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ECML
2006
Springer
15 years 10 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...
EDBTW
2006
Springer
15 years 10 months ago
Window Specification over Data Streams
Several query languages have been proposed for managing data streams in modern monitoring applications. Continuous queries expressed in these languages usually employ windowing con...
Kostas Patroumpas, Timos K. Sellis
ISCA
1998
IEEE
135views Hardware» more  ISCA 1998»
15 years 10 months ago
Branch Prediction Based on Universal Data Compression Algorithms
Data compression and prediction are closely related. Thus prediction methods based on data compression algorithms have been suggested for the branch prediction problem. In this wo...
Eitan Federovsky, Meir Feder, Shlomo Weiss
ACMACE
2008
ACM
15 years 8 months ago
Designing location-based mobile games with a purpose: collecting geospatial data with CityExplorer
The games with a purpose paradigm proposed by Luis von Ahn [9] is a new approach for game design where useful but boring tasks, like labeling a random image found in the web, are ...
Sebastian Matyas, Christian Matyas, Christoph Schl...
ASUNAM
2010
IEEE
15 years 8 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen