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» The Shortcut Problem - Complexity and Approximation
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132
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UAI
1998
15 years 5 months ago
Large Deviation Methods for Approximate Probabilistic Inference
We study two-layer belief networks of binary random variables in which the conditional probabilities Pr childjparents depend monotonically on weighted sums of the parents. In larg...
Michael J. Kearns, Lawrence K. Saul
137
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CSUR
1999
114views more  CSUR 1999»
15 years 3 months ago
Directions for Research in Approximate System Analysis
useful for optimizing compilers [15], partial evaluators [11], abstract debuggers [1], models-checkers [2], formal verifiers [13], etc. The difficulty of the task comes from the fa...
Patrick Cousot
130
Voted
TSMC
1998
135views more  TSMC 1998»
15 years 3 months ago
Universal stabilization using control Lyapunov functions, adaptive derivative feedback, and neural network approximators
— In this paper, the problem of stabilization of unknown nonlinear dynamical systems is considered. An adaptive feedback law is constructed that is based on the switching adaptiv...
Elias B. Kosmatopoulos
152
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TODS
2002
92views more  TODS 2002»
15 years 3 months ago
Searching in metric spaces with user-defined and approximate distances
Metric access methods (MAMs), such as the M-tree, are powerful index structures for supporting ty queries on metric spaces, which represent a common abstraction for those searchin...
Paolo Ciaccia, Marco Patella
97
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CORR
2011
Springer
153views Education» more  CORR 2011»
14 years 10 months ago
Partially Linear Bayesian Estimation with Application to Sparse Approximations
—We address the problem of estimating a random vector X from two sets of measurements Y and Z, such that the estimator is linear in Y . We show that the partially linear minimum ...
Tomer Michaeli, Daniel Sigalov, Yonina C. Eldar