model learning in human visual perception
- Bayesian Sets
- CMOL CrossNets: Possible Neuromorphic Nanoelectronic Circuits
- Computing the Solution Path for the Regularized Support Vector Regression
- Conditional Visual Tracking in Kernel Space
- Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
- Cyclic Equilibria in Markov Games
- Divergences, surrogate loss functions and experimental design
- Dynamic Social Network Analysis using Latent Space Models
- Efficient estimation of hidden state dynamics from spike trains
- Efficient Unsupervised Learning for Localization and Detection in Object Categories
- Fast Information Value for Graphical Models
- From Batch to Transductive Online Learning
- Fusion of Similarity Data in Clustering
- Group and Topic Discovery from Relations and Their Attributes
- Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps
- Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs
- How fast to work: Response vigor, motivation and tonic dopamine
- Large-Scale Multiclass Transduction
- Layered Dynamic Textures
- Learning from Data of Variable Quality
- Learning in Silicon: Timing is Everything
- Learning Minimum Volume Sets
- Learning Rankings via Convex Hull Separation
- Logic and MRF Circuitry for Labeling Occluding and Thinline Visual Contours
- Margin Semi-Supervised Learning for Structured Variables Yasemin Altun, David A. McAllester, Mikhail Belkin
- Mixture Modeling by Affinity Propagation
- Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity
- Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI
- Non-iterative Estimation with Perturbed Gaussian Markov Processes
- Norepinephrine and Neural Interrupts
- Oblivious Equilibrium: A Mean Field Approximation for Large-Scale Dynamic Games
- Optimizing spatio-temporal filters for improving Brain-Computer Interfacing
- Policy-Gradient Methods for Planning
- Principles of real-time computing with feedback applied to cortical microcircuit models
- Radial Basis Function Network for Multi-task Learning
- Rate Distortion Codes in Sensor Networks
- Recovery of Jointly Sparse Signals from Few Random Projections
- Searching for Character Models
- Sensory Adaptation within a Bayesian Framework for Perception
- Sequence and Tree Kernels with Statistical Feature Mining
- Silicon growth cones map silicon retina
- Spiking Inputs to a Winner-take-all Network
- Structured Prediction via the Extragradient Method
- Transfer learning for text classification
- Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments
- Worst-Case Bounds for Gaussian Process Models