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5,330
A scheduling model for reduced CPU energy
 ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE
, 1995
"... The energy usage of computer systems is becoming an important consideration, especially for batteryoperated systems. Various methods for reducing energy consumption have been investigated, both at the circuit level and at the operating systems level. In this paper, we propose a simple model of job s ..."
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Cited by 558 (3 self)
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an offline algorithm that computes, for any set of jobs, a minimumenergy schedule. We then consider some online algorithms and their competitive performance for the power function P(s) = sp where p 3 2. It is shown that one natural heuristic, called the Average Rate heuristic, uses at most a constant
Amortized Efficiency of List Update and Paging Rules
, 1985
"... In this article we study the amortized efficiency of the “movetofront” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes 0(i) time, we show that movetofront is within a constant factor of optimum amo ..."
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Cited by 824 (8 self)
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factor that depends on the size of fast memory. No online paging algorithm has better amortized performance.
Efficient and Effective Querying by Image Content
 Journal of Intelligent Information Systems
, 1994
"... In the QBIC (Query By Image Content) project we are studying methods to query large online image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include med ..."
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Cited by 503 (13 self)
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In the QBIC (Query By Image Content) project we are studying methods to query large online image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include
Constrained model predictive control: Stability and optimality
 AUTOMATICA
, 2000
"... Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and t ..."
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Cited by 738 (16 self)
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from an extensive literature essential principles that ensure stability and use these to present a concise characterization of most of the model predictive controllers that have been proposed in the literature. In some cases the finite horizon optimal control problem solved online is exactly
Learning Information Extraction Rules for Semistructured and Free Text
 Machine Learning
, 1999
"... . A wealth of online text information can be made available to automatic processing by information extraction (IE) systems. Each IE application needs a separate set of rules tuned to the domain and writing style. WHISK helps to overcome this knowledgeengineering bottleneck by learning text extract ..."
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Cited by 437 (10 self)
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. A wealth of online text information can be made available to automatic processing by information extraction (IE) systems. Each IE application needs a separate set of rules tuned to the domain and writing style. WHISK helps to overcome this knowledgeengineering bottleneck by learning text
Ricci Flow with Surgery on ThreeManifolds
"... This is a technical paper, which is a continuation of [I]. Here we verify most of the assertions, made in [I, §13]; the exceptions are (1) the statement that a 3manifold which collapses with local lower bound for sectional curvature is a graph manifold this is deferred to a separate paper, as the ..."
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Cited by 448 (2 self)
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, as the proof has nothing to do with the Ricci flow, and (2) the claim about the lower bound for the volumes of the maximal horns and the smoothness of the solution from some time on, which turned out to be unjustified, and, on the other hand, irrelevant for the other conclusions. The Ricci flow with surgery
Applications of Random Sampling in Computational Geometry, II
 Discrete Comput. Geom
, 1995
"... We use random sampling for several new geometric algorithms. The algorithms are "Las Vegas," and their expected bounds are with respect to the random behavior of the algorithms. These algorithms follow from new general results giving sharp bounds for the use of random subsets in geometric ..."
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Cited by 432 (12 self)
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algorithms. These bounds show that random subsets can be used optimally for divideandconquer, and also give bounds for a simple, general technique for building geometric structures incrementally. One new algorithm reports all the intersecting pairs of a set of line segments in the plane, and requires O
SCHEDULING TO MINIMIZE MAX FLOW TIME: OFFLINE AND ONLINE ALGORITHMS
 INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE
, 2004
"... We investigate the max flow time scheduling problem in the offline and online setting. We prove positive and negative theoretical results. In the offline setting, we address the unrelated parallel machines model and present the first known fully polynomial time approximation scheme, when the nu ..."
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Cited by 5 (1 self)
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We investigate the max flow time scheduling problem in the offline and online setting. We prove positive and negative theoretical results. In the offline setting, we address the unrelated parallel machines model and present the first known fully polynomial time approximation scheme, when
Sparse online gaussian processes
 Neural Computation
"... Minor corrections included a a The authors acknowledge reader feedbacks We develop an approach for sparse representations of Gaussian Process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of ..."
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Cited by 183 (8 self)
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Minor corrections included a a The authors acknowledge reader feedbacks We develop an approach for sparse representations of Gaussian Process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination
An optimal online algorithm for metrical task systems
 JOURNAL OF THE ACM
, 1992
"... In practice, almost all dynamic systems require decisions to be made online, without full knowledge of their future impact on the system. A general model for the processing of sequences of tasks is introduced, and a general online decision algorithm is developed. It is shown that, for an importan ..."
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Cited by 209 (8 self)
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, for an important algorithms. class of special cases, this algorithm is optimal among all online Specifically, a task system (S. d) for processing sequences of tasks consists of a set S of states and a cost matrix d where d(i, j) is the cost of changing from state i to state j (we assume that d satisfies
Results 11  20
of
5,330