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» Bias and Variance Approximation in Value Function Estimates
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TWC
2010
13 years 3 months ago
Reduced-Complexity Joint Baseband Compensation of Phase Noise and I/Q Imbalance for MIMO-OFDM Systems
The maximum likelihood estimate of the impulse response of a frequency-selective channel in the presence of phase noise and I/Q imbalance is derived. The complexity of the joint es...
Rabie Rabiei, Won Namgoong, Naofal Al-Dhahir
EPIA
2003
Springer
14 years 1 months ago
Evolutionary Neuroestimation of Fitness Functions
Abstract. One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in ...
Jesús S. Aguilar-Ruiz, Daniel Mateos, Domin...
UAI
2008
13 years 10 months ago
Observation Subset Selection as Local Compilation of Performance Profiles
Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of me...
Yan Radovilsky, Solomon Eyal Shimony
WSC
2001
13 years 10 months ago
Monte Carlo simulation approach to stochastic programming
Various stochastic programmingproblemscan be formulated as problems of optimization of an expected value function. Quite often the corresponding expectation function cannot be com...
Alexander Shapiro
ICML
2009
IEEE
14 years 9 months ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...