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265,041
The Alignment Template Approach to Statistical Machine Translation
, 2004
"... A phrase-based statistical machine translation approach — the alignment template approach — is described. This translation approach allows for general many-to-many relations between words. Thereby, the context of words is taken into account in the translation model, and local changes in word order f ..."
Abstract
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Cited by 480 (26 self)
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from source to target language can be learned explicitly. The model is described using a log-linear modeling approach, which is a generalization of the often used source–channel approach. Thereby, the model is easier to extend than classical statistical machine translation systems. We describe
A finite-state framework for log-linear models in Machine Translation 1
"... Abstract. Log-linear models represent nowadays the state-of-the-art in statistical machine translation. There, several models are combined altogether into a whole statistical approach. Finite-state transducers constitute a special type of statistical translation model whose interest has been proved ..."
Abstract
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Cited by 2 (1 self)
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Abstract. Log-linear models represent nowadays the state-of-the-art in statistical machine translation. There, several models are combined altogether into a whole statistical approach. Finite-state transducers constitute a special type of statistical translation model whose interest has been proved
Log-Linear Models for Label Ranking
, 2003
"... Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking functions from supervised data. We assume that each instance in the training data is associated with a list of preferenc ..."
Abstract
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Cited by 109 (5 self)
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of labels. Special cases of our setting are multilabel categorization and hierarchical classification. We present a general boosting-based learning algorithm for the label ranking problem and prove a lower bound on the progress of each boosting iteration. The applicability of our approach
A Compositional Approach to Performance Modelling
, 1996
"... Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more ea ..."
Abstract
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Cited by 757 (102 self)
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Performance modelling is concerned with the capture and analysis of the dynamic behaviour of computer and communication systems. The size and complexity of many modern systems result in large, complex models. A compositional approach decomposes the system into subsystems that are smaller and more
A Language Modeling Approach to Information Retrieval
, 1998
"... Models of document indexing and document retrieval have been extensively studied. The integration of these two classes of models has been the goal of several researchers but it is a very difficult problem. We argue that much of the reason for this is the lack of an adequate indexing model. This sugg ..."
Abstract
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Cited by 1154 (42 self)
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an approach to retrieval based on probabilistic language modeling. We estimate models for each document individually. Our approach to modeling is non-parametric and integrates document indexing and document retrieval into a single model. One advantage of our approach is that collection statistics which
Structural equation modeling in practice: a review and recommended two-step approach.
- Psychological Bulletin,
, 1988
"... In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We di ..."
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Cited by 1825 (3 self)
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In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We
Shape modeling with front propagation: A level set approach
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1995
"... Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains some of the attractive features of existing methods and over- ..."
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Cited by 808 (20 self)
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Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains some of the attractive features of existing methods and over
Option Pricing: A Simplified Approach
- Journal of Financial Economics
, 1979
"... This paper presents a simple discrete-time model for valumg optlons. The fundamental econonuc principles of option pricing by arbitrage methods are particularly clear In this setting. Its development requires only elementary mathematics, yet it contains as a special limiting case the celebrated Blac ..."
Abstract
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Cited by 1016 (10 self)
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This paper presents a simple discrete-time model for valumg optlons. The fundamental econonuc principles of option pricing by arbitrage methods are particularly clear In this setting. Its development requires only elementary mathematics, yet it contains as a special limiting case the celebrated
A Maximum Entropy approach to Natural Language Processing
- COMPUTATIONAL LINGUISTICS
, 1996
"... The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statistical estimation and pattern recognition. In this paper we des ..."
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Cited by 1366 (5 self)
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describe a method for statistical modeling based on maximum entropy. We present a maximum-likelihood approach for automatically constructing maximum entropy models and describe how to implement this approach efficiently, using as examples several problems in natural language processing.
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