The authors model a virtual circuit in a computer network as a sequence of servers in tandem. They explicitly take into account cross traffic at the servers from other virtual circuits. The analysis of the model leads...
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ISBN:
(纸本)0780306023
The authors model a virtual circuit in a computer network as a sequence of servers in tandem. They explicitly take into account cross traffic at the servers from other virtual circuits. The analysis of the model leads them to propose a novel flow control scheme, which they term send-time control. A measure to evaluate the performance of flow control schemes, called the packet performance index, is proposed. They compare the send-time control scheme with the window-based flow control scheme of transmission control protocol (TCP) using simulation. The results obtained show that send-time control is superior to the window-based scheme.
We have shown how graphical languages such as CODE/ROPE and PPSE can be used to design SIMD or data parallel programs. The advantages of this approach are machine independence, design clarity, automated program analys...
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It is well known that, for fixed k, to find the k-th largest of n elements n+(k-1)log2n+Θ(1) comparisons are necessary and sufficient. But do the same bounds apply if we use a different type of query? We show that th...
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作者:
ALOIMONOS, YDURIC, ZComputer Vision Laboratory
Center for Automation Research Department of Computer Science Institute for Advanced Computer Studies University of Maryland College Park 20742-3411 MD United States
Passive navigation refers to the ability of an organism or a robot that moves in its environment to determine its own motion precisely on the basis of some perceptual input, for the purposes of kinetic stabilization. ...
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While procrastination is generally regarded as an undesirable quality, this paper points out a potential advantage to some uses of procrastination. Working with a formal model of machine learning we show that machines...
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ISBN:
(纸本)089791497X
While procrastination is generally regarded as an undesirable quality, this paper points out a potential advantage to some uses of procrastination. Working with a formal model of machine learning we show that machines that procrastinate about how many learning trials are needed are demonstrably more powerful than machines that do not procrastinate. The model used essentially allows the learning machine to speculate about how many trials it will need, and to then later revise (increase) its estimate. The more often revision are allowed, the more the machine is procrastinating. We show that the more the machine is allowed to procrastinate, the larger the class of learning phenomena (represented by sets of recursive functions) becomes. The learning machines we study all endeavor to learn recursive functions. The recursive functions are sufficiently rich so as to be able to encode any computable mapping from descriptions of stimuli to the descriptions of the associated responses.
Generalization is a learning problem that has received considerable attention. The generalization problem is to take a finite sample of some concept and produce an algorithm that can produce all other (perhaps infinit...
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ISBN:
(纸本)089791497X
Generalization is a learning problem that has received considerable attention. The generalization problem is to take a finite sample of some concept and produce an algorithm that can produce all other (perhaps infinitely many) samples of the same concept. Inductive inference is the study of this problem in a most general framework [1]. The classification problem is to take a finite sample of some concept and decide which type of concept the sample is from. The choice of type is usually finite. If the mechanism performing the classification is limiting, e.g., it makes more and more conjectures as to a classification as time goes on, then the process can also be considered as a type of learning. Roughly, we will say that some suitable mechanism has learned an appropriate classification if its sequence of conjectures stabilizes at some point. In this paper we formalize, at a suitable level of abstraction, the classification problem and rigorously compare it to the generalization problem. Despite some obvious similarities, the two notions are shown to be distinct. The new formalism of classification is investigated further.
Software reuse can be achieved through an organization that focuses on utilization of life cycle products from previous developments. The component factory is both an example of the more general concepts of experience...
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When a set of rules generates (conflicting) values for a virtual attribute of some tuple, the system must resolve the inconsistency and decide on a unique value that is assigned to that attribute. In most current syst...
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Using the Trellis human/computer interaction model as an implementation vehicle, we demonstrate how to use concurrency-supporting hypertext to provide visual displays of the execution flows through a parallel Lisp pro...
The dynamics of large networks is known to be complex. In this paper, we study a characterization of network dynamics in terms of transit times and losses. Applicability of this characterization is studied through exp...
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