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Practical Byzantine fault tolerance

by Miguel Castro, Barbara Liskov , 1999
"... This paper describes a new replication algorithm that is able to tolerate Byzantine faults. We believe that Byzantinefault-tolerant algorithms will be increasingly important in the future because malicious attacks and software errors are increasingly common and can cause faulty nodes to exhibit arbi ..."
Abstract - Cited by 673 (15 self) - Add to MetaCart
arbitrary behavior. Whereas previous algorithms assumed a synchronous system or were too slow to be used in practice, the algorithm described in this paper is practical: it works in asynchronous environments like the Internet and incorporates several important optimizations that improve the response time

The geometry of algorithms with orthogonality constraints

by Alan Edelman, Tomás A. Arias, Steven T. Smith - SIAM J. MATRIX ANAL. APPL , 1998
"... In this paper we develop new Newton and conjugate gradient algorithms on the Grassmann and Stiefel manifolds. These manifolds represent the constraints that arise in such areas as the symmetric eigenvalue problem, nonlinear eigenvalue problems, electronic structures computations, and signal proces ..."
Abstract - Cited by 640 (1 self) - Add to MetaCart
of previously unrelated algorithms. It is our hope that developers of new algorithms and perturbation theories will benefit from the theory, methods, and examples in this paper.

Linear pattern matching algorithms

by Peter Weiner - IN PROCEEDINGS OF THE 14TH ANNUAL IEEE SYMPOSIUM ON SWITCHING AND AUTOMATA THEORY. IEEE , 1972
"... In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but sub-optimal algorithms. In this paper, we introduce an interesting data structure called a bi-tree. A linear ti ..."
Abstract - Cited by 546 (0 self) - Add to MetaCart
In 1970, Knuth, Pratt, and Morris [1] showed how to do basic pattern matching in linear time. Related problems, such as those discussed in [4], have previously been solved by efficient but sub-optimal algorithms. In this paper, we introduce an interesting data structure called a bi-tree. A linear

An Algorithm for Tracking Multiple Targets

by Donald B. Reid - IEEE Transactions on Automatic Control , 1979
"... Abstract—An algorithm for tracking multiple targets In a cluttered algorithms. Clustering is the process of dividing the entire environment Is developed. The algorithm Is capable of Initiating tracks, set of targets and measurements into independent groups accounting for false or m[~clngreports, and ..."
Abstract - Cited by 596 (0 self) - Add to MetaCart
target, or that the measurement Is false. nally, it is desirable for an algorithm to be recursive so Target states are estimated from each such da*a-as.soclatloo hypothesis that all the previous data do not have to be reprocessed using a 1C~InlQnfilter. As mere measurements are received, the probabill

Analysis of Recommendation Algorithms for E-Commerce

by Badrul Sarwar, George Karypis, Joseph Konstan, John Rield , 2000
"... Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in E-Commerce nowadays. In this paper, we investigate several techniques for analyzing large-scale pu ..."
Abstract - Cited by 523 (22 self) - Add to MetaCart
-scale purchase and preference data for the purpose of producing useful recommendations to customers. In particular, we apply a collection of algorithms such as traditional data mining, nearest-neighbor collaborative ltering, and dimensionality reduction on two dierent data sets. The rst data set was derived from

Algorithms for Non-negative Matrix Factorization

by Daniel D. Lee, H. Sebastian Seung - In NIPS , 2001
"... Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed. They differ only slightly in the multiplicative factor used in the update rules. One algorithm can be shown to minim ..."
Abstract - Cited by 1246 (5 self) - Add to MetaCart
Non-negative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed. They differ only slightly in the multiplicative factor used in the update rules. One algorithm can be shown

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

Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming

by M. X. Goemans, D.P. Williamson - Journal of the ACM , 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
Abstract - Cited by 1211 (13 self) - Add to MetaCart
the solution to a nonlinear programming relaxation. This relaxation can be interpreted both as a semidefinite program and as an eigenvalue minimization problem. The best previously known approximation algorithms for these problems had performance guarantees of ...

On the algorithmic implementation of multi-class kernel-based vector machines

by Koby Crammer, Yoram Singer, Nello Cristianini, John Shawe-taylor, Bob Williamson - Journal of Machine Learning Research
"... In this paper we describe the algorithmic implementation of multiclass kernel-based vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic ob ..."
Abstract - Cited by 559 (13 self) - Add to MetaCart
In this paper we describe the algorithmic implementation of multiclass kernel-based vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic

Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach

by Eckart Zitzler, Lothar Thiele - IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION , 1999
"... Evolutionary algorithms (EA’s) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a singl ..."
Abstract - Cited by 813 (22 self) - Add to MetaCart
Evolutionary algorithms (EA’s) are often well-suited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a
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