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» Learning Monotonic Linear Functions
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PLDI
2010
ACM
14 years 7 months ago
Complete Functional Synthesis
Synthesis of program fragments from specifications can make programs easier to write and easier to reason about. To integrate synthesis into programming languages, synthesis algor...
Viktor Kuncak, Mika l Mayer, Ruzica Piskac, Philip...
VLSISP
2010
254views more  VLSISP 2010»
13 years 8 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
TEC
2008
115views more  TEC 2008»
13 years 9 months ago
Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
ALT
2010
Springer
13 years 11 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
GECCO
2009
Springer
200views Optimization» more  GECCO 2009»
14 years 4 months ago
Apply ant colony optimization to Tetris
Tetris is a falling block game where the player’s objective is to arrange a sequence of different shaped tetrominoes smoothly in order to survive. In the intelligence games, ag...
Xingguo Chen, Hao Wang, Weiwei Wang, Yinghuan Shi,...