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Active Learning with Statistical Models

by David A. Cohn, Zoubin Ghahramani, Michael I. Jordan , 1995
"... For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative, statist ..."
Abstract - Cited by 679 (10 self) - Add to MetaCart
For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative

Head-Driven Statistical Models for Natural Language Parsing

by Michael Collins , 1999
"... ..."
Abstract - Cited by 1158 (15 self) - Add to MetaCart
Abstract not found

Statistical Models of Appearance for Computer Vision

by T.F. Cootes, C.J. Taylor , 2000
"... ..."
Abstract - Cited by 357 (2 self) - Add to MetaCart
Abstract not found

Statistical Models for Text Segmentation

by Doug Beeferman, Adam Berger, John Lafferty - Machine Learning , 1999
"... . This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text. The mode ..."
Abstract - Cited by 273 (2 self) - Add to MetaCart
. This paper introduces a new statistical approach to automatically partitioning text into coherent segments. The approach is based on a technique that incrementally builds an exponential model to extract features that are correlated with the presence of boundaries in labeled training text

Statistics and causal inference.

by Paul W Holland - J. Am. Statist. Assoc., , 1986
"... Problems involving causal inference have dogged at the heels of statistics since its earliest days. Correlation does not imply causation, and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is address ..."
Abstract - Cited by 736 (1 self) - Add to MetaCart
Problems involving causal inference have dogged at the heels of statistics since its earliest days. Correlation does not imply causation, and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question

Improved Statistical Alignment Models

by Franz Josef Och, Hermann Ney - In Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics , 2000
"... In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model, smoothing techniques and various modifications. ..."
Abstract - Cited by 607 (12 self) - Add to MetaCart
In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model, smoothing techniques and various modifications.

A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotype phase

by Paul Scheet, Matthew Stephens - American Journal of Human Genetics , 2005
"... We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of ..."
Abstract - Cited by 408 (10 self) - Add to MetaCart
We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because

Three Generative, Lexicalised Models for Statistical Parsing

by Michael Collins , 1997
"... In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free gram- mar. We then extend the model to in- clude a probabilistic treatment of both subcategorisation and wh~movement. Results on Wall Street Journal text show that the parse ..."
Abstract - Cited by 570 (8 self) - Add to MetaCart
In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free gram- mar. We then extend the model to in- clude a probabilistic treatment of both subcategorisation and wh~movement. Results on Wall Street Journal text show

Statistical phrase-based translation

by Franz Josef Och, Daniel Marcu , 2003
"... We propose a new phrase-based translation model and decoding algorithm that enables us to evaluate and compare several, previously proposed phrase-based translation models. Within our framework, we carry out a large number of experiments to understand better and explain why phrase-based models outpe ..."
Abstract - Cited by 944 (11 self) - Add to MetaCart
We propose a new phrase-based translation model and decoding algorithm that enables us to evaluate and compare several, previously proposed phrase-based translation models. Within our framework, we carry out a large number of experiments to understand better and explain why phrase-based models

A Systematic Comparison of Various Statistical Alignment Models

by Franz Josef Och, Hermann Ney - COMPUTATIONAL LINGUISTICS , 2003
"... ..."
Abstract - Cited by 1879 (72 self) - Add to MetaCart
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