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A Probabilistic Framework for Semi-Supervised Clustering

A Probabilistic Framework for Semi-Supervised Clustering

A Probabilistic Framework for Semi-Supervised Clustering. Sugato Basu Mikhail Bilenko Raymond J. Mooney Dept ment of Computer Sciences University of Texas at Austin Presented by Jingting Zeng. Outline. Introduction Background Algorithm Experiments Conclusion.

By landen
(137 views)

Contact address E-mail: Ferdous.Sohel@infotech.monash.au

Contact address E-mail: Ferdous.Sohel@infotech.monash.au

G. B. B. C. P. Q. D. A. K. H. A. D. BK. BA. s. r. E. F. Region 2. Region 1. Region 3. 1 pel. Shape Codec. WHAT IS THE MINIMUM DISTANCE OF POINT B FROM LINE AD ??. OBJECTIVE of this WORK. QUALITY. Which one is BETTER ?.

By lucine
(96 views)

Operationally Optimal VERTEX-BASED SHAPE CODING

Operationally Optimal VERTEX-BASED SHAPE CODING

Operationally Optimal VERTEX-BASED SHAPE CODING. Guido M. Schuster, Gerry Melnikov, and Aggelos K. Katesaggelos. Outline. Introduction Rate and Distortion Directed Acyclic Graph Formulation Experimental Results and Comparisons Conclusions. Introduction.

By cecil
(77 views)

PATTERN COMPARISON TECHNIQUES

PATTERN COMPARISON TECHNIQUES

PATTERN COMPARISON TECHNIQUES. Test Pattern:. Reference Pattern:. 4.2 SPEECH (ENDPIONT) DETECTION. 4.3 DISTORTION MEASURES-MATHEMATICAL CONSIDERATIONS. x and y: two feature vectors defined on a vector space X. The properties of metric or distance function d:.

By mira-whitehead
(126 views)

Automatic Floating-Point to Fixed-Point Transformations

Automatic Floating-Point to Fixed-Point Transformations

Automatic Floating-Point to Fixed-Point Transformations. Kyungtae Han, Alex G. Olson, Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin. 2006 Asilomar Conference on Signals, Systems, and Computers. October 30th, 2006. Outline. Introduction

By moana-christian
(106 views)

Rate Distortion Theory

Rate Distortion Theory

Rate Distortion Theory. Introduction. The description of an arbitrary real number requires an infinite number of bits, so a finite representation of a continuous random variable can never be perfect.

By amcdowell
(0 views)

Distance-Reciprocal Distortion measure for Binary Document Images

Distance-Reciprocal Distortion measure for Binary Document Images

Distance-Reciprocal Distortion measure for Binary Document Images. Author : Haiping Lu, Alex C. Kot, Yun Q. Shi Source : Signal Processing Letters, IEEE , Volume: 11 , Issue: 2 , Feb. 2004 Pages:228 - 231 Adviser : Chin-Chen Chang Speaker : Ming-Hui Ho

By wandatomlinson
(0 views)


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