ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Quality control using scalar quality measures is standard practice in manufacturing. However, there are also quality measures that are determined at a large number of positions on ...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
There are many clustering tasks which are closely related in the real world, e.g. clustering the web pages of different universities. However, existing clustering approaches neglec...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
In this paper, we restudy the non-convex data factorization problems (regularized or not, unsupervised or supervised), where the optimization is confined in the nonnegative orthan...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures bu...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Given a large transaction database, association analysis is concerned with efficiently finding strongly related objects. Unlike traditional associate analysis, where relationships ...