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2,019,978
Disk cachemiss ratio analysis and design considerations
 ACM Transactions on Computer Systems
, 1985
"... power and toward disk drives of rapidly increasing density, but with disk performance increasing very slowly if at all. The implication of these trends is that at some point the processing power of computer systems will be limited by the throughput of the input/output (I/O) system. A solution to thi ..."
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Cited by 61 (5 self)
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to this problem, which is described and evaluated in this paper, is disk cache. The idea is to buffer recently used portions of the disk address space in electronic storage. Empirically, it is shown that a large (e.g., 8090 percent) fraction of all I/O requests are captured by a cache of an 8Mbyte orderofmagnitude
Pegasos: Primal Estimated subgradient solver for SVM
"... We describe and analyze a simple and effective stochastic subgradient descent algorithm for solving the optimization problem cast by Support Vector Machines (SVM). We prove that the number of iterations required to obtain a solution of accuracy ɛ is Õ(1/ɛ), where each iteration operates on a singl ..."
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Cited by 521 (19 self)
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linear kernels while working solely on the primal objective function, though in this case the runtime does depend linearly on the training set size. Our algorithm is particularly well suited for large text classification problems, where we demonstrate an orderofmagnitude speedup over previous SVM learning
Fast Algorithms for Mining Association Rules
, 1994
"... We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known a ..."
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Cited by 3538 (15 self)
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algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems. We also show how the best features of the two proposed algorithms can be combined into a hybrid algorithm, called AprioriHybrid. Scaleup experiments show that AprioriHybrid scales linearly
Scalable Application Layer Multicast
, 2002
"... We describe a new scalable applicationlayer multicast protocol, specifically designed for lowbandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the applicationlayer multicast peers and can support a number of different data deliv ..."
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Cited by 722 (21 self)
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endtoend latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic. Finally, we present results from our widearea testbed in which we experimented with 32100 member groups distributed over 8 different
Fast texture synthesis using treestructured vector quantization
, 2000
"... Figure 1: Our texture generation process takes an example texture patch (left) and a random noise (middle) as input, and modifies this random noise to make it look like the given example texture. The synthesized texture (right) can be of arbitrary size, and is perceived as very similar to the given ..."
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Cited by 555 (12 self)
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, but runs two orders of magnitude faster. This permits us to apply texture synthesis to problems where it has traditionally been considered impractical. In particular, we have applied it to constrained synthesis for image editing and temporal texture generation. Our algorithm is derived from Markov Random
Measuring ISP Topologies with Rocketfuel
 In Proc. ACM SIGCOMM
, 2002
"... To date, realistic ISP topologies have not been accessible to the research community, leaving work that depends on topology on an uncertain footing. In this paper, we present new Internet mapping techniques that have enabled us to directly measure routerlevel ISP topologies. Our techniques reduce t ..."
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Cited by 829 (28 self)
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the number of required traces compared to a bruteforce, alltoall approach by three orders of magnitude without a significant loss in accuracy. They include the use of BGP routing tables to focus the measurements, exploiting properties of IP routing to eliminate redundant measurements, better alias
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 ..."
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Cited by 512 (8 self)
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the standard algorithm by several orders of magnitude. In practice we obtain stereo, optical flow and image restoration algorithms that are as accurate as other global methods (e.g., using the Middlebury stereo benchmark) while being as fast as local techniques. 1
Efficiently mining long patterns from databases
, 1998
"... We present a patternmining algorithm that scales roughly linearly in the number of maximal patterns embedded in a database irrespective of the length of the longest pattern. In comparison, previous algorithms based on Apriori scale exponentially with longest pattern length. Experiments on real data ..."
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Cited by 453 (3 self)
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data show that when the patterns are long, our algorithm is more efficient by an order of magnimaximal frequent itemset, MaxMiner’s output implicitly and concisely represents all frequent itemsets. MaxMiner is shown to result in two or more orders of magnitude in performance improvements over Apriori
The ‘Squidgy ’ : An OrderofMagnitude Display
"... This paper presents a display approach aimed at visualizing scales and ranges that span many orders of magnitude, with a focus on retaining qualitative aspects of nonlinear scales. This was achieved by the linking of linear and nonlinear frames of reference and allowing the user to explore this li ..."
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This paper presents a display approach aimed at visualizing scales and ranges that span many orders of magnitude, with a focus on retaining qualitative aspects of nonlinear scales. This was achieved by the linking of linear and nonlinear frames of reference and allowing the user to explore
A scaled conjugate gradient algorithm for fast supervised learning
 NEURAL NETWORKS
, 1993
"... A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural netwo ..."
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Cited by 438 (0 self)
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FletcherGoldfarbShanno memoryless quasiNewton algorithm (BFGS) [1]. SCG yields a speedup of at least an order of magnitude relative to BP. The speedup depends on the convergence criterion, i.e., the bigger demand for reduction in error the bigger the speedup. SCG is fully automated including no user dependent parameters
Results 1  10
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