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» Analysis of Random Noise and Random Walk Algorithms
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COLT
2007
Springer
15 years 10 months ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak
ICCAD
2008
IEEE
129views Hardware» more  ICCAD 2008»
16 years 1 months ago
A capacitance solver for incremental variation-aware extraction
Abstract—Lithographic limitations and manufacturing uncertainties are resulting in fabricated shapes on wafer that are topologically equivalent, but geometrically different from ...
Tarek A. El-Moselhy, Ibrahim M. Elfadel, Luca Dani...
TCS
2010
15 years 3 months ago
Maximum likelihood analysis of algorithms and data structures
We present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelih...
Ulrich Laube, Markus E. Nebel
CORR
2007
Springer
134views Education» more  CORR 2007»
15 years 4 months ago
Rate-Constrained Wireless Networks with Fading Channels: Interference-Limited and Noise-Limited Regimes
A network of n wireless communication links is considered in a Rayleigh fading environment. It is assumed that each link can be active and transmit with a constant power P or rema...
Masoud Ebrahimi, Amir K. Khandani
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
16 years 5 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle