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SAC
2006
ACM
16 years 27 days ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
AUSAI
2003
Springer
16 years 5 days ago
Choosing Learning Algorithms Using Sign Tests with High Replicability
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Remco R. Bouckaert
ISCAS
2002
IEEE
153views Hardware» more  ISCAS 2002»
15 years 12 months ago
Biological learning modeled in an adaptive floating-gate system
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
Christal Gordon, Paul E. Hasler
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 11 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
VIP
2003
15 years 8 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin