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Instancebased learning algorithms
 Machine Learning
, 1991
"... Abstract. Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances to ..."
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Cited by 1389 (18 self)
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. This approach extends the nearest neighbor algorithm, which has large storage requirements. We describe how storage requirements can be significantly reduced with, at most, minor sacrifices in learning rate and classification accuracy. While the storagereducing algorithm performs well on several realworld
The Cache Performance and Optimizations of Blocked Algorithms
 In Proceedings of the Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
, 1991
"... Blocking is a wellknown optimization technique for improving the effectiveness of memory hierarchies. Instead of operating on entire rows or columns of an array, blocked algorithms operate on submatrices or blocks, so that data loaded into the faster levels of the memory hierarchy are reused. This ..."
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Cited by 574 (5 self)
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given cache size, the block size that minimizes the expected number of cache misses is very small. Tailoring the block size according to the matrix size and cache parameters can improve the average performance and reduce the variance in performance for different matrix sizes. Finally, whenever possible
The weighted majority algorithm
, 1992
"... We study the construction of prediction algorithms in a situation in which a learner faces a sequence of trials, with a prediction to be made in each, and the goal of the learner is to make few mistakes. We are interested in the case that the learner has reason to believe that one of some pool of kn ..."
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Cited by 877 (43 self)
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of known algorithms will perform well, but the learner does not know which one. A simple and effective method, based on weighted voting, is introduced for constructing a compound algorithm in such a circumstance. We call this method the Weighted Majority Algorithm. We show that this algorithm is robust
Randomized Gossip Algorithms
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2006
"... Motivated by applications to sensor, peertopeer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
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Cited by 532 (5 self)
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method that solves the optimization problem over the network. The relation of averaging time to the second largest eigenvalue naturally relates it to the mixing time of a random walk with transition probabilities derived from the gossip algorithm. We use this connection to study the performance
Experiments with a New Boosting Algorithm
, 1996
"... In an earlier paper, we introduced a new “boosting” algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced the relate ..."
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Cited by 2213 (20 self)
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In an earlier paper, we introduced a new “boosting” algorithm called AdaBoost which, theoretically, can be used to significantly reduce the error of any learning algorithm that consistently generates classifiers whose performance is a little better than random guessing. We also introduced
A Data Locality Optimizing Algorithm
, 1991
"... This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory that unifi ..."
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Cited by 804 (16 self)
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This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory
An Efficient Boosting Algorithm for Combining Preferences
, 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
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Cited by 727 (18 self)
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boosting algorithm for combining preferences called RankBoost. We also describe an efficient implementation of the algorithm for certain natural cases. We discuss two experiments we carried out to assess the performance of RankBoost. In the first experiment, we used the algorithm to combine different WWW
The Macroscopic Behavior of the TCP Congestion Avoidance Algorithm
, 1997
"... In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts and alw ..."
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Cited by 652 (18 self)
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In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts
Design and Evaluation of a Compiler Algorithm for Prefetching
 in Proceedings of the Fifth International Conference on Architectural Support for Programming Languages and Operating Systems
, 1992
"... Softwarecontrolled data prefetching is a promising technique for improving the performance of the memory subsystem to match today's highperformance processors. While prefetching is useful in hiding the latency, issuing prefetches incurs an instruction overhead and can increase the load on the ..."
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Cited by 501 (20 self)
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Softwarecontrolled data prefetching is a promising technique for improving the performance of the memory subsystem to match today's highperformance processors. While prefetching is useful in hiding the latency, issuing prefetches incurs an instruction overhead and can increase the load
CostAware WWW Proxy Caching Algorithms
 IN PROCEEDINGS OF THE 1997 USENIX SYMPOSIUM ON INTERNET TECHNOLOGY AND SYSTEMS
, 1997
"... Web caches can not only reduce network traffic and downloading latency, but can also affect the distribution of web traffic over the network through costaware caching. This paper introduces GreedyDualSize, which incorporates locality with cost and size concerns in a simple and nonparameterized fash ..."
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Cited by 540 (6 self)
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parameterized fashion for high performance. Tracedriven simulations show that with the appropriate cost definition, GreedyDualSize outperforms existing web cache replacement algorithms in many aspects, including hit ratios, latency reduction and network cost reduction. In addition, GreedyDualSize can potentially
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