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KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 5 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
163
Voted
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
16 years 5 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
133
Voted
KDD
2005
ACM
166views Data Mining» more  KDD 2005»
16 years 5 months ago
A general model for clustering binary data
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Tao Li
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 5 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 5 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher