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3,487,376
Additive Logistic Regression: a Statistical View of Boosting
 Annals of Statistics
, 1998
"... Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input dat ..."
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Cited by 1719 (25 self)
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Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input
Improving DirectMapped Cache Performance by the Addition of a Small FullyAssociative Cache and Prefetch Buffers
, 1990
"... ..."
Improved Statistical Alignment Models
 In Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics
, 2000
"... In this paper, we present and compare various singleword based alignment models for statistical machine translation. We discuss the five IBM alignment models, the HiddenMarkov alignment model, smoothing techniques and various modifications. ..."
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Cited by 593 (13 self)
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In this paper, we present and compare various singleword based alignment models for statistical machine translation. We discuss the five IBM alignment models, the HiddenMarkov alignment model, smoothing techniques and various modifications.
Eliciting selfexplanations improves understanding
 Cognitive Science
, 1994
"... Learning involves the integration of new information into existing knowledge. Generoting explanations to oneself (selfexplaining) facilitates that integration process. Previously, selfexplanation has been shown to improve the acquisition of problemsolving skills when studying workedout examples. ..."
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Cited by 556 (22 self)
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Learning involves the integration of new information into existing knowledge. Generoting explanations to oneself (selfexplaining) facilitates that integration process. Previously, selfexplanation has been shown to improve the acquisition of problemsolving skills when studying workedout examples
Making the most of statistical analyses: Improving interpretation and presentation
 American Journal of Political Science
, 2000
"... Social scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. ..."
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Cited by 550 (24 self)
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Social scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. In this article, we offer an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a readerfriendly manner. Using this technique requires some expertise,
Mining Sequential Patterns: Generalizations and Performance Improvements
 Research Report RJ 9994, IBM Almaden Research
, 1995
"... Abstract. The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transactiontime, and each transaction is a set of items. The problem is to discover all sequential patterns with a user ..."
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Cited by 748 (5 self)
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Abstract. The problem of mining sequential patterns was recently introduced in [3]. We are given a database of sequences, where each sequence is a list of transactions ordered by transactiontime, and each transaction is a set of items. The problem is to discover all sequential patterns with a userspeci ed minimum support, where the support of a pattern is the number of datasequences that contain the pattern. An example of a sequential pattern is \5 % of customers bought `Foundation' and `Ringworld ' in one transaction, followed by `Second Foundation ' in a later transaction". We generalize the problem as follows. First, we add time constraints that specify a minimum and/or maximum time period between adjacent elements in a pattern. Second, we relax the restriction that the items in an element of a sequential pattern must come from the same transaction, instead allowing the items to be present in a set of transactions whose transactiontimes are within a userspeci ed time window. Third, given a userde ned taxonomy (isa hierarchy) on items, we allow sequential patterns to include items across all levels of the taxonomy. We present GSP, a new algorithm that discovers these generalized sequential patterns. Empirical evaluation using synthetic and reallife data indicates that GSP is much faster than the AprioriAll algorithm presented in [3]. GSP scales linearly with the number of datasequences, and has very good scaleup properties with respect to the average datasequence size. 1
Theoretical improvements in algorithmic efficiency for network flow problems

, 1972
"... This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps req ..."
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Cited by 565 (0 self)
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This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps required by earlier algorithms. First, the paper states the maximum flow problem, gives the FordFulkerson labeling method for its solution, and points out that an improper choice of flow augmenting paths can lead to severe computational difficulties. Then rules of choice that avoid these difficulties are given. We show that, if each flow augmentation is made along an augmenting path having a minimum number of arcs, then a maximum flow in an nnode network will be obtained after no more than ~(n a n) augmentations; and then we show that if each flow change is chosen to produce a maximum increase in the flow value then, provided the capacities are integral, a maximum flow will be determined within at most 1 + logM/(M1) if(t, S) augmentations, wheref*(t, s) is the value of the maximum flow and M is the maximum number of arcs across a cut. Next a new algorithm is given for the minimumcost flow problem, in which all shortestpath computations are performed on networks with all weights nonnegative. In particular, this
Improved prediction of signal peptides  SignalP 3.0
 J. MOL. BIOL.
, 2004
"... We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cle ..."
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Cited by 655 (7 self)
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that the cleavage site position and the amino acid composition of the signal peptide are correlated, new features have been included as input to the neural network. This addition, combined with a thorough errorcorrection of a new data set, have improved the performance of the predictor significantly over Signal
Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants
 Review of Economic Studies
, 2002
"... This paper empirically investigates the effects of liberalized trade on plant productivity in the case of Chile. Chile presents an interesting setting to study this relationship since it underwent a massive trade liberalization that significantly exposed its plants to competition from abroad during ..."
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Cited by 530 (14 self)
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evidence of within plant productivity improvements that can be attributed to a liberalized trade for the plants in the importcompeting sector. In many cases, aggregate productivity improvements stem from the reshuffling of resources and output from less to more efficient producers.
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
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Cited by 598 (55 self)
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presents a more sophisticated search algorithm for optimal (and anytime) winner determination, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases. We also uncover
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