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JMLR
2006
99views more  JMLR 2006»
15 years 2 months ago
Worst-Case Analysis of Selective Sampling for Linear Classification
A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
RAS
2010
106views more  RAS 2010»
15 years 25 days ago
A developmental algorithm for ocular-motor coordination
This paper presents a model of ocular-motor development, inspired by ideas and data from developmental psychology. The learning problem concerns the growth of the transform betwee...
F. Chao, M. H. Lee, J. J. Lee
128
Voted
IEEEPACT
1998
IEEE
15 years 6 months ago
A Matrix-Based Approach to the Global Locality Optimization Problem
Global locality analysis is a technique for improving the cache performance of a sequence of loop nests through a combination of loop and data layout optimizations. Pure loop tran...
Mahmut T. Kandemir, Alok N. Choudhary, J. Ramanuja...
120
Voted
SAC
2002
ACM
15 years 2 months ago
Automatic code generation for executing tiled nested loops onto parallel architectures
This paper presents a novel approach for the problem of generating tiled code for nested for-loops using a tiling transformation. Tiling or supernode transformation has been widel...
Georgios I. Goumas, Maria Athanasaki, Nectarios Ko...
ALT
2010
Springer
15 years 4 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang