Results 1 - 10 of 6,453

A Sieve Algorithm for the Shortest Lattice Vector Problem

by Miklós Ajtai , Ravi Kumar, et al. , 2001
"... We present a randomized 2 O(n) time algorithm to compute a shortest non-zero vector in an n-dimensional rational lattice. The best known time upper bound for this problem was 2 O(n log n) ..."
Abstract - Cited by 211 (3 self) - Add to MetaCart
We present a randomized 2 O(n) time algorithm to compute a shortest non-zero vector in an n-dimensional rational lattice. The best known time upper bound for this problem was 2 O(n log n)

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 ...

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

Routing in a Delay Tolerant Network

by Sushant Jain, Kevin Fall, Rabin Patra , 2004
"... We formulate the delay-tolerant networking routing problem, where messages are to be moved end-to-end across a connectivity graph that is time-varying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property that no con ..."
Abstract - Cited by 621 (8 self) - Add to MetaCart
We formulate the delay-tolerant networking routing problem, where messages are to be moved end-to-end across a connectivity graph that is time-varying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property

Fast approximate nearest neighbors with automatic algorithm configuration

by Marius Muja, David G. Lowe - In VISAPP International Conference on Computer Vision Theory and Applications , 2009
"... nearest-neighbors search, randomized kd-trees, hierarchical k-means tree, clustering. For many computer vision problems, the most time consuming component consists of nearest neighbor matching in high-dimensional spaces. There are no known exact algorithms for solving these high-dimensional problems ..."
Abstract - Cited by 455 (2 self) - Add to MetaCart
nearest-neighbors search, randomized kd-trees, hierarchical k-means tree, clustering. For many computer vision problems, the most time consuming component consists of nearest neighbor matching in high-dimensional spaces. There are no known exact algorithms for solving these high

A general approximation technique for constrained forest problems

by Michel X. Goemans, David P. Williamson - SIAM J. COMPUT. , 1995
"... We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles, or paths satisfying certain requirements. In particular, many basic combinatorial optimization proble ..."
Abstract - Cited by 414 (21 self) - Add to MetaCart
-collecting traveling salesman or Steiner tree problems, we obtain 2-approximation algorithms, therefore improving the previously best-known performance guarantees of 2.5 and 3, respectively [Math. Programming, 59 (1993), pp. 413-420].

Technological pedagogical content knowledge: A framework for integrating technology in teacher knowledge.

by M J Koehler , P Mishra - Teachers College Record, , 2006
"... Abstract This paper describes a framework for teacher knowledge for technology integration called technological pedagogical content knowledge (originally TPCK, now known as TPACK, or technology, pedagogy, and content knowledge). This framework builds on Lee Shulman's construct of pedagogical c ..."
Abstract - Cited by 420 (19 self) - Add to MetaCart
Abstract This paper describes a framework for teacher knowledge for technology integration called technological pedagogical content knowledge (originally TPCK, now known as TPACK, or technology, pedagogy, and content knowledge). This framework builds on Lee Shulman's construct of pedagogical

A comparative study of energy minimization methods for Markov random fields

by Richard Szeliski, Ramin Zabih, Daniel Scharstein, Olga Veksler, Aseem Agarwala, Carsten Rother, et al. - IN ECCV , 2006
"... One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with some quantity such as depth or texture. While many such problems can be elegantly expressed in the language of Markov Ran ..."
Abstract - Cited by 415 (36 self) - Add to MetaCart
the solution quality and running time of several common energy minimization algorithms. We investigate three promising recent methods—graph cuts, LBP, and tree-reweighted message passing—as well as the well-known older iterated conditional modes (ICM) algorithm. Our benchmark problems are drawn from published

The Determinants of Credit Spread Changes.

by Pierre Collin-Dufresne , Robert S Goldstein , J Spencer Martin , Gurdip Bakshi , Greg Bauer , Dave Brown , Francesca Carrieri , Peter Christoffersen , Susan Christoffersen , Greg Duffee , Darrell Duffie , Vihang Errunza , Gifford Fong , Mike Gallmeyer , Laurent Gauthier , Rick Green , John Griffin , Jean Helwege , Kris Jacobs , Chris Jones , Andrew Karolyi , Dilip Madan , David Mauer , Erwan Morellec , Federico Nardari , N R Prabhala , Tony Sanders , Sergei Sarkissian , Bill Schwert , Ken Singleton , Chester Spatt , René Stulz - Journal of Finance , 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
Abstract - Cited by 422 (2 self) - Add to MetaCart
-grade bond yield changes on Treasury yield changes and stock returns (see Kwan (1996)) we find that the R 2 falls to five percent when the dependent variable is credit spread changes. Hence, while much is known about yield changes, we have very limited knowledge about the determinants of credit spread

Adaptive Wavelet Thresholding for Image Denoising and Compression

by S. Grace Chang, Bin Yu, Martin Vetterli - IEEE TRANSACTIONS ON IMAGE PROCESSING , 2000
"... The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution (GGD) widely used in image processing ..."
Abstract - Cited by 362 (4 self) - Add to MetaCart
with the image assumed known. It also outperforms Donoho and Johnstone's SureShrink most of the time. The second part
Results 1 - 10 of 6,453