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abFigure 1a You can either see as figure a black goblet standing in front of a white groundor you can see two white faces looking at each other in front of a black groundb Four Ku Klux Klansmen. induseduorg 105 MEASURING CONSUMERS PERCEP TION OF THE ASSOCIATION BETWEEN BRAND AND CE LEBRITY ENDORSER Parkee M Bhatnagar Research Scholar MM Institute of Mana gement MM University Mullana Ambala Dr Amit Mittal Professor MM Institute of Manageme nt 1

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 Media Contacts Mr. Sanjay Shukla, COO, Percept One Tel: +91-22-30428822 / +91-11-39998405 Ph: +91-9810315432 Email: sanjay.shukla@pdmindia.com  We presented this project at several occasions including CUNY psycholinguistic supper, Penn Linguistic Colloquium 35, WCCFL 29, and the phonology study group at the University of California, Santa C Outline. Motivation. Multiple Instance Learning (MIL). Diverse Density. Single Point Concept. Disjunctive Point Concept. SVM Algorithms for MIL. Single Instance Learner (SIL). Sparse MIL. mi-SVM. MI-SVM. Methods. There are three major components of a class definition.. 1. Instance . variables . (also called . fields in the API documentation).. 2. Constructors. .. 3. Methods. .. The following notes will show how to write code for a user designed class, dealing with each of those three parts in order. . An example of something.. I know it is cold out. ;. . f. or . instance. , there is snow outside.. Do you have a lot of Christmas presents to play with now that it is January? For . instance. , video games and Legos?. 294such percep-norms such the of tardy. Hopefully, future ofChina whichbased on largely or the pro-should be willing a should thecanabout prevalence and of about for Tai-2An colonial records women lea = number of vertices – number of edges + number of faces. Or in short-hand,. . . = |V| - |E| + |F|. where V = set of vertices. E = set of edges. F = set of faces. of a series of preparatory lectures for the Fall 2013 online course MATH:7450 (22M:305) Topics in Topology: Scientific and Engineering Applications of Algebraic Topology. Target Audience: Anyone interested in . An example of something.. I know it is cold out. ;. . f. or . instance. , there is snow outside.. Do you have a lot of Christmas presents to play with now that it is January? For . instance. , video games and Legos?. 1. Nearest Neighbor Learning. Classify based on local similarity. Ranges from simple . nearest neighbor . to case-based and analogical reasoning. Use local information near the current query instance to decide the classification of that instance. Outline. The importance of instance selection. Rough set theory. Fuzzy-rough sets. Fuzzy-rough instance selection. Experimentation. Conclusion. Knowledge discovery. The problem of too much data. Requires storage. Wei Zhang, . Hongzhi Li. , Chong-Wah Ngo, Shih-Fu Chang. City Univeristy of Hong Kong. Columbia University. 1. Visual Instance Mining. visual . instance. : a specific visual entity. object (car, apple, flower). The characteristic roots of the (. p×p. ) matrix . A. are the solutions of the following determinant equation: . Laplace expansion. is used to write the characteristic polynomial as. :. Since (.