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98
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CVPR
2007
IEEE
16 years 2 months ago
Learning Visual Similarity Measures for Comparing Never Seen Objects
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
Eric Nowak, Frédéric Jurie
115
Voted
METRICS
1997
IEEE
15 years 4 months ago
Assessing Feedback Of Measurement Data: Relating Schlumberger Rps Practice To Learning Theory
Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...
Rini van Solingen, Egon Berghout, Erik Kooiman
112
Voted
ICST
2009
IEEE
14 years 10 months ago
Test Redundancy Measurement Based on Coverage Information: Evaluations and Lessons Learned
Measurement and detection of redundancy in test suites attempt to achieve test minimization which in turn can help reduce test maintenance costs, and to also ensure the integrity ...
Negar Koochakzadeh, Vahid Garousi, Frank Maurer
90
Voted
EMNLP
2009
14 years 10 months ago
Learning Term-weighting Functions for Similarity Measures
Measuring the similarity between two texts is a fundamental problem in many NLP and IR applications. Among the existing approaches, the cosine measure of the term vectors represen...
Wen-tau Yih
86
Voted
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
16 years 1 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...