Results 1  10
of
281,704
Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming
 Journal of the ACM
, 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (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
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (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
Random cutting and records in deterministic and random trees
 ALG
, 2006
"... We study random cutting down of a rooted tree and show that the number of cuts is equal (in distribution) to the number of records in the tree when edges (or vertices) are assigned random labels. Limit theorems are given for this number, in particular when the tree is a random conditioned Galton–Wat ..."
Abstract

Cited by 48 (9 self)
 Add to MetaCart
We study random cutting down of a rooted tree and show that the number of cuts is equal (in distribution) to the number of records in the tree when edges (or vertices) are assigned random labels. Limit theorems are given for this number, in particular when the tree is a random conditioned Galton
Graphcut textures: Image and video synthesis using graph cuts
 ACM Transactions on Graphics, SIGGRAPH 2003
, 2003
"... This banner was generated by merging the source images in Figure 6 using our interactive texture merging technique. In this paper we introduce a new algorithm for image and video texture synthesis. In our approach, patch regions from a sample image or video are transformed and copied to the output a ..."
Abstract

Cited by 490 (9 self)
 Add to MetaCart
and then stitched together along optimal seams to generate a new (and typically larger) output. In contrast to other techniques, the size of the patch is not chosen apriori, but instead a graph cut technique is used to determine the optimal patch region for any given offset between the input and output texture
Randomized Cuts for 3D Mesh Analysis
"... The goal of this paper is to investigate a new shape analysis method based on randomized cuts of 3D surface meshes. The general strategy is to generate a random set of mesh segmentations and then to measure how often each edge of the mesh lies on a segmentation boundary in the randomized set. The re ..."
Abstract

Cited by 60 (2 self)
 Add to MetaCart
The goal of this paper is to investigate a new shape analysis method based on randomized cuts of 3D surface meshes. The general strategy is to generate a random set of mesh segmentations and then to measure how often each edge of the mesh lies on a segmentation boundary in the randomized set
Proof verification and hardness of approximation problems
 IN PROC. 33RD ANN. IEEE SYMP. ON FOUND. OF COMP. SCI
, 1992
"... We show that every language in NP has a probablistic verifier that checks membership proofs for it using logarithmic number of random bits and by examining a constant number of bits in the proof. If a string is in the language, then there exists a proof such that the verifier accepts with probabilit ..."
Abstract

Cited by 797 (39 self)
 Add to MetaCart
We show that every language in NP has a probablistic verifier that checks membership proofs for it using logarithmic number of random bits and by examining a constant number of bits in the proof. If a string is in the language, then there exists a proof such that the verifier accepts
Efficient belief propagation for early vision
 In CVPR
, 2004
"... Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advances are often still too slow for practical u ..."
Abstract

Cited by 515 (8 self)
 Add to MetaCart
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advances are often still too slow for practical
APPENDIX TO RANDOM CUTTING AND RECORDS IN DETERMINISTIC AND RANDOM TREES
"... This is an appendix to [3], and we use the notation there. In particular, if T is a rooted tree, X(T) denotes the random number of (edge) cuttings needed to destroy the tree completely, or equivalently, the number of records in the tree when the edges have random labels. Further, Tn is a random cond ..."
Abstract
 Add to MetaCart
This is an appendix to [3], and we use the notation there. In particular, if T is a rooted tree, X(T) denotes the random number of (edge) cuttings needed to destroy the tree completely, or equivalently, the number of records in the tree when the edges have random labels. Further, Tn is a random
A comparative study of energy minimization methods for Markov random fields
 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
Random Fields (MRF’s), the resulting energy minimization problems were widely viewed as intractable. Recently, algorithms such as graph cuts and loopy belief propagation (LBP) have proven to be very powerful: for example, such methods form the basis for almost all the topperforming stereo methods
Analysis of a random cut test instance generator for the TSP
 IN COMPLEXITY IN NUMERICAL OPTIMIZATION, P. PARDALOS, ED. SINGAPORE: WORLD SCIENTIFIC
, 1993
"... Test Instance Generators (TIG’s) are important to evaluate heuristic procedures for NPhard problems. We analyze a TIG in use for the TSP. This TIG, due to Pilcher and Rardin, is based on a random cut method. We show that it generates a class of instances of intermediate complexity: not as hard as t ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
Test Instance Generators (TIG’s) are important to evaluate heuristic procedures for NPhard problems. We analyze a TIG in use for the TSP. This TIG, due to Pilcher and Rardin, is based on a random cut method. We show that it generates a class of instances of intermediate complexity: not as hard
Robust Random Cut Forest Based Anomaly Detection On Streams
"... Abstract In this paper we focus on the anomaly detection problem for dynamic data streams through the lens of random cut forests. We investigate a robust random cut data structure that can be used as a sketch or synopsis of the input stream. We provide a plausible definition of nonparametric anoma ..."
Abstract
 Add to MetaCart
Abstract In this paper we focus on the anomaly detection problem for dynamic data streams through the lens of random cut forests. We investigate a robust random cut data structure that can be used as a sketch or synopsis of the input stream. We provide a plausible definition of non
Results 1  10
of
281,704