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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 7 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
ICCV
2007
IEEE
14 years 9 months ago
Discriminative Subsequence Mining for Action Classification
Recent approaches to action classification in videos have used sparse spatio-temporal words encoding local appearance around interesting movements. Most of these approaches use a ...
Sebastian Nowozin, Gökhan H. Bakir, Koji Tsud...
ICTAI
2003
IEEE
14 years 21 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
KDD
1997
ACM
106views Data Mining» more  KDD 1997»
13 years 11 months ago
Clustering Sequences of Complex Objects
Sequential Data This paper is about the unsuperviseddiscovery of patterns in sequencesof compositeobjects. A compositeobject may be describedas a sequenceof other, simpler data. In...
A. Ketterlin
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
13 years 11 months ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh