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» Learning a Classification Model for Segmentation
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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 5 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
ACTAC
2006
126views more  ACTAC 2006»
15 years 5 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...
ECML
2006
Springer
15 years 8 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 5 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
IVC
2002
143views more  IVC 2002»
15 years 4 months ago
Towards the automatic analysis of complex human body motions
The classification of human body motion is an integral component for the automatic interpretation of video sequences. In a first part we present an effective approach that uses mi...
Jens Rittscher, Andrew Blake, Stephen J. Roberts