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Realtime article Filters Cody Kw ok Dieter ox Marina Meil Dept

Realtime article Filters Cody Kw ok Dieter ox Marina Meil Dept

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Correcting Sample Selection Bias by Unlabeled Data Jiayuan Huang chool of Computer Science Univ

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of Waterloo Canada j9huangcsuwaterlooca Alexander...

Modeling Human Location Data with Mixtures of Kernel Densities Moshe Lichman Department of Computer Science University of California Irvine mlichmanics

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uciedu Padhraic Smyth Department of Computer Scien...

KRLE A new Data Compression Algorithm for Wireless Sensor Network Eug ene Pamba CapoChichi Herv e Guyennet Laboratory of Computer Science LIFC University of Franche Comt Besancon France mpamba herv

KRLE A new Data Compression Algorithm for Wireless Sensor Network Eug ene Pamba CapoChichi Herv e Guyennet Laboratory of Computer Science LIFC University of Franche Comt Besancon France mpamba herv

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THREADS Efcient Deterministic Multithreading Tongping Liu Charlie Curtsinger Emery D

THREADS Efcient Deterministic Multithreading Tongping Liu Charlie Curtsinger Emery D

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International Journal of Computer Applications Volume No

International Journal of Computer Applications Volume No

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10 August 2010 46 A Suitability Study of Discret...

Training Linear Discriminant Analysis in Linear Time Deng Cai Dept

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of Computer Science UIUC dengcai2csuiucedu Xiaofe...

Fisher Linear Discriminant Analysis Max Welling Department of Computer Science University of Toronto Kings College Road Toronto MS G Canada wellingcs

Fisher Linear Discriminant Analysis Max Welling Department of Computer Science University of Toronto Kings College Road Toronto MS G Canada wellingcs

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torontoedu Abstract This is a note to explain Fish...

CONTROL DATA Computer system eal Time Applications At this precise moment events in science and industry are occurring which demand solutions and control

CONTROL DATA Computer system eal Time Applications At this precise moment events in science and industry are occurring which demand solutions and control

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Among these events inrealtime are many that direc...

RealCoded Memetic Algorithms with Crossover HillClimbing Manuel Lozano lozanodecsai

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ugr es Dept of Computer Science and AI University ...

Efciently Matching Sets of Features with Random Histograms Wei Dong Zhe Wang Moses Charikar Kai Li Department of Computer Science Princeton University Olden Street Princeton NJ USA wdongzhewangmose

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princetonedu ABSTRACT As the commonly used represe...

TwoFrame Motion Estimation Based on Polynomial Expansion Gunnar Farneb ack Computer Vision Laboratory Link oping University SE Link oping Sweden gfisy

TwoFrame Motion Estimation Based on Polynomial Expansion Gunnar Farneb ack Computer Vision Laboratory Link oping University SE Link oping Sweden gfisy

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liuse httpwwwisyliusecvl Abstract This paper prese...

Robotic Mapping A Survey Sebastian Thrun February CMUCS School of Computer Science Carnegie Mellon University Pittsburgh PA Abstract This article provides a comprehensive introduction into the eld

Robotic Mapping A Survey Sebastian Thrun February CMUCS School of Computer Science Carnegie Mellon University Pittsburgh PA Abstract This article provides a comprehensive introduction into the eld

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It describes and compares various probabilistic t...

What Missing in AI The Interface Lay er edr Domingos Department of Computer Science and Engineering Uni ersity of ashington Seattle pedrodcs

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Memory Interleaving Norman Matloff Department of Computer Science University of California at Davis November N

Memory Interleaving Norman Matloff Department of Computer Science University of California at Davis November N

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S Matloff 1 Introduction With large memories many ...

Discriminati raining of Kalman Filters Pieter Abbeel Adam Coates Michael Montemerlo Andre Ng and Sebastian Thrun Department of Computer Science Stanford Uni ersity Stanford CA Abstract Kalman lters

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Ho we er their perf ormance critically depends on...

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1 0 n 0 Error between 64257lter output and a d...

Issues Regarding Threshold Concepts in Computer Science Janet Rountree Nathan Rountree Department of Computer Science University of Otago Dunedin New Zealand Email janetnathan cs

Issues Regarding Threshold Concepts in Computer Science Janet Rountree Nathan Rountree Department of Computer Science University of Otago Dunedin New Zealand Email janetnathan cs

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otagoacnz Abstract Threshold Concepts deserve disc...

OURNAL OF NFORMATION CIENCE AND NGINEERING Short Paper Novel Hierarchical Interconnection Networks for HighPerformance Multicomputer Systems ENE E J AN UAN S HIN H WANG M ING B L IN AND D ERON L

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Boosting multistep autoregressive forecasts Souhaib Ben Taieb SBENTAIE ULB AC BE Machine Learning Group Computer Science Department Faculty of Sciences Universit e Libre de Bruxelles Brussels Belgium

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Rob J Hyndman OB H YNDMAN MONASH EDU Department o...

Pr ogram Element Matc hing or MultiV er sion Pr ogram Anal yses Mir yung Kim Da vid Notkin Computer Science Engineer ing Univ ersity of ashington Seattle mir yungnotkin cs

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w ashingtonedu ABSTRA CT Multiv ersion program ana...

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edu Abstract The emergence of multicore processors...

etri Netbased Mo del for eb Service Comp osition Rac hid Hamadi Boualem Benatallah Sc ho ol of Computer Science and Engineering The Univ ersit of New South ales Sydney NSW Australia rhamadibouale cs

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uns w edu a Abstract The In ternet is going throu...

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Deterministic signals Power spectral density denitions Power spectral density properties SGN Advanced Signal Processing Lecture Spectrum estimation Ioan Tabus Department of Signal Processing Tamper

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Module Power Disipation in CMOS Circuits Lecture Power Disipation in CMOS Circuits Objectives In this lecture you will learn the following Motivation Effect of Power Disipation How to Reduce Temp

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monasheduau INTRODUCTION In last months edition of...

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Designs of Counters with Near Minimal CountingSampling Period and Hardware Complexity ChiHsiang Yeh Dept

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of Elec Computer Eng Queens University Kingston ...

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of Computer Science UCL Interactive Centre Univ C...

Matching Points with Rectangles and Squares Sergey Bereg Nikolaus Mutsanas and Alexander Wol Department of Computer Science University of Texas at Dallas U

Matching Points with Rectangles and Squares Sergey Bereg Nikolaus Mutsanas and Alexander Wol Department of Computer Science University of Texas at Dallas U

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SA Email besputdallasedu Fakult57512at f57512ur In...

Water Resources Systems Modeling Techniques and Analysis Lecture Course Instructor Prof

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P P MUJUMDAR Department of Civil Engg IISc brPage...

Dang Tuan NGUYEN and Ha QuyTinh LUONG Faculty of Computer Science University of Information Technology Vietnam Nationnal University HCMC Ho Chi Minh City Vietnam Abstract Keywords

Dang Tuan NGUYEN and Ha QuyTinh LUONG Faculty of Computer Science University of Information Technology Vietnam Nationnal University HCMC Ho Chi Minh City Vietnam Abstract Keywords

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Introduction 2 System Architecture brPage 2br 3 S...

Large Scale Semisupervised Linear SVMs Vikas Sindhwani Department of Computer Science University of Chicago Chicago IL USA vikasscs

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uchicagoedu S Sathiya Keerthi Yahoo Research Media...

Finding Progression Stages in Timeevolving Event Sequences Jaewon Yang Julian McAuley Jure Leskovec Paea LePendu Nigam Shah Computer Science Stanford University jayang jmcauley jurecs

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stanfordedu Biomedical Informatics Stanford Univer...

Road Sign Detection and Recognition Abstract Introduction Submitted to the IEEE Computer Society International Conference on Computer Vision and Pattern Recognition June

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brPage 2br Detecting the Signs a b Figure 1 a sho...

Course Notes Week Math C Applied Numerical Linear Algebra Lecture Steepest Descent The connection with Lanczos iteration and the CG was not originally known

Course Notes Week Math C Applied Numerical Linear Algebra Lecture Steepest Descent The connection with Lanczos iteration and the CG was not originally known

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CG was originally derived in a manner closer to t...

Generic descent algorithm Generalization to multiple dimensions Problems of descent methods possible improvements Fixes Local minima Lecture descent methods Gradient descent reminder fx fm gues

Generic descent algorithm Generalization to multiple dimensions Problems of descent methods possible improvements Fixes Local minima Lecture descent methods Gradient descent reminder fx fm gues

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This can be generalized to any dimension brPage 9...

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