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156
Voted
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 4 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
155
Voted
ICAC
2007
IEEE
15 years 10 months ago
Adaptive Learning of Metric Correlations for Temperature-Aware Database Provisioning
This paper introduces a transparent self-configuring architecture for automatic scaling with temperature awareness in the database tier of a dynamic content web server. We use a ...
Saeed Ghanbari, Gokul Soundararajan, Jin Chen, Cri...
111
Voted
ECML
2000
Springer
15 years 8 months ago
Metric-Based Inductive Learning Using Semantic Height Functions
In the present paper we propose a consistent way to integrate syntactical least general generalizations (lgg's) with semantic evaluation of the hypotheses. For this purpose we...
Zdravko Markov, Ivo Marinchev
226
Voted
TSE
2010
140views more  TSE 2010»
15 years 2 months ago
Learning a Metric for Code Readability
—In this paper, we explore the concept of code readability and investigate its relation to software quality. With data collected from 120 human annotators, we derive associations...
Raymond P. L. Buse, Westley Weimer
166
Voted
CVPR
2010
IEEE
15 years 11 months ago
Data Fusion through Cross-modality Metric Learning using Similarity-Sensitive Hashing
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...