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» Learning Monotonic Linear Functions
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ICML
2004
IEEE
16 years 16 days ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ADCM
2006
74views more  ADCM 2006»
14 years 11 months ago
Linearly constrained reconstruction of functions by kernels with applications to machine learning
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
Robert Schaback, J. Werner
CORR
2010
Springer
141views Education» more  CORR 2010»
14 years 10 months ago
Learning Functions of Few Arbitrary Linear Parameters in High Dimensions
Let us assume that f is a continuous function defined on the unit ball of Rd , of the form f(x) = g(Ax), where A is a k×d matrix and g is a function of k variables for k ≪ d. ...
Massimo Fornasier, Karin Schnass, Jan Vybír...
FOCS
1996
IEEE
15 years 3 months ago
A Polynomial-Time Algorithm for Learning Noisy Linear Threshold Functions
Avrim Blum, Alan M. Frieze, Ravi Kannan, Santosh V...
STACS
2009
Springer
15 years 6 months ago
A Stronger LP Bound for Formula Size Lower Bounds via Clique Constraints
We introduce a new technique proving formula size lower bounds based on the linear programming bound originally introduced by Karchmer, Kushilevitz and Nisan [11] and the theory of...
Kenya Ueno