Results 1 - 10 of 36,540

A Data Locality Optimizing Algorithm

by Michael E. Wolf, Monica S. Lam , 1991
"... This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory that unifi ..."
Abstract - Cited by 804 (16 self) - Add to MetaCart
that unifies the various transforms as unimodular matrix transformations. The algorithm has been implemented in the SUIF (Stanford University Intermediate Format) compiler, and is successful in optimizing codes such as matrix multiplication, successive over-relaxation (SOR), LU decomposition without pivoting

An Overview of Evolutionary Algorithms in Multiobjective Optimization

by Carlos M. Fonseca, Peter J. Fleming - Evolutionary Computation , 1995
"... The application of evolutionary algorithms (EAs) in multiobjective optimization is currently receiving growing interest from researchers with various backgrounds. Most research in this area has understandably concentrated on the selection stage of EAs, due to the need to integrate vectorial performa ..."
Abstract - Cited by 492 (13 self) - Add to MetaCart
The application of evolutionary algorithms (EAs) in multiobjective optimization is currently receiving growing interest from researchers with various backgrounds. Most research in this area has understandably concentrated on the selection stage of EAs, due to the need to integrate vectorial

Dynamic programming algorithm optimization for spoken word recognition

by Hiroaki Sakoe, Seibi Chiba - IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING , 1978
"... This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms, are der ..."
Abstract - Cited by 788 (3 self) - Add to MetaCart
words in different The effective slope constraint characteristic is qualitatively analyzed, and the optimum slope constraint condition is determined through experiments. The optimized algorithm is then extensively subjected to experimentat comparison with various DP-algorithms, previously applied

Toward optimal feature selection

by Daphne Koller, Mehran Sahami - In 13th International Conference on Machine Learning , 1995
"... In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for de ning the theoretically optimal, but computationally intractable, method for feature subset selection is presented. We show that our goal should be to eliminate a feature if it g ..."
Abstract - Cited by 480 (9 self) - Add to MetaCart
if it gives us little or no additional information beyond that subsumed by the remaining features. In particular, this will be the case for both irrelevant and redundant features. We then give an e cient algorithm for feature selection which computes an approximation to the optimal feature selection criterion

Depth-first Iterative-Deepening: An Optimal Admissible Tree Search

by Richard E. Korf - Artificial Intelligence , 1985
"... The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw-deepening a ..."
Abstract - Cited by 527 (24 self) - Add to MetaCart
The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw

Multimodality Image Registration by Maximization of Mutual Information

by Frederik Maes, André Collignon, Dirk Vandermeulen, Guy Marchal, Paul Suetens - IEEE TRANSACTIONS ON MEDICAL IMAGING , 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
Abstract - Cited by 791 (10 self) - Add to MetaCart
A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence

Minimum Error Rate Training in Statistical Machine Translation

by Franz Josef Och , 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
Abstract - Cited by 757 (7 self) - Add to MetaCart
Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training

Good features to track

by Jianbo Shi, Carlo Tomasi , 1994
"... No feature-based vision system can work unless good features can be identified and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature se ..."
Abstract - Cited by 2050 (14 self) - Add to MetaCart
selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world. These methods are based on a new tracking algorithm that extends previous

Comparison of Multiobjective Evolutionary Algorithms: Empirical Results

by Eckart Zitzler, Lothar Thiele, Kalyanmoy Deb , 2000
"... In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in conver ..."
Abstract - Cited by 628 (41 self) - Add to MetaCart
In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly

Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks

by Ros Tassiulas, Anthony Ephremides - IEEE Transactions on Automatic Control , 1992
"... Abstruct-The stability of a queueing network with interdependent servers is considered. The dependency of servers is described by the definition of their subsets that can be activated simultaneously. Multihop packet radio networks (PRN’s) provide a motivation for the consideration of this system. We ..."
Abstract - Cited by 949 (19 self) - Add to MetaCart
. We study the problem of scheduling the server activation under the constraints imposed by the dependency among them. The performance criterion of a scheduling policy m is its throughput that is characterized by its stability region C,, that is, the set of vectors of arrival rates for which the system
Results 1 - 10 of 36,540