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» A Theory for Memory-Based Learning
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NIPS
2008
15 years 7 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
IFIP12
2004
15 years 7 months ago
An Adaptive Assessment System to Evaluate Student Ability Level
: The experience from years of development and use, the advance of technology, and the development of authoring tools for questions and tests has resulted in a sophisticated, compu...
Antonella Carbonaro, Giorgio Casadei, Simone Riccu...
NIPS
1993
15 years 7 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
15 years 6 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
ML
2008
ACM
15 years 6 months ago
A linear fit gets the correct monotonicity directions
Let f be a function on Rd that is monotonic in every variable. There are 2d possible assignments to the directions of monotonicity (two per variable). We provide sufficient condit...
Malik Magdon-Ismail, Joseph Sill