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» Kolmogorov Complexity and Model Selection
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MCU
2007
95views Hardware» more  MCU 2007»
13 years 6 months ago
Slightly Beyond Turing's Computability for Studying Genetic Programming
Inspired by genetic programming (GP), we study iterative algorithms for non-computable tasks and compare them to naive models. This framework justifies many practical standard tri...
Olivier Teytaud
ICANN
2009
Springer
13 years 11 months ago
Modelling Image Complexity by Independent Component Analysis, with Application to Content-Based Image Retrieval
Abstract. Estimating the degree of similarity between images is a challenging task as the similarity always depends on the context. Because of this context dependency, it seems qui...
Jukka Perkiö, Aapo Hyvärinen
STACS
2005
Springer
13 years 10 months ago
Kolmogorov-Loveland Randomness and Stochasticity
An infinite binary sequence X is Kolmogorov-Loveland (or KL) random if there is no computable non-monotonic betting strategy that succeeds on X in the sense of having an unbounde...
Wolfgang Merkle, Joseph S. Miller, André Ni...
NIPS
2003
13 years 6 months ago
From Algorithmic to Subjective Randomness
We explore the phenomena of subjective randomness as a case study in understanding how people discover structure embedded in noise. We present a rational account of randomness per...
Thomas L. Griffiths, Joshua B. Tenenbaum
DCC
2006
IEEE
14 years 4 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley