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KDD
2010
ACM
257views Data Mining» more  KDD 2010»
15 years 10 months ago
Multi-task learning for boosting with application to web search ranking
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
ADBIS
2007
Springer
143views Database» more  ADBIS 2007»
16 years 28 days ago
Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
Rayner Alfred, Dimitar Kazakov
ICIP
2004
IEEE
16 years 8 months ago
Multisensor raster and vector data fusion based on uncertainty modeling
We propose a new methodology for fusing temporally changing multisensor raster and vector data by developing a spatially and temporally varying uncertainty model of acquired and t...
Sang-Chul Lee, Peter Bajcsy
TSP
2011
96views more  TSP 2011»
15 years 1 months ago
A Signal Processing Approach to Fourier Analysis of Ranking Data: The Importance of Phase
—Ranking data is a type of data obtained in some elections, in customer surveys, as well as from web search results. Such data may be considered as a type of signal defined on t...
Ramakrishna Kakarala
PKDD
2007
Springer
109views Data Mining» more  PKDD 2007»
16 years 25 days ago
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains
Abstract. When seeking for small clusters it is very intricate to distinguish between incidental agglomeration of noisy points and true local patterns. We present the PAMALOC algor...
Frank Höppner, Mirko Böttcher