Results 1  10
of
285,416
Distributed Minimum Error Rate Training of SMT using Particle Swarm Optimization
"... The direct optimization of a translation metric is an integral part of building stateoftheart SMT systems. Unfortunately, widely used translation metrics such as BLEUscore are nonsmooth, nonconvex, and nontrivial to optimize. Thus, standard optimizers such as minimum error rate training (MERT) ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
The direct optimization of a translation metric is an integral part of building stateoftheart SMT systems. Unfortunately, widely used translation metrics such as BLEUscore are nonsmooth, nonconvex, and nontrivial to optimize. Thus, standard optimizers such as minimum error rate training (MERT
Particle swarm optimization
, 1995
"... eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications ..."
Abstract

Cited by 3535 (22 self)
 Add to MetaCart
eberhart @ engr.iupui.edu A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described
Minimum Error Rate Training in Statistical Machine Translation
, 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
Abstract

Cited by 663 (7 self)
 Add to MetaCart
Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
Abstract

Cited by 730 (8 self)
 Add to MetaCart
output representations. This paper compares these three approaches to a new technique in which errorcorrecting codes are employed as a distributed output representation. We show that these output representations improve the generalization performance of both C4.5 and backpropagation on a wide range
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
Abstract

Cited by 766 (29 self)
 Add to MetaCart
Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
, 2002
"... We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language senten ..."
Abstract

Cited by 497 (30 self)
 Add to MetaCart
We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language
How Much Training is Needed in MultipleAntenna Wireless Links?
 IEEE Trans. Inform. Theory
, 2000
"... .... ..."
Using Discriminant Eigenfeatures for Image Retrieval
, 1996
"... This paper describes the automatic selection of features from an image training set using the theories of multidimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for viewbased class retrieval ..."
Abstract

Cited by 504 (15 self)
 Add to MetaCart
This paper describes the automatic selection of features from an image training set using the theories of multidimensional linear discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for viewbased class
TransformationBased ErrorDriven Learning and Natural Language Processing: A Case Study in PartofSpeech Tagging
 Computational Linguistics
, 1995
"... this paper, we will describe a simple rulebased approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learni ..."
Abstract

Cited by 916 (7 self)
 Add to MetaCart
this paper, we will describe a simple rulebased approach to automated learning of linguistic knowledge. This approach has been shown for a number of tasks to capture information in a clearer and more direct fashion without a compromise in performance. We present a detailed case study of this learning method applied to part of speech tagging
The process group approach to reliable distributed computing
 Communications of the ACM
, 1993
"... The difficulty of developing reliable distributed softwme is an impediment to applying distributed computing technology in many settings. Expeti _ with the Isis system suggests that a structured approach based on virtually synchronous _ groups yields systems that are substantially easier to develop, ..."
Abstract

Cited by 573 (19 self)
 Add to MetaCart
distributed system to follow directly from the reliability of its constituents, but this is not always the case. The mechanisms used to structure a distributed system and to implement cooperation between components play a vital role in determining how reliable the system will be. Many contemporary
Results 1  10
of
285,416