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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 3 months ago
Applying both positive and negative selection to supervised learning for anomaly detection
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Xiaoshu Hang, Honghua Dai
JMLR
2002
133views more  JMLR 2002»
13 years 9 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
CIARP
2007
Springer
14 years 4 months ago
Image Segmentation Using Automatic Seeded Region Growing and Instance-Based Learning
Segmentation through seeded region growing is widely used because it is fast, robust and free of tuning parameters. However, the seeded region growing algorithm requires an automat...
Octavio Gómez, Jesús A. Gonzá...
ICPR
2008
IEEE
14 years 11 months ago
Fuzzy rule selection using Iterative Rule Learning for speech data classification
Fuzzy rule base systems have been successfully used for pattern classification. These systems focus on generating a rule-base from numerical input data. The resulting rule-base ca...
Bin Ma, Chng Eng Siong, Haizhou Li, Omid Dehzangi
CIARP
2009
Springer
14 years 4 months ago
Learning Relational Grammars from Sequences of Actions
Many tasks can be described by sequences of actions that normally exhibit some form of structure and that can be represented by a grammar. This paper introduces FOSeq, an algorithm...
Blanca Vargas-Govea, Eduardo F. Morales