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» Optimal Error Correction for Computationally Bounded Noise
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TIP
1998
128views more  TIP 1998»
13 years 8 months ago
Nonlinear wavelet image processing: variational problems, compression, and noise removal through wavelet shrinkage
This paper examines the relationship between wavelet-based image processing algorithms and variational problems. Algorithms are derived as exact or approximate minimizers of varia...
Antonin Chambolle, Ronald A. DeVore, Nam-Yong Lee,...
AIPS
2010
13 years 11 months ago
When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
Emma Brunskill
SPAA
2003
ACM
14 years 2 months ago
The effect of communication costs in solid-state quantum computing architectures
Quantum computation has become an intriguing technology with which to attack difficult problems and to enhance system security. Quantum algorithms, however, have been analyzed un...
Dean Copsey, Mark Oskin, Tzvetan S. Metodi, Freder...
JACM
2000
131views more  JACM 2000»
13 years 8 months ago
The soft heap: an approximate priority queue with optimal error rate
A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat...
Bernard Chazelle
RC
2007
83views more  RC 2007»
13 years 8 months ago
Computing the Pessimism of Inclusion Functions
Abstract. “Computing the pessimism” means bounding the overestimation produced by an inclusion function. There are two important distinctions with classical error analysis. Fir...
Gilles Chabert, Luc Jaulin