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A method for reusable and adaptable reference models Table of Contents TABLE OF CONTENTS ERROR! NO TABLE OF CONTENTS ENTRIES FOUND.
, 2007
"... Mathematics and Computer Science, ..."
Maximum Likelihood Linear Transformations for HMMBased Speech Recognition
 COMPUTER SPEECH AND LANGUAGE
, 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
Abstract

Cited by 570 (68 self)
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of the constrained modelspace transform from the simple diagonal case to the full or blockdiagonal case. The constrained and unconstrained transforms are evaluated in terms of computational cost, recognition time efficiency, and use for speaker adaptive training. The recognition performance of the two model
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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. Introduction The task of calculating posterior marginals on nodes in an arbitrary Bayesian network is known to be NP hard In this paper we investigate the approximation performance of "loopy belief propagation". This refers to using the wellknown Pearl polytree algorithm [12] on a Bayesian network
Querying objectoriented databases
 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
, 1992
"... We present a novel language for querying objectoriented databases. The language is built around the idea of extended path expressions that substantially generalize [ZAN83], and on an adaptation of the firstorder formalization of objectoriented languages from [KW89, KLW90, KW92]. The language inco ..."
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Cited by 492 (6 self)
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We present a novel language for querying objectoriented databases. The language is built around the idea of extended path expressions that substantially generalize [ZAN83], and on an adaptation of the firstorder formalization of objectoriented languages from [KW89, KLW90, KW92]. The language
Index Structures for Path Expressions
, 1997
"... In recent years there has been an increased interest in managing data which does not conform to traditional data models, like the relational or object oriented model. The reasons for this nonconformance are diverse. One one hand, data may not conform to such models at the physical level: it may be ..."
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Cited by 333 (7 self)
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be simply specified by a schema which is too complex or changes too often to be described easily as a traditional schema. The term semistructured data has been used to refer to such data. The data model proposed for this kind of data consists of an edgelabeled graph, in which nodes correspond to objects
AHAM: A Dexterbased Reference Model for Adaptive Hypermedia
, 1999
"... Hypermedia applications offer users the impression that there are many meaningful ways to navigate through a large body of information nodes. This rich link structure not only creates orientation problems, it may also be a source of comprehension problems when users follow paths through the informat ..."
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Cited by 222 (49 self)
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. In this paper we describe a reference model for adaptive hypermedia applications, called AHAM, which encompasses most features...
Consistency of the group lasso and multiple kernel learning
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2007
"... We consider the leastsquare regression problem with regularization by a block 1norm, i.e., a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization by the 1norm where all spaces have dimension one, where it ..."
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Cited by 274 (33 self)
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it is commonly referred to as the Lasso. In this paper, we study the asymptotic model consistency of the group Lasso. We derive necessary and sufficient conditions for the consistency of group Lasso under practical assumptions, such as model misspecification. When the linear predictors and Euclidean norms
A Comparison of Dynamic Branch Predictors that use Two Levels of Branch History
 in Proceedings of the 20th Annual International Symposium on Computer Architecture
, 1993
"... Recent attention to speculative execution as a mechanism for increasing performance of single instruction streams has demanded substantially better branch prediction than what has been previously available. We [1, 2] and Pan, So, and Rahmeh [4] have both proposed variations of the same aggressive dy ..."
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Cited by 278 (9 self)
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dynamic branch predictor for handling those needs. We call the basic model TwoLevel Adaptive Branch Prediction; Pan, So, and Rahmeh call it Correlation Branch Prediction. In this paper, we adopt the terminology of [2] and show that there are really nine variations of the same basic model. We compare
Maintaining Stream Statistics over Sliding Windows (Extended Abstract)
, 2002
"... We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding window model. We consider the following basic problem: Given a stream of bits, maintain a count of the number of 1's i ..."
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Cited by 269 (9 self)
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for the basic counting problem, one can adapt many other techniques to work for the sliding window model, with a multiplicative overhead of O( 1 ffl log N) in memory and a 1 + ffl factor loss in accuracy. These include maintaining approximate histograms, hash tables, and statistics or aggregates such as sum
Multidimensional Independent Component Analysis.
 In Proc. Int. Workshop on HigherOrder Stat
, 1998
"... This discussion paper proposes to generalize the notion of Independent Component Analysis (ICA) to the notion of Multidimensional Independent Component Analysis (MICA). We start from the ICA or blind source separation (BSS) model and show that it can be uniquely identified provided it is properly p ..."
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Cited by 257 (15 self)
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parameterized in terms of onedimensional subspaces. From this standpoint, the BSS/ICA model is generalized to multidimensional components. We discuss how ICA standard algorithms can be adapted to MICA decomposition. The relevance of these ideas is illustrated by a MICA decomposition of ECG signals. 1. BLIND
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