When we were invited to write a retrospective article about our AAAI-99 paper on mutual bootstrapping (Riloff and Jones 1999), our first reaction was hesitation because, well, that algorithm seems old and clunky now. But upon reflection, it shaped a great deal of subsequent work on bootstrapped learning for natural language processing, both by ourselves and others. So our second reaction was enthusiasm, for the opportunity to think about the path from 1999 to 2017 and to share the lessons that we learned about bootstrapped learning along the way. This article begins with a brief history of related research that preceded and inspired the mutual bootstrapping work, to position it with respect to that period of time. We then describe the gener...
We describe a coherent view of learning and reasoning with relational representations in the context...
This paper addresses these concerns by conducting new analyses of the data from Snedeker, Gleitman, ...
Journal ArticleThis paper describes a bootstrapping algorithm called Basilisk that learns high-quali...
Bootstrapping is a minimally supervised machine learning algorithm used in natural language processi...
Natural language processing (NLP) is a rapidly growing field with a wide range of applications, such...
Co-Training is a weakly supervised learning paradigm in which the redundancy of the learning task is...
[[abstract]]This paper addresses a fundamental dilemma in the design of intelligent language learnin...
This paper offers a personal perspective on the development of language and infor-mation processing ...
Deep learning has been the mainstream technique in natural language processing (NLP) area. However, ...
The paper starts with the history of Natural Language Processing (NLP) and revisits the concepts and...
After becoming familiar with preparing text data in different formats and training different algorit...
Integrating knowledge across different domains is an essential feature of human learning. Learning p...
One of the important goals of Artificial Intelligence (AI) is to mimic the ability of humans to leve...
this paper we take the broadest possible view of language. What have we learnt about language in the...
Text style transfer is an important task in controllable language generation. Supervised approaches ...
We describe a coherent view of learning and reasoning with relational representations in the context...
This paper addresses these concerns by conducting new analyses of the data from Snedeker, Gleitman, ...
Journal ArticleThis paper describes a bootstrapping algorithm called Basilisk that learns high-quali...
Bootstrapping is a minimally supervised machine learning algorithm used in natural language processi...
Natural language processing (NLP) is a rapidly growing field with a wide range of applications, such...
Co-Training is a weakly supervised learning paradigm in which the redundancy of the learning task is...
[[abstract]]This paper addresses a fundamental dilemma in the design of intelligent language learnin...
This paper offers a personal perspective on the development of language and infor-mation processing ...
Deep learning has been the mainstream technique in natural language processing (NLP) area. However, ...
The paper starts with the history of Natural Language Processing (NLP) and revisits the concepts and...
After becoming familiar with preparing text data in different formats and training different algorit...
Integrating knowledge across different domains is an essential feature of human learning. Learning p...
One of the important goals of Artificial Intelligence (AI) is to mimic the ability of humans to leve...
this paper we take the broadest possible view of language. What have we learnt about language in the...
Text style transfer is an important task in controllable language generation. Supervised approaches ...
We describe a coherent view of learning and reasoning with relational representations in the context...
This paper addresses these concerns by conducting new analyses of the data from Snedeker, Gleitman, ...
Journal ArticleThis paper describes a bootstrapping algorithm called Basilisk that learns high-quali...