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Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics
, 1996
"... For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain has ..."
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Cited by 543 (13 self)
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has run for M steps, with M sufficiently large, the distribution governing the state of the chain approximates the desired distribution. Unfortunately it can be difficult to determine how large M needs to be. We describe a simple variant of this method that determines on its own when to stop
Chaff: Engineering an Efficient SAT Solver
, 2001
"... Boolean Satisfiability is probably the most studied of combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in Electronic Design Automation (EDA), as well ..."
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Cited by 1350 (18 self)
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as in Artificial Intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the DavisPutnam (DP) search algorithm
Active learning literature survey
, 2010
"... The key idea behind active learning is that a machine learning algorithm can achieve greater accuracy with fewer labeled training instances if it is allowed to choose the data from which is learns. An active learner may ask queries in the form of unlabeled instances to be labeled by an oracle (e.g., ..."
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Cited by 326 (1 self)
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.g., a human annotator). Active learning is wellmotivated in many modern machine learning problems, where unlabeled data may be abundant but labels are difficult, timeconsuming, or expensive to obtain. This report provides a general introduction to active learning and a survey of the literature
Finding motifs using random projections
, 2001
"... Pevzner and Sze [23] considered a precise version of the motif discovery problem and simultaneously issued an algorithmic challenge: find a motif Å of length 15, where each planted instance differs from Å in 4 positions. Whereas previous algorithms all failed to solve this (15,4)motif problem, Pevz ..."
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Cited by 285 (6 self)
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, Pevzner and Sze introduced algorithms that succeeded. However, their algorithms failed to solve the considerably more difficult (14,4), (16,5), and (18,6)motif problems. We introduce a novel motif discovery algorithm based on the use of random projections of the input’s substrings. Experiments
Annealed importance sampling
 In Statistics and Computing
, 2001
"... Abstract. Simulated annealing — moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions — has traditionally been used as an inexact method of handling isolated modes in Markov chain samplers. Here, it is shown how one can use the Markov chain t ..."
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Cited by 262 (5 self)
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transitions for such an annealing sequence to define an importance sampler. The Markov chain aspect allows this method to perform acceptably even for highdimensional problems, where finding good importance sampling distributions would otherwise be very difficult, while the use of importance weights ensures
Rapid, Accurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms
 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS
, 1993
"... Researchers have long sought genetic algorithms (GAs) that can solve difficult search, optimization, and machine learning problems quickly. Despite years of work on simple GAs and their variants it is still unknown how difficult a problem simple GAs can solve, how quickly they can solve it, and with ..."
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Cited by 120 (23 self)
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Researchers have long sought genetic algorithms (GAs) that can solve difficult search, optimization, and machine learning problems quickly. Despite years of work on simple GAs and their variants it is still unknown how difficult a problem simple GAs can solve, how quickly they can solve it
difficult labour
"... Background: Dystocia, difficult labour, is a common but also complex problem during childbirth. It can be attributed to either weak contractions of the uterus, a large infant, reduced capacity of the pelvis or combinations of these. Previous studies have indicated that there is a genetic component i ..."
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Background: Dystocia, difficult labour, is a common but also complex problem during childbirth. It can be attributed to either weak contractions of the uterus, a large infant, reduced capacity of the pelvis or combinations of these. Previous studies have indicated that there is a genetic component
How Difficult is it to Walk the Dog?
 IN PROC. 23RD EUROPEAN WORKSHOP ON COMPUTATIONAL GEOMETRY
, 2007
"... We study the complexity of computing the Fréchet distance (also called dogleash distance) between two polygonal curves with a total number of n vertices. For two polygonal curves in the plane we prove an Ω(n log n) lower bound for the decision problem in the algebraic computation tree model allowin ..."
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Cited by 17 (5 self)
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allowing arithmetic operations and tests. Up to now only a O(n 2) upper bound for the decision problem was known. The Ω(n log n) lower bound extends to variants of the Fréchet distance such as the weak as well as the discrete Fréchet distance. For the onedimensional case we give a lineartime algorithm
Improving timbre similarity: How high is the sky
 Results in Speech and Audio Sciences
"... Abstract. We report on experiments done in an attempt to improve the performance of a music similarity measure which we introduced earlier. The technique aims at comparing music titles on the basis of their global “timbre”, which has many applications in the field of Music Information Retrieval. Suc ..."
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Cited by 181 (14 self)
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. Such measures of timbre similarity have seen a growing interest lately, and every contribution (including ours) is yet another instantiation of the same basic pattern recognition architecture, only with different algorithm variants and parameters. Most give encouraging results with a little effort, and imply
Automated Extraction and Parameterization of Motions in Large Data Sets
 ACM Transactions on Graphics
, 2004
"... Large motion data sets often contain many variants of the same kind of motion, but without appropriate tools it is difficult to fully exploit this fact. This paper provides automated methods for identifying logically similar motions in a data set and using them to build a continuous and intuitively ..."
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Cited by 183 (2 self)
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Large motion data sets often contain many variants of the same kind of motion, but without appropriate tools it is difficult to fully exploit this fact. This paper provides automated methods for identifying logically similar motions in a data set and using them to build a continuous and intuitively
Results 1  10
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