The task of learning a natural language is an instance of inductive inference (making gener-alizations based on the past observations to predict the future ones) studied within several traditions in the sciences under such names as “machine learning, ” “grammar induction,” and “computational learning theory. ” In this article, I aim to introduce some of the con
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...
We present in this article a top-down inductive system, ALLiS, for learning linguistic structures. ...
International audienceThis paper focuses on a subfield of machine learning, the so- called grammatica...
this paper we take the broadest possible view of language. What have we learnt about language in the...
When dealing with language, (machine) learning can take many different faces, of which the most impo...
A fundamental debate in the machine learning of language has been the role of prior knowledge in the...
How do children learn language in a way that allows generalization -- producing and comprehending ut...
This paper gives a brief introduction to a particular machine learning method known as inductive log...
Abstract. This thesis examines the use of machine learning techniques in various tasks of natural la...
My doctoral research focuses on understanding semantic knowledge in neural network models trained so...
encompass automatic computing procedures based on logical or binary operations that learn a task fro...
After becoming familiar with preparing text data in different formats and training different algorit...
We investigated the processing of inflected Serbian adjective forms to bring together quantitative l...
In this paper, we review recent progress in the field of machine learning and examine its implicatio...
This article briefly reviews some recent work on artificial language learning in children and adults...
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...
We present in this article a top-down inductive system, ALLiS, for learning linguistic structures. ...
International audienceThis paper focuses on a subfield of machine learning, the so- called grammatica...
this paper we take the broadest possible view of language. What have we learnt about language in the...
When dealing with language, (machine) learning can take many different faces, of which the most impo...
A fundamental debate in the machine learning of language has been the role of prior knowledge in the...
How do children learn language in a way that allows generalization -- producing and comprehending ut...
This paper gives a brief introduction to a particular machine learning method known as inductive log...
Abstract. This thesis examines the use of machine learning techniques in various tasks of natural la...
My doctoral research focuses on understanding semantic knowledge in neural network models trained so...
encompass automatic computing procedures based on logical or binary operations that learn a task fro...
After becoming familiar with preparing text data in different formats and training different algorit...
We investigated the processing of inflected Serbian adjective forms to bring together quantitative l...
In this paper, we review recent progress in the field of machine learning and examine its implicatio...
This article briefly reviews some recent work on artificial language learning in children and adults...
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...
We present in this article a top-down inductive system, ALLiS, for learning linguistic structures. ...
International audienceThis paper focuses on a subfield of machine learning, the so- called grammatica...