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115
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ECML
2006
Springer
15 years 4 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
127
Voted
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
15 years 4 months ago
A specification-based fitness function for evolutionary testing of object-oriented programs
Encapsulation of states in object-oriented programs hinders the search for test data using evolutionary testing. As client code is oblivious to the internal state of a server obje...
Yoonsik Cheon, Myoung Kim
146
Voted
EMNLP
2011
14 years 26 days ago
Training a Log-Linear Parser with Loss Functions via Softmax-Margin
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...
Michael Auli, Adam Lopez
109
Voted
AUSAI
2010
Springer
14 years 10 months ago
A Heuristic on Effective and Efficient Clustering on Uncertain Objects
We study the problem of clustering uncertain objects whose locations are uncertain and described by probability density functions. We analyze existing pruning algorithms and experi...
Edward Hung, Lei Xu, Chi-Cheong Szeto
108
Voted
ICPR
2004
IEEE
16 years 2 months ago
Selecting Canonical Views for View-Based 3-D Object Recognition
Given a collection of sets of 2-D views of 3-D objects and a similarity measure between them, we present a method for summarizing the sets using a small subset called a bounded ca...
Ali Shokoufandeh, Jeff Abrahamson, M. Fatih Demirc...