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Limit Laws for Heights in Generalized Tries and PATRICIA Tries
, 1999
"... We consider digital trees such as (generalized) tries and PATRICIA tries, built from n random strings generated by an unbiased memoryless source (i.e., all symbols are equally likely). We study limit laws of the height which is defined as the longest path in such trees. It turns out that this heigh ..."
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Cited by 6 (0 self)
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We consider digital trees such as (generalized) tries and PATRICIA tries, built from n random strings generated by an unbiased memoryless source (i.e., all symbols are equally likely). We study limit laws of the height which is defined as the longest path in such trees. It turns out
PATRICIA TRIES AGAIN REVISITED
, 1986
"... This paper studies the average complexity of Patricia tries from the successful and unsuccessful search point of view. It is assumed that the Patricia trie is buill over a Velemcnt alphabet, and keys are strings of elements from Ihe alphabet The occurrence of Lbe i t.h element from lhe alphabet in ..."
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This paper studies the average complexity of Patricia tries from the successful and unsuccessful search point of view. It is assumed that the Patricia trie is buill over a Velemcnt alphabet, and keys are strings of elements from Ihe alphabet The occurrence of Lbe i t.h element from lhe alphabet
Profiles of PATRICIA Tries ∗
"... A PATRICIA trie is a trie in which nonbranching paths are compressed. The external profile Bn,k, defined to be the number of leaves at level k of a PATRICIA trie on n nodes, is an important “summarizing ” parameter, in terms of which several other parameters of interest can be formulated. Here we d ..."
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Cited by 1 (1 self)
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derive precise asymptotics for the expected value and variance of Bn,k, as well as a central limit theorem with error bound on the characteristic function, for PATRICIA tries on n infinite binary strings generated by a memoryless source with bias p> 1/2 for k ∼ α log n with α ∈ (1 / log(1/q) + , 1
LIMITING DISTRIBUTION FOR THE DEPTH IN PATRICIA TRIES
, 2000
"... This paper establishes the limiting distribution for the depth of keys in a PATRICIA trie. A PATRICIA trie is a variation of the trie, a wellknown tree structure, which is a frequently used data structure in many applications of computer science and telecommunications. These applications include dy ..."
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This paper establishes the limiting distribution for the depth of keys in a PATRICIA trie. A PATRICIA trie is a variation of the trie, a wellknown tree structure, which is a frequently used data structure in many applications of computer science and telecommunications. These applications include
Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention
 Psychological Bulletin
, 1992
"... The authors suggest that the most promising route to effective strategies for the prevention of adolescent alcohol and other drug problems is through a riskfocused approach. This approach requires the identification of risk factors for drug abuse, identification of methods by which risk factors hav ..."
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Cited by 693 (18 self)
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have been effectively addressed, and application of these methods to appropriate highrisk and general population samples in controlled studies. The authors review risk and protective factors for drug abuse, assess a number of approaches for drug abuse prevention potential with highrisk groups
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 707 (18 self)
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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 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 search strategies, each of which is a query expansion for a given domain. For this task, we compare the performance of RankBoost to the individual search strategies. The second experiment is a collaborativefiltering task for making movie recommendations. Here, we present results comparing RankBoost to nearestneighbor and regression algorithms.
Parameterized Complexity
, 1998
"... the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs ..."
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Cited by 1218 (75 self)
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the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs into the toolkit of every algorithm designer. The purpose of the seminar was to bring together leading experts from all over the world, and from the diverse areas of computer science that have been attracted to this new framework. The seminar was intended as the rst larger international meeting with a specic focus on parameterized complexity, and it hopefully serves as a driving force in the development of the eld. 1 We had 49 participants from Australia, Canada, India, Israel, New Zealand, USA, and various European countries. During the workshop 25 lectures were given. Moreover, one night session was devoted to open problems and Thursday was basically used for problem discussion
What Do We Know about Capital Structure? Some Evidence from International Data
 Journal of Finance
, 1995
"... We investigate the determinants of capital structure choice by analyzing the financing decisions of public firms in the major industrialized countries. At an aggregate level, firm leverage is fairly similar across the G7 countries. We find that factors identified by previous studies as correlated i ..."
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Cited by 954 (14 self)
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We investigate the determinants of capital structure choice by analyzing the financing decisions of public firms in the major industrialized countries. At an aggregate level, firm leverage is fairly similar across the G7 countries. We find that factors identified by previous studies as correlated in the crosssection with firm leverage in the U.S., are similarly correlated in other countries as well. However, a deeper examination of the U.S. and foreign evidence suggests that the theoretical underpinnings of the observed correlations are still largely unresolved.
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