index int64 0 20.3k | text stringlengths 0 1.3M | year stringdate 1987-01-01 00:00:00 2024-01-01 00:00:00 | No stringlengths 1 4 |
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2,200 | Learning to Classify Galaxy Shapes Using the EM Algorithm Sergey Kirshner Information and Computer Science University of California Irvine, CA 92697-3425 skirshne@ics.uci.edu Igor V. Cadez Sparta Inc., 23382 Mill Creek Drive #100, Laguna Hills, CA 92653 igor cadez@sparta.com Padhraic Smyth Inf... | 2002 | 189 |
2,201 | Information Regularization with Partially Labeled Data Martin Szummer MIT AI Lab & CBCL Cambridge, MA 02139 szummer@ai.mit.edu Tommi Jaakkola MIT AI Lab Cambridge, MA 02139 tommi@ai.mit.edu Abstract Classification with partially labeled data requires using a large number of unlabeled examples (or... | 2002 | 19 |
2,202 | FloatBoost Learning for Classification Stan Z. Li Microsoft Research Asia Beijing, China ZhenQiu Zhang Institute of Automation CAS, Beijing, China Heung-Yeung Shum Microsoft Research Asia Beijing, China HongJiang Zhang Microsoft Research Asia Beijing, China Abstract AdaBoost [3] minimize... | 2002 | 190 |
2,203 | Adaptive Scaling for Feature Selection in SVMs Yves Grandvalet Heudiasyc, UMR CNRS 6599, Universit´e de Technologie de Compi`egne, Compi`egne, France Yves.Grandvalet@utc.fr St´ephane Canu PSI INSA de Rouen, St Etienne du Rouvray, France Stephane.Canu@insa-rouen.fr Abstract This paper introduces ... | 2002 | 191 |
2,204 | Adaptive Classification by Variational Kalman Filtering Peter Sykacek Department of Engineering Science University of Oxford Oxford, OX1 3PJ, UK psyk@robots.ox.ac.uk Stephen Roberts Department of Engineering Science University of Oxford Oxford, OX1 3PJ, UK sjrob@robots.ox.ac.uk Abstract We prop... | 2002 | 192 |
2,205 | A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages D¨orthe Malzahn Manfred Opper Informatics and Mathematical Modelling, Technical University of Denmark, R.-Petersens-Plads Building 321, DK-2800 Lyngby, Denmark Neural Computing Research Group, Schoo... | 2002 | 193 |
2,206 | Developing Topography and Ocular Dominance Using two aVLSI Vision Sensors and a Neurotrophic Model of Plasticity Terry Elliott Dept. Electronics & Computer Science University of Southampton Highfield Southampton, SO17 1BJ United Kingdom te@ecs.soton.ac.uk J¨org Kramer Institute of Neuroinformatics ... | 2002 | 194 |
2,207 | Gaussian Process Priors With Uncertain Inputs Application to Multiple-Step Ahead Time Series Forecasting Agathe Girard Department of Computing Science University of Glasgow Glasgow, G12 8QQ agathe@dcs.gla.ac.uk Carl Edward Rasmussen Gatsby Unit University College London London, WC1N 3AR edward@g... | 2002 | 195 |
2,208 | Maximum Likelihood and the Information Bottleneck Noam Slonim Yair Weiss School of Computer Science & Engineering, Hebrew University, Jerusalem 91904, Israel noamm,yweiss @cs.huji.ac.il Abstract The information bottleneck (IB) method is an information-theoretic formulation for clustering problem... | 2002 | 196 |
2,209 | The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum John Shawe-Taylor Royal Holloway University of London john©cs.rhul.ac.uk Christopher K. I. Williams School of Informatics University of Edinburgh c.k.i.williams©ed.ac.uk Abstract In th... | 2002 | 197 |
2,210 | Adaptive Quantization and Density Estimation in Silicon David Hsu Seth Bridges Miguel Figueroa Chris Diorio Department of Computer Science and Engineering University of Washington ... | 2002 | 198 |
2,211 | Improving Transfer Rates in Brain Computer Interfacing: A Case Study Peter Meinicke, Matthias Kaper, Florian Hoppe, Manfred Heumann and Helge Ritter University of Bielefeld Bielefeld, Germany {pmeinick, mkaper, fhoppe, helge} @techfak.uni-bielefeld.de Abstract In this paper we present results of a study o... | 2002 | 199 |
2,212 | Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach Christopher G. Atkeson Robotics Institute and HCII Carnegie Mellon University Pittsburgh, PA 15213, USA cga@cmu.edu Jun Morimoto ATR Human Information Science Laboratories, Dept. 3 Keihanna Science City Kyoto ... | 2002 | 2 |
2,213 | Intrinsic Dimension Estimation Using Packing Numbers Bal´azs K´egl Department of Computer Science and Operations Research University of Montreal CP 6128 succ. Centre-Ville, Montr´eal, Canada H3C 3J7 kegl@iro.umontreal.ca Abstract We propose a new algorithm to estimate the intrinsic dimension of data s... | 2002 | 20 |
2,214 | Discriminative Learning for Label Sequences via Boosting Yasemin Altun, Thomas Hofmann and Mark Johnson* Department of Computer Science *Department of Cognitive and Linguistics Sciences Brown University, Providence, RI 02912 {altun,th}@cs.brown.edu, Mark_Johnson@brown.edu Abstract This paper inv... | 2002 | 200 |
2,215 | Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games Xiaofeng Wang ECE Department Carnegie Mellon University Pittsburgh, PA 15213 xiaofeng@andrew.cmu.edu Tuomas Sandholm CS Department Carnegie Mellon University Pittsburgh, PA 15213 sandholm@cs.cmu.edu Abstract Multia... | 2002 | 201 |
2,216 | Using Manifold Structure for Partially Labelled Classification Mikhail Belkin University of Chicago Department of Mathematics misha@math.uchicago.edu Partha Niyogi University of Chicago Depts of Computer Science and Statistics niyogi@cs.uchicago.edu Abstract We consider the general prob... | 2002 | 202 |
2,217 | Recovering Intrinsic Images from a Single Image Marshall F Tappen William T Freeman Edward H Adelson MIT Artificial Intelligence Laboratory Cambridge, MA 02139 mtappen@ai.mit.edu, wtf@ai.mit.edu, adelson@ai.mit.edu Abstract We present an algorithm that uses multiple cues to recover shading and reflectan... | 2002 | 203 |
2,218 | A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics Eric Allender Computer Science Department Rutgers University allender@cs.rutgers.edu Sanjeev Arora Computer Science Department Princeton University arora@cs.princeton.edu Michael Kearns Department of C... | 2002 | 204 |
2,219 | A Prototype for Automatic Recognition of Spontaneous Facial Actions M.S. Bartlett, G. Littlewort, B. Braathen, T.J. Sejnowski , and J.R. Movellan Institute for Neural Computation and Department of Biology University of California, San Diego and Howard Hughes Medical Institute at the Salk Institute Em... | 2002 | 205 |
2,220 | Exact MAP Estimates by (Hyper)tree Agreement Martin J. Wainwright, Department of EECS, UC Berkeley, Berkeley, CA 94720 martinw@eecs.berkeley.edu Tommi S. Jaakkola and Alan S. Willsky, Department of EECS, Massachusetts Institute of Technology, Cambridge, MA, 02139 tommi,willsky @mit.edu Abstr... | 2002 | 206 |
2,221 | Prediction of Protein Topologies Using Generalized IOHMMs and RNNs Gianluca Pollastri and Pierre Baldi Department of Information and Computer Science University of California, Irvine Irvine, CA 92697-3425 gpollast,pfbaldi@ics.uci.edu Alessandro Vullo and Paolo Frasconi Dipartimento di Sistemi e Informat... | 2002 | 207 |
2,222 | Mismatch String Kernels for SVM Protein Classification Christina Leslie Department of Computer Science Columbia University cleslie@cs.columbia.edu Eleazar Eskin Department of Computer Science Columbia University eeskin@cs.columbia.edu Jason Weston Max-Planck Institute Tuebingen, Germany weston@... | 2002 | 21 |
2,223 | Adaptive Caching by Refetching Robert B. Gramacy , Manfred K. Warmuth , Scott A. Brandt, Ismail Ari Department of Computer Science, UCSC Santa Cruz, CA 95064 rbgramacy, manfred, scott, ari @cs.ucsc.edu Abstract We are constructing caching policies that have 13-20% lower miss rates than th... | 2002 | 22 |
2,224 | Timing and Partial Observability in the Dopamine System Nathaniel D. Daw1,3, Aaron C. Courville2,3, and David S. Touretzky1,3 1Computer Science Department, 2Robotics Institute, 3Center for the Neural Basis of Cognition Carnegie Mellon University, Pittsburgh, PA 15213 {daw,aaronc,dst}@cs.cmu.edu Abstract A... | 2002 | 23 |
2,225 | Multiple Cause Vector Quantization David A. Ross and Richard S. Zemel Department of Computer Science University of Toronto {dross,zemel}@cs.toronto.edu Abstract We propose a model that can learn parts-based representations of highdimensional data. Our key assumption is that the dimensions of the data can ... | 2002 | 24 |
2,226 | Unsupervised Color Constancy Kinh Tieu Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 tieu@ai.mit.edu Erik G. Miller Computer Science Division UC Berkeley Berkeley, CA 94720 egmil@cs.berkeley.edu Abstract In [1] we introduced a linear statistical mode... | 2002 | 25 |
2,227 | Value-Directed Compression of POMDPs Pascal Poupart Departement of Computer Science University of Toronto Toronto, ON, M5S 3H5 ppoupart@cs.toronto.edu Craig Boutilier Department of Computer Science University of Toronto Toronto, ON, M5S 3H5 cebly@cs.toronto.edu Abstract We examine the problem of... | 2002 | 26 |
2,228 | Constraint Classification for Multiclass Classification and Ranking Sariel Har-Peled Dan Roth Dav Zimak Department of Computer Science University of Illinois Urbana, IL 61801 sariel,danr,davzimak @uiuc.edu Abstract The constraint classification framework captures many flavors of multiclass classifi... | 2002 | 27 |
2,229 | Neural Decoding of Cursor Motion Using a Kalman Filter W. Wu M. J. Black Y. Gao E. Bienenstock M. Serruya A. Shaikhouni J. P. Donoghue Division of Applied Mathematics, Dept. of Computer Science, Dept. of Neuroscience, Division of Biology and Medicine, Brown ... | 2002 | 28 |
2,230 | On the Dirichlet Prior and Bayesian Regularization Harald Steck Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 harald@ai.mit.edu Tommi S. Jaakkola Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 t... | 2002 | 29 |
2,231 | A Differential Semantics for Jointree Algorithms James D. Park and Adnan Darwiche Computer Science Department University of California, Los Angeles, CA 90095 {jd,darwiche}@cs.ucla.edu Abstract A new approach to inference in belief networks has been recently proposed, which is based on an algebraic repres... | 2002 | 3 |
2,232 | Scaling of Probability-Based Optimization Algorithms J. L. Shapiro Department of Computer Science University of Manchester Manchester, M13 9PL U.K. jls@cs.man.ac.uk Abstract Population-based Incremental Learning is shown require very sensitive scaling of its learning rate. The learning rate must scale... | 2002 | 30 |
2,233 | Forward-Decoding Kernel-Based Phone Sequence Recognition Shantanu Chakrabartty and Gert Cauwenberghs Center for Language and Speech Processing Department of Electrical and Computer Engineering Johns Hopkins University, Baltimore MD 21218 {shantanu,gert}@jhu.edu Abstract Forward decoding kernel m... | 2002 | 31 |
2,234 | Optoelectronic Implementation of a FitzHugh-Nagumo Neural Model Alexandre R.S. Romariz , Kelvin Wagner Optoelectronic Computing Systems Center University of Colorado, Boulder, CO, USA 80309-0425 romariz@colorado.edu Abstract An optoelectronic implementation of a spiking neuron model based on the Fit... | 2002 | 32 |
2,235 | Margin-Based Algorithms for Information Filtering Nicol`o Cesa-Bianchi DTI, University of Milan via Bramante 65 26013 Crema, Italy cesa-bianchi@dti.unimi.it Alex Conconi DTI, University of Milan via Bramante 65 26013 Crema, Italy conconi@dti.unimi.it Claudio Gentile CRII, Universit`a dell’Ins... | 2002 | 33 |
2,236 | Half-Lives of EigenFlows for Spectral Clustering Chakra Chennubhotla & Allan D. Jepson Department of Computer Science, University of Toronto, Canada M5S 3H5 chakra,jepson @cs.toronto.edu Abstract Using a Markov chain perspective of spectral clustering we present an algorithm to automatically find the n... | 2002 | 34 |
2,237 | The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging Anton Schwaighofer1 2 1 TU Graz, Institute for Theoretical Computer Science Inffeldgasse 16b, 8010 Graz, Austria http://www.igi.tugraz.at/aschwaig Volker Tresp, Peter Mayer 2 Siemens Corporate Technology, Department of N... | 2002 | 35 |
2,238 | Optimality of Reinforcement Learning Algorithms with Linear Function Approximation Ralf Schoknecht ILKD University of Karlsruhe, Germany ralf.schoknecht@ilkd.uni-karlsruhe.de Abstract There are several reinforcement learning algorithms that yield approximate solutions for the problem of policy e... | 2002 | 36 |
2,239 | Evidence Optimization Techniques for Estimating Stimulus-Response Functions Maneesh Sahani Gatsby Unit, UCL 17 Queen Sq., London, WC1N 3AR, UK. maneesh@gatsby.ucl.ac.uk Jennifer F. Linden Keck Center, UCSF San Francisco, CA 94143–0732, USA. linden@phy.ucsf.edu Abstract An essential step in underst... | 2002 | 37 |
2,240 | Binary Coding in Auditory Cortex Michael R. DeWeese and Anthony M. Zador Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724 deweese@cshl.edu, zador@cshl.edu Abstract Cortical neurons have been reported to use both rate and temporal codes. Here we describe a novel mode in which each neuron g... | 2002 | 38 |
2,241 | Learning Attractor Landscapes for Learning Motor Primitives Auke Jan Ijspeert1,3∗, Jun Nakanishi2, and Stefan Schaal1,2 1University of Southern California, Los Angeles, CA 90089-2520, USA 2ATR Human Information Science Laboratories, Kyoto 619-0288, Japan 3EPFL, Swiss Federal Institute of Technology, Lausanne,... | 2002 | 39 |
2,242 | “Name That Song!”: A Probabilistic Approach to Querying on Music and Text Eric Brochu Department of Computer Science University of British Columbia Vancouver, BC, Canada ebrochu@cs.ubc.ca Nando de Freitas Department of Computer Science University of British Columbia Vancouver, BC, Canada nando@cs.... | 2002 | 4 |
2,243 | Combining Dimensions and Features in Similarity-Based Representations Daniel J. Navarro Department of Psychology Ohio State University navarro.20@osu.edu Michael D. Lee Department of Psychology University of Adelaide michael.lee@psychology.adelaide.edu.au Abstract This paper develops a new represe... | 2002 | 40 |
2,244 | Bayesian Monte Carlo Carl Edward Rasmussen and Zoubin Ghahramani Gatsby Computational Neuroscience Unit University College London 17 Queen Square, London WC1N 3AR, England edward,zoubin@gatsby.ucl.ac.uk http://www.gatsby.ucl.ac.uk Abstract We investigate Bayesian alternatives to classical Monte Carlo me... | 2002 | 41 |
2,245 | A Model for Learning Variance Components of Natural Images Yan Karklin yan+@cs.cmu.edu Michael S. Lewicki∗ lewicki@cnbc.cmu.edu Computer Science Department & Center for the Neural Basis of Cognition Carnegie Mellon University Abstract We present a hierarchical Bayesian model for learning efficient co... | 2002 | 42 |
2,246 | Effective Dimension and Generalization of Kernel Learning Tong Zhang IBM T.J. Watson Research Center Yorktown Heights, NY 10598 tzhang@watson.ibm.com Abstract We investigate the generalization performance of some learning problems in Hilbert function Spaces. We introduce a concept of scalesensitive effe... | 2002 | 43 |
2,247 | Nash Propagation for Loopy Graphical Games Luis E. Ortiz Michael Kearns Department of Computer and Information Science University of Pennsylvania leortiz,mkearns @cis.upenn.edu Abstract We introduce NashProp, an iterative and local message-passing algorithm for computing Nash equilibria in multi-pla... | 2002 | 44 |
2,248 | Neuromorphic Bistable VLSI Synapses with Spike-Timing-Dependent Plasticity Giacomo Indiveri Institute of Neuroinformatics University/ETH Zurich CH-8057 Zurich, Switzerland giacomo@ini.phys.ethz.ch Abstract We present analog neuromorphic circuits for implementing bistable synapses with spike-timing-depen... | 2002 | 45 |
2,249 | Source Separation with a Sensor Array Using Graphical Models and Subband Filtering Hagai Attias Microsoft Research Redmond, WA 98052 hagaia@microsoft.com Abstract Source separation is an important problem at the intersection of several fields, including machine learning, signal processing, and speech tec... | 2002 | 46 |
2,250 | Dopamine Induced Bistability Enhances Signal Processing in Spiny Neurons Aaron J. Gruberl,2, Sara A. Solla2,3, and James C. Houk2,l Departments of Biomedical Engineeringl, Physiology2, and Physics and Astronomy3 Northwestern University, Chicago, IL 60201 { a-gruberl, solla, j-houk }@northwestern.edu A... | 2002 | 47 |
2,251 | An Information Theoretic Approach to the Functional Classification of Neurons Elad Schneidman,1,2 William Bialek,1 and Michael J. Berry II2 1Department of Physics and 2Department of Molecular Biology Princeton University, Princeton NJ 08544, USA {elads,wbialek,berry}@princeton.edu Abstract A population of ... | 2002 | 48 |
2,252 | An Asynchronous Hidden Markov Model for Audio-Visual Speech Recognition Samy Bengio Dalle Molle Institute for Perceptual Artificial Intelligence (IDIAP) CP 592, rue du Simplon 4, 1920 Martigny, Switzerland bengio@idiap.ch.http://www.idiap.ch/-bengio Abstract This paper presents a novel Hidden Ma... | 2002 | 49 |
2,253 | Automatic Derivation of Statistical Algorithms: The EM Family and Beyond Alexander G. Gray Carnegie Mellon University agray@cs.cmu.edu Bernd Fischer and Johann Schumann RIACS / NASA Ames fisch,schumann @email.arc.nasa.gov Wray Buntine Helsinki Institute for IT buntine@hiit.fi Abstract Mach... | 2002 | 5 |
2,254 | Shape Recipes: Scene Representations that Refer to the Image William T. Freeman and Antonio Torralba Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 {wtf, torralba}@ai.mit.edu Abstract The goal of low-level vision is to estimate an underlying scene, given an... | 2002 | 50 |
2,255 | Real-time Particle Filters Cody Kwok Dieter Fox Marina Meil˘a Dept. of Computer Science & Engineering, Dept. of Statistics University of Washington Seattle, WA 98195 ctkwok,fox @cs.washington.edu, mmp@stat.washington.edu Abstract Particle filters estimate the state of dynamical syste... | 2002 | 51 |
2,256 | Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting Kenji Fukumizu Institute of Statistical Mathematics Tokyo 106-8569 Japan fukumizu@ism.ac.jp Shotaro Akaho AIST Tsukuba 305-8568 Japan s.akaho@aist.go.jp Shun-ichi Amari RIKEN Wako 351-0198 Japan amari@bra... | 2002 | 52 |
2,257 | Manifold Parzen Windows Pascal Vincent and Yoshua Bengio Dept. IRO, Université de Montréal C.P. 6128, Montreal, Qc, H3C 3J7, Canada {vincentp,bengioy}@iro.umontreal.ca http://www.iro.umontreal.ca/ vincentp Abstract The similarity between objects is a fundamental element of many learning algorithms. Mo... | 2002 | 53 |
2,258 | Parametric Mixture Models for Multi-Labeled Text Naonori Ueda Kazumi Saito NTT Communication Science Laboratories 2-4 Hikaridai, Seikacho, Kyoto 619-0237 Japan {ueda,saito}@cslab.kecl.ntt.co.jp Abstract We propose probabilistic generative models, called parametric mixture models (PMMs), for multiclass, ... | 2002 | 54 |
2,259 | Transductive and Inductive Methods for Approximate Gaussian Process Regression Anton Schwaighofer1 2 1 TU Graz, Institute for Theoretical Computer Science Inffeldgasse 16b, 8010 Graz, Austria http://www.igi.tugraz.at/aschwaig Volker Tresp2 2 Siemens Corporate Technology CT IC4 Otto-Hahn-Ring 6, 8173... | 2002 | 55 |
2,260 | Adapting Codes and Embeddings for Polychotomies Gunnar R¨atsch, Alexander J. Smola RSISE, CSL, Machine Learning Group The Australian National University Canberra, 0200 ACT, Australia Gunnar.Raetsch, Alex.Smola @anu.edu.au Sebastian Mika Fraunhofer FIRST Kekulestr. 7 12489 Berlin, Germany mika@... | 2002 | 56 |
2,261 | Topographic Map Formation by Silicon Growth Cones Brian Taba and Kwabena Boahen Department of Bioengineering University of Pennsylvania Philadelphia, P A 19104 {blaba, kwabena}@neuroengineering.upenn.edu Abstract We describe a self-configuring neuromorphic chip that uses a model of activity-d... | 2002 | 57 |
2,262 | Analysis of Information in Speech based on MANOVA Sachin s. Kajarekarl and Hynek Hermansky l,2 1 Department of Electrical and Computer Engineering OGI School of Science and Engineering at OHSU Beaverton, OR 2International Computer Science Institute Berkeley, CA { sachin,hynek} @asp.ogi.edu Ab... | 2002 | 58 |
2,263 | Discriminative Binaural Sound Localization Ehud Ben-Reuven and Yoram Singer School of Computer Science & Engineering The Hebrew University, Jerusalem 91904, Israel udi@benreuven.com, singer@cs.huji.ac.il Abstract Time difference of arrival (TDOA) is commonly used to estimate the azimuth of a source in a mic... | 2002 | 59 |
2,264 | Going Metric: Denoising Pairwise Data Volker Roth Julian Laub Informatik III, University of Bonn Roemerstr 164, 53117 Bonn, Germany roth©cs.uni-bonn.de Fraunhofer FIRST.IDA Kekulestr. 7, 12489 Berlin, Germany jlaub©first.fhg.de Joachim M. Buhmann Informatik III, University of Bonn Roeme... | 2002 | 6 |
2,265 | Fractional Belief Propagation Wim Wiegerinck and Tom Heskes SNN, University of Nijmegen Geert Grooteplein 21, 6525 EZ, Nijmegen, the Netherlands wimw,tom @snn.kun.nl Abstract We consider loopy belief propagation for approximate inference in probabilistic graphical models. A limitation of the standard ... | 2002 | 60 |
2,266 | Stability-Based Model Selection Tilman Lange, Mikio L. Braun, Volker Roth, Joachim M. Buhmann (lange,braunm,roth,jb)@cs.uni-bonn.de Institute of Computer Science, Dept. III, University of Bonn R¨omerstraße 164, 53117 Bonn, Germany Abstract Model selection is linked to model assessment, which is the proble... | 2002 | 61 |
2,267 | Hidden Markov Model of Cortical Synaptic Plasticity: Derivation of the Learning Rule Michael Eisele W. M. Keck Center for Integrative Neuroscience San Francisco, CA 94143-0444 eisele@phy.ucsf.edu Kenneth D. Miller W. M. Keck Center for Integrative Neuroscience San Francisco, CA 94143-0444 ken@phy.... | 2002 | 62 |
2,268 | Automatic Alignment of Local Representations Yee Whye Teh and Sam Roweis Department of Computer Science, University of Toronto ywteh,roweis @cs.toronto.edu Abstract We present an automatic alignment procedure which maps the disparate internal representations learned by several local dimensionality red... | 2002 | 63 |
2,269 | Field-Programmable Learning Arrays Seth Bridges, Miguel Figueroa, David Hsu, and Chris Diorio Department of Computer Science and Engineering University of Washington 114 Sieg Hall, Box 352350 Seattle, WA 98195-2350 seth,miguel,hsud,diorio @cs.washington.edu Abstract This paper introduces the Field... | 2002 | 64 |
2,270 | Boosting Density Estimation Saharon Rosset Department of Statistics Stanford University Stanford, CA, 94305 saharon@stat.stanford.edu Eran Segal Computer Science Department Stanford University Stanford, CA, 94305 eran@cs.stanford.edu Abstract Several authors have suggested viewing boosting as a ... | 2002 | 65 |
2,271 | Support Vector Machines for Multi ple-Instance Learning Stuart Andrews, Ioannis Tsochantaridis and Thomas Hofmann Department of Computer Science, Brown University, Providence, RI 02912 {stu,it,th}@cs.brown.edu Abstract This paper presents two new formulations of multiple-instance learning as a maxi... | 2002 | 66 |
2,272 | Bias-Optimal Incremental Problem Solving J¨urgen Schmidhuber IDSIA, Galleria 2, 6928 Manno-Lugano, Switzerland juergen@idsia.ch Abstract Given is a problem sequence and a probability distribution (the bias) on programs computing solution candidates. We present an optimally fast way of incrementally solvin... | 2002 | 67 |
2,273 | Rate Distortion Function in the Spin Glass State: a Toy Model Tatsuto Murayama and Masato Okada Laboratory for Mathematical Neuroscience RIKEN Brain Science Institute Saitama, 351-0198, JAPAN {murayama,okada}@brain.riken.go.jp Abstract We applied statistical mechanics to an inverse problem of linear map... | 2002 | 68 |
2,274 | Adaptive Nonlinear System Identification with Echo State Networks Herbert Jaeger International University Bremen D-28759 Bremen, Germany h.jaeger@iu-bremen. de Abstract Echo state networks (ESN) are a novel approach to recurrent neural network training. An ESN consists of a large, fixed, recurrent ... | 2002 | 69 |
2,275 | String Kernels, Fisher Kernels and Finite State Automata Craig Saunders John Shawe-Taylor Alexei Vinokourov Department of Computer Science Royal Holloway, University of London Email: {craig, j st, alexei }«lcs. rhul. ac. uk Abstract In this paper we show how the generation of documents can be... | 2002 | 7 |
2,276 | Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch Lawrence K. Saul1, Daniel D. Lee2, Charles L. Isbell3, and Yann LeCun4 1 Department of Computer and Information Science 2Department of Electrical and System Engineering University of Pennsylvania, 200 South 33r... | 2002 | 70 |
2,277 | An Impossibility Theorem for Clustering Jon Kleinberg Department of Computer Science Cornell University Ithaca NY 14853 Abstract Although the study of clustering is centered around an intuitively compelling goal, it has been very difficult to develop a unified framework for reasoning about it at a technica... | 2002 | 71 |
2,278 | Visual Development Aids the Acquisition of Motion Velocity Sensitivities Robert A. Jacobs Department of Brain and Cognitive Sciences University of Rochester Rochester, NY 14627 robbie@bcs.rochester.edu Melissa Dominguez Department of Computer Science University of Rochester Rochester, NY 14627 mel... | 2002 | 72 |
2,279 | On the Complexity of Learning the Kernel Matrix Olivier Bousquet, Daniel J. L. Herrmann MPI for Biological Cybernetics Spemannstr. 38, 72076 T¨ubingen Germany olivier.bousquet, daniel.herrmann @tuebingen.mpg.de Abstract We investigate data based procedures for selecting the kernel when learning wi... | 2002 | 73 |
2,280 | Clustering with the Fisher Score Koji Tsuda, Motoaki Kawanabe and Klaus-Robert M¨uller AIST CBRC, 2-41-6, Aomi, Koto-ku, Tokyo, 135-0064, Japan Fraunhofer FIRST, Kekul´estr. 7, 12489 Berlin, Germany Dept. of CS, University of Potsdam, A.-Bebel-Str. 89, 14482 Potsdam, Germany koji.t... | 2002 | 74 |
2,281 | Artefactual Structure from Least Squares Multidimensional Scaling Nicholas P. Hughes Department of Engineering Science University of Oxford Oxford, 0X1 3PJ, UK nph@robots.ox.ac.uk David Lowe Neural Computing Research Group Aston University Birmingham, B4 7ET, UK d.lowe@aston.ac.uk Abstract We ... | 2002 | 75 |
2,282 | Adaptation and Unsupervised Learning Peter Dayan Maneesh Sahani Gr´egoire Deback Gatsby Computational Neuroscience Unit 17 Queen Square, London, England, WC1N 3AR. dayan, maneesh @gatsby.ucl.ac.uk, gdeback@ens-lyon.fr Abstract Adaptation is a ubiquitous neural and psychological phenomenon, with ... | 2002 | 76 |
2,283 | Learning in Zero-Sum Team Markov Games Using Factored Value Functions Michail G. Lagoudakis Department of Computer Science Duke University Durham, NC 27708 mgl@cs.duke.edu Ronald Parr Department of Computer Science Duke University Durham, NC 27708 parr@cs.duke.edu Abstract We present a new met... | 2002 | 77 |
2,284 | Convergence Properties of some Spike-Triggered Analysis Techniques Liam Paninski Center for Neural Science New York University New York, NY 10003 liam@cns.nyu. edu http://www.cns.nyu.edu/rvliam Abstract vVe analyze the convergence properties of three spike-triggered data analysis techniques. All o... | 2002 | 78 |
2,285 | Learning to Take Concurrent Actions Khashayar Rohanimanesh Department of Computer Science University of Massachusetts Amherst, MA 01003 khash@cs.umass.edu Sridhar Mahadevan Department of Computer Science University of Massachusetts Amherst, MA 01003 mahadeva@cs.umass.edu Abstract We investigate ... | 2002 | 79 |
2,286 | Extracting Relevant Structures with Side Information Gal Chechik and Naftali Tishby ggal,tishby @cs.huji.ac.il School of Computer Science and Engineering and The Interdisciplinary Center for Neural Computation The Hebrew University of Jerusalem, 91904, Israel Abstract The problem of extracting... | 2002 | 8 |
2,287 | Handling Missing Data with Variational Bayesian Learning of ICA Kwokleung Chan, Te-Won Lee and Terrence Sejnowski The Salk Institute, Computational Neurobiology Laboratory, 10010 N. Torrey Pines Road, La Jolla,, CA 92037, USA {kwchan,tewon,terry}@salk.edu Abstract Missing data is common in real-world da... | 2002 | 80 |
2,288 | Ranking with Large Margin Principle: Two Approaches* Amnon Shashua School of CS&E Hebrew University of Jerusalem Jerusalem 91904, Israel email: shashua@cs.huji.ac.il Anat Levin School of CS&E Hebrew University of Jerusalem Jerusalem 91904, Israel email: alevin@cs.huji.ac.il Abstract ... | 2002 | 81 |
2,289 | A Bilinear Model for Sparse Coding David B. Grimes and Rajesh P. N. Rao Department of Computer Science and Engineering University of Washington Seattle, WA 98195-2350, U.S.A. grimes,rao @cs.washington.edu Abstract Recent algorithms for sparse coding and independent component analysis (ICA) have demo... | 2002 | 82 |
2,290 | Data-Dependent Bounds for Bayesian Mixture Methods Ron Meir Department of Electrical Engineering Technion, Haifa 32000, Israel rmeir@ee.technion.ac.il Tong Zhang IBM T.J. Watson Research Center Yorktown Heights, NY 10598, USA tzhang@watson.ibm.com Abstract We consider Bayesian mixture approaches, ... | 2002 | 83 |
2,291 | Information Diffusion Kernels John Lafferty School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 USA lafferty@cs.cmu.edu Guy Lebanon School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 USA lebanon@cs.cmu.edu Abstract A new family of kernels for statis... | 2002 | 84 |
2,292 | Boosted Dyadic Kernel Discriminants Baback Moghaddam Mitsubishi Electric Research Laboratory 201 Broadway Cambridge MA 02139 USA baback@merl.com Gregory Shakhnarovich MIT AI Laboratory 200 Technology Square Cambridge MA 02139 USA gregory@ai.mit.edu Abstract We introduce a novel learning algorith... | 2002 | 85 |
2,293 | Derivative observations in Gaussian Process Models of Dynamic Systems E. Solak Dept. Elec. & Electr. Eng., Strathclyde University, Glasgow G1 1QE, Scotland, UK. ercan.solak@strath.ac.uk R. Murray-Smith Dept. Computing Science, University of Glasgow Glasgow G12 8QQ, Scotland, UK. rod... | 2002 | 86 |
2,294 | Global Versus Local Methods in Nonlinear Dimensionality Reduction Vin de Silva Department of Mathematics, Stanford University, Stanford. CA 94305 silva@math.stanford.edu Joshua B. Tenenbaum Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge. MA 02139 jbt@a... | 2002 | 87 |
2,295 | Learning Graphical Models with Mercer Kernels Francis R. Bach Division of Computer Science University of California Berkeley, CA 94720 fbach@cs.berkeley.edu Michael I. Jordan Computer Science and Statistics University of California Berkeley, CA 94720 jordan@cs.berkeley.edu Abstract We present ... | 2002 | 88 |
2,296 | Stochastic Neighbor Embedding Geoffrey Hinton and Sam Roweis Department of Computer Science, University of Toronto 10 King’s College Road, Toronto, M5S 3G5 Canada hinton,roweis @cs.toronto.edu Abstract We describe a probabilistic approach to the task of placing objects, described by high-dimensional v... | 2002 | 89 |
2,297 | Classifying Patterns of Visual Motion a Neuromorphic Approach Jakob Heinzle and Alan Stocker Institute of Neuroinformatics University and ETH Z¨urich Winterthurerstr. 190, 8057 Z¨urich, Switzerland jakob,alan @ini.phys.ethz.ch Abstract We report a system that classifies and can learn to classify pat... | 2002 | 9 |
2,298 | Learning in Spiking Neural Assemblies David Barber Institute for Adaptive and Neural Computation Edinburgh University 5 Forrest Hill, Edinburgh, EH1 2QL, U.K. dbarber@anc.ed.ac.uk Abstract We consider a statistical framework for learning in a class of networks of spiking neurons. Our aim is to show how op... | 2002 | 90 |
2,299 | A Model for Real-Time Computation in Generic Neural Microcircuits Wolfgang Maass , Thomas Natschl¨ager Institute for Theoretical Computer Science Technische Universitaet Graz, Austria maass, tnatschl @igi.tu-graz.ac.at Henry Markram Brain Mind Institute EPFL, Lausanne, Switzerland henry.markr... | 2002 | 91 |
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