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Topic: VEGAS algorithm

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	Las Vegas algorithm Definition / Las Vegas algorithm Research (Site not responding. Last check: 2007-10-16)
		In computing, a Las Vegas algorithm is a randomized algorithm A randomized algorithm is an algorithm which is allowed to flip a truly random coin.
		Las Vegas algorithm is a randomized algorithm which is correct; that is, it always produces the correct result.
		Las Vegas algorithm is a rnadomized algorithm which never errs; but with small probability, it may r eport failure.
	www.elresearch.com /Las_Vegas_algorithm (214 words)

	cc.html (Site not responding. Last check: 2007-10-16)
		The justification for this algorithm is that W_k - R_k D_k is an estimate of x_k, the backlog of connection k inside the router.
		Accordingly, if the algorithm converges and results in x_k being close to 2, then all the connections will have an equal share of the router and have R_k close to C/N. Moreover, the total backlog will be rather small and the algorithm achieves a fair and efficient use of the resources.
		We have seen that Vegas converges (at least in the simplistic case of a single bottleneck) to a fair allocation.
	www.ccs.neu.edu /home/matta/courses/com3530/S99/notes/walrand-cc.html (2179 words)

	GNU Scientific Library -- Reference Manual: VEGAS
		The VEGAS algorithm of Lepage is based on importance sampling.
		This is equivalent to locating the peaks of the function from the projections of the integrand onto the coordinate axes.
		VEGAS incorporates a number of additional features, and combines both stratified sampling and importance sampling.
	linux.duke.edu /~mstenner/free-docs/gsl-ref-1.0/gsl-ref_353.html (977 words)

	18
		The expected behavior of a randomized algorithm is no better than the average behavior of its associated deterministic algorithm and is usually a little worse due to such things as the overhead of calls to a random number generator.
		The analog of the class NC for sequential algorithms is the class RNC for parallel algorithms.
		algorithm is a probabilistic algorithm that has a certain probability of returning the correct answer whatever input is considered.
	www.ececs.uc.edu /~jpaul/472/prob.html (2907 words)

	Monte Carlo method
		Monte Carlo methods are algorithms for solving various kinds of computational problems by using random numbers (or more often pseudo-random numbers), as opposed to deterministic algorithms.
		Because of the repetition of algorithms and the large number of calculations involved, Monte Carlo is a method suited to calculation using a computer, utilizing many techniques of computer simulation.
		A Monte Carlo algorithm is a numerical Monte Carlo method used to find solutions to mathematical problems (which may have many variables) that cannot easily be solved, for example, by integral calculus, or other numerical methods.
	www.sciencedaily.com /encyclopedia/monte_carlo_method (930 words)

	Encyclopedia: VEGAS algorithm (Site not responding. Last check: 2007-10-16)
		It samples points from the probability distribution described by the function f, so that the points are concentrated in the regions that make the largest contribution to the integral.
		In practice it is not possible to sample from the exact distribution g for an arbitrary function, so importance sampling algorithms aim to produce efficient approximations to the desired distribution.
		The VEGAS algorithm approximates the exact distribution by making a number of passes over the integration region while histogramming the function f.
	www.nationmaster.com /encyclopedia/VEGAS-algorithm (398 words)

	Las Vegas algorithm (Site not responding. Last check: 2007-10-16)
		Definition: A randomized algorithm that always produces correct results, with the only variation from one run to another being its running time.
		A Las Vegas algorithm always gives the right answer, but the run time is indeterminate.
		Algorithms and Theory of Computation Handbook, CRC Press LLC, 1999, "Las Vegas algorithm", from Dictionary of Algorithms and Data Structures, Paul E. Black, ed., NIST.
	www.nist.gov /dads/HTML/lasVegas.html (142 words)

	TCP Vegas for Linux (Site not responding. Last check: 2007-10-16)
		TCP Vegas is a congestion control algorithm that reduces queuing and packet loss, and thus reduces latency and increases overall throughput, by carefully matching the sending rate to the rate at which packets are successfully being drained by the network.
		This Linux implementation was done by Neal Cardwell (a grad student) and Boris Bak (a recently-graduated undergrad) in the CSE department of the University of Washington-Seattle.
		The basic result is that the Vegas implementation achieved bandwidths that were comparable in most cases, and slightly higher in a number of cases.
	www.flophouse.com /~neal/uw/linux-vegas (2033 words)

	The Complexity Of Primality (Site not responding. Last check: 2007-10-16)
		Although the two problems are strongly related in that a deterministic algorithm for one problem also yields a deterministic algorithm for the other, it makes sense to consider both of them in the framework of complexity theory.
		Depending on R, the algorithm performs computation on the integer P and outputs "Yes" if R provides a witness for the compositeness of P. If P is prime, then no R will ever produce a witness and the algorithm always outputs "No".
		This combined algorithm is called a Las Vegas algorithm: if it outputs an answer, the answer is always correct; and the probability that it will eventually output an answer can be made arbitrarily high by letting k be large enough.
	www.vacets.org /articles/primality.html (941 words)

	Premal's Page (Site not responding. Last check: 2007-10-16)
		Current computational protein design algorithms use clever mathematics to iteratively reduce the search space, eventually arriving at a sequence that is the global minimum energy conformation (GMEC) for the target fold.
		The VEGAS algorithm is really a concept that uses intermediate algorithms in the protein design process.
		We have demonstrated that use of VEGAS makes currently challenging problems to be obtained more efficiently, and produces the best solutions for very large problems, currently non tractable by our battery of algorithms.
	www.cco.caltech.edu /~premal/currentprojects.html (561 words)

	Randomized Algorithms (Site not responding. Last check: 2007-10-16)
		Randomized algorithms save time by choosing a starting point arbitrarily, rather than deciding where the best starting point is. As a result, the algorithm will have a high probability of producing the correct solution.
		In essence therefore, a Las Vegas algorithm is a Monte Carlo algorithm with verification.
		Consider an algorithm to find the element that is atleast as large as the median of an array.
	www.msci.memphis.edu /~giri/7713/f98/vachali.html (997 words)

	Las Vegas (disambiguation) - Wikipedia, the free encyclopedia
		Las Vegas from the Spanish word for the meadows for the US usages and from vega meadow < Iberian vaica or baika meadow < Iberian ibai river in other places.
		Las Vegas algorithms, a type of randomized algorithm
		The Union Pacific Railroad operated a passenger train beginning in the summer of 1937 called the City of Las Vegas, which ran between Las Vegas, Nevada, and Los Angeles, California.
	en.wikipedia.org /wiki/Las_Vegas_(disambiguation) (228 words)

	VEGAS algorithm (Site not responding. Last check: 2007-10-16)
		The VEGAS algorithm is a method for reducing error in the Monte Carlo simulation by using a known or approximate probability distribution function to concentrate the search in those areas of the graph thatmake the greatest contribution to the final integral.
		In practice it is not possible to sample from the exact distribution g for an arbitraryfunction, so importance sampling algorithms aim to produce efficient approximations to the desired distribution.
		The VEGAS algorithm approximates the exact distribution by making a number of passes over the integration region whilehistogramming the function f.
	www.therfcc.org /vegas-algorithm-64343.html (356 words)

	GNU Scientific Library -- Reference Manual - Monte Carlo Integration (Site not responding. Last check: 2007-10-16)
		The plain Monte Carlo algorithm samples points randomly from the integration region to estimate the integral and its error.
		The MISER algorithm of Press and Farrar is based on recursive stratified sampling.
		The MISER algorithm proceeds by bisecting the integration region along one coordinate axis to give two sub-regions at each step.
	www.ugcs.caltech.edu /info/gsl/gsl-ref_23.html (2648 words)

	Citations: Randomized dynamic algorithms with polylogarithmic time per operation - Henzinger, King (ResearchIndex) (Site not responding. Last check: 2007-10-16)
		The deterministic fully dynamic algorithms for 2 edge connectivity (given in [3] 2 vertex connectivity (given in [10] and cycle equivalence (given in [8] are good examples of this.
		In fact, the 2 vertex connectivity algorithm of [11] does not work for some graphs in which the maximum degree is (polylog(n) 13] In view of this, simpler algorithms will be more useful for applications which do not require....
		The algorithm is based on the static maximum matching algorithm described in [33] The space needed is linear and the preprocessing time is....
	citeseer.ist.psu.edu /context/167458/0 (2616 words)

	ZPL - Wikipedia, the free encyclopedia
		In complexity theory, ZPL (Zero-error Probabilistic Logarithmic space) is the set of problems solvable by a probabilistic Turing machine which always yields the correct answer and uses logarithmic space on average.
		Probabilistic algorithms that always give the correct answer are called Las Vegas algorithms.
		A surprising result is that ZPL is equal to both RL and NL; thus, if a problem can be solved in logarithmic space with nondeterminism or with one-sided error, it can be solved with no error and logarithmic space on average.
	www.wikipedia.org /wiki/ZPL (131 words)

	Las Vegas Algorithm for Gene Recognition (Site not responding. Last check: 2007-10-16)
		The algorithm either predicts an exon assembly with extremely high accuracy (not requiring experimental verification) or warns a biologist that the accuracy of a prediction is insufficient and further experimental work is required.
		Algorithms which `reply correctly when they reply at all' and have an `no answer' option otherwise are called Las Vegas algorithms in computer science.
		The algorithm works properly only when a human genomic DNA sequence is provided since algorithm parameters are set based on a human sample.
	www-hto.usc.edu /software/ssze/spliced.html (1675 words)

	[No title]
		The retransmission data of Vegas is almost 50% of that of Reno.
		On the other hand, Vegas and Reno both can not solve the problem of multiple packet loss, so they have the same possibility to wait for timeout due to the most frequently happened problem.
		Vegas has less outstanding data due to congestion avoidance so that it retransmits less.
	netweb.usc.edu /yaxu/Livetest/latex/1 (1486 words)

	GNU Scientific Library -- Reference Manual - Monte Carlo Integration (Site not responding. Last check: 2007-10-16)
		Using this algorithm the estimate of the integral E(f; N) for N randomly distributed points x_i is given by,
		The direction is chosen by examining all d possible bisections and selecting the one which will minimize the combined variance of the two sub-regions.
		With recursive sampling the overall variance should scale better than 1/N, since the values from the sub-regions will be obtained using a procedure which explicitly minimizes their variance.
	jamesthornton.com /gnu/gsl/gsl-ref_23.html (2729 words)

	[No title] (Site not responding. Last check: 2007-10-16)
		Apparently, not all randomized algorithms are called Monte Carlo - there is another class called Vegas methods.
		A Las Vegas algorithm may follow a random path but always ariives at the same solution (e.g.
		This according to Motvani and and Raghavan, "Randomized Algorithms", Cambrideg University Press, 1995, pp.
	www.math.niu.edu /~rusin/known-math/99/montecarlo (232 words)

	Re: TCP Vegas Fairness. (Site not responding. Last check: 2007-10-16)
		In general, it's hard for a local algorithm (with only implicit information from switches/routers along the path) to implement a global property (although you don't define "fairness", it seems like you mean "equal throughput for all flows through a given path").
		Vegas, like Reno, is not particularly designed to be fair.
		Vegas also seems to try to avoid packet loss and (relatedly) to operate with buffers closer to empty than to full, which reduces RTT.
	ils.unc.edu /dempsey/tcp/msg00077.html (396 words)

	Paper review: The Design Philosophy of the DARPA Internet Protocols Reviewer: Kevin Hofstra
		The slow start with congestion avoidance algorithm that Vegas uses is a Vegas* modification that uses the delay between ACKs to actively probe for the congestion limit without actually having to lose packets, much like its linear increase algorithm is able to do.
		Significance- 2 The article is very effective in showing how Vegas leads to greater throughput, less packet loss, and fewer occurrences of congestion, but it is a modification of Reno and should not be considered groundbreaking.
		System researchers and builders should recognize that it is often possible to improve on the convergence and decrease the deviation of an algorithm that approaches a constant.
	zoo.cs.yale.edu /classes/cs633/Reviews/Bp95.kjh29.html (452 words)

	GNU Scientific Library -- Reference Manual - Monte Carlo Examples (Site not responding. Last check: 2007-10-16)
		The MISER algorithm reduces the error by a factor of two, and also correctly estimates the error,
		In the case of the VEGAS algorithm the program uses an initial warm-up run of 10,000 function calls to prepare, or "warm up", the grid.
		The final estimate from VEGAS (using a similar number of function calls) is significantly more accurate than the other two algorithms.
	www.math.utah.edu:8080 /software/gsl/gsl-ref_354.html (440 words)

	Las Vegas & Monte Carlo Algorithms
		The Las Vegas and the Monte Carlo algorithms, respectively, are both characterized as random algorithms.
		It seems to be that the Las Vegas algorithm is an algorithm that will always give the correct answer, or it will give no answer at all.
		But to make a generic Monte Carlo algorithm into a Las Vegas then you would need to add some type of means of checking if the correct pivot was taken as well as the correct answer was given.
	www.joegakenheimer.com /gakenheimer/algorithms/las_vegas_monte_carlo.htm (496 words)

	Dictionary of Algorithms and Data Structures
		This is a dictionary of algorithms, algorithmic techniques, data structures, archetypical problems, and related definitions.
		We do not include algorithms particular to business data processing, communications, operating systems or distributed algorithms, programming languages, AI, graphics, or numerical analysis: it is tough enough covering "general" algorithms and data structures.
		Data Structures and Algorithms is a wonderful site with illustrations, explanations, analysis, and code taking the student from arrays and lists through trees, graphs, and intractable problems.
	www.nist.gov /dads (595 words)

	Citations: A Las Vegas RNC Algorithm for Maximum Matching - Karloff (ResearchIndex) (Site not responding. Last check: 2007-10-16)
		They also yield randomized NC algorithms for several other problems not known to be in NC, e.g.
		This paper (see Figure 1) presents a simple and efficient randomized algorithm for finding the Gallai Edmonds decomposition: Lemma 3.3 shows that, with high probability, the partition A(G) C(G) D(G) for a given graph G can be found by computing a basis for....
		Aside from theoretical issues, the algorithm presented here may be modified to yield practical, that is relatively....
	sherry.ifi.unizh.ch /context/247578/0 (1139 words)

	The Posterior Probability Distribution of Alignments (Site not responding. Last check: 2007-10-16)
		A working-estimate of the machine parameters is needed to calculate the distributions in the algorithm and a weighted average from "recent" alignments is used for this purpose; the algorithm seems to be insensitive to the details of how this is done.
		Since the algorithm actually uses message lengths, the message lengths are multiplied by p which is equivalent to raising the probabilities to the power p.
		The tuning of simulated annealing algorithms is a difficult area and more work needs to be done on tuning the one described here.
	www.csse.monash.edu /~lloyd/tildeStrings/Multiple/94.JME (7580 words)

	[No title] (Site not responding. Last check: 2007-10-16)
		The whole puprose of this paper is to examine whether the claims of efficiency of TCP Vegas in the TCP Vegas paper, are true, using a large number of simulations.
		As a conclusion, Vegas is stated to be conservative since it is much less aggresive, both during the Congestion Avoidance and the Slow Start phase.
		Finally, the time that Vegas saves is analysed into three parts, the time saved by the decrease in the number of time-outs, the time saved by the decrease of Fast Retransmissions and the time saved by the decreased number of retransmitted segments.
	www.it.kth.se /~haritak/project/details/VegasExp.html (464 words)

	Untitled Document - VEGAS (Site not responding. Last check: 2007-10-16)
		Go to the first, previous, next, last section, table of contents.
		This routines uses the VEGAS Monte Carlo algorithm to integrate the function
		These parameters set the level of information printed by VEGAS.
	www.ugcs.caltech.edu /info/gsl/montecarlo_4.html (987 words)

	CS174 Spring 99, Lecture 2, John Canny
		From the definitions, you can see that a Las Vegas algorithm is also a Monte Carlo algorithm (Monte Carlo is a broader definition because nothing is guaranteed).
		To turn a Monte-Carlo algorithm into a Las Vegas algorithm, you need to add a means for checking if the answer is correct and retrying if it isn't.
		distinct permutations (based on the j choices), there is a 1 to 1 correspondence between the algorithms permutations and all the permutations of 1...n.
	www.cs.berkeley.edu /~jfc/cs174lecs/lec2.html (774 words)

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