Corpus-based Learning of Analogies and Semantic Relations
We present an algorithm for learning from unlabeled text, based on the Vector Space Model (VSM) of information retrieval, that
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Correction of Errors in a Modality Corpus Used for Machine Translation by Using Machine-learning Method
We performed corpus correction on a modality corpus for machine translation by using such machine-learning methods as the maximum-entropy method.
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CSIEC (Computer Simulator in Educational Communication): An Intelligent Web-Based Teaching System for Foreign Language Learning
In this paper we present an innovative intelligent web-based computer-aided instruction system for foreign language learning: CSIEC (Computer Simulator in
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Democratic Reinforcement: Learning via Self-Organization
The problem of learning in the absence of external intelligence is discussed in the context of a simple model. The
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Dialogue Act Tagging with Transformation-Based Learning
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a
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Do not forget: Full memory in memory-based learning of word pronunciation
Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior
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Dynamics of Learning with Restricted Training Sets II: Tests and Applications
We apply a general theory describing the dynamics of supervised learning in layered neural networks in the regime where the
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Eavesdropping on Electronic Guidebooks: Observing Learning Resources in Shared Listening Environments
We describe an electronic guidebook, Sotto Voce, that enables visitors to share audio information by eavesdropping on each other's guidebook
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Elusive Unfoldability: Learning a Contact Potential to Fold Crambin
We investigate the extent to which the commonly used standard pairwise contact potential can be used to identify the native
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Explaining away ambiguity: Learning verb selectional preference with Bayesian networks
This paper presents a Bayesian model for unsupervised learning of verb selectional preferences. For each verb the model creates a
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Explanation-based Learning for Machine Translation
In this paper we present an application of explanation-based learning (EBL) in the parsing module of a real-time English-Spanish machine
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Exploiting Context When Learning to Classify
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context
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Forgetting Exceptions is Harmful in Language Learning
We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for
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General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multi-agent systems (MAS's) in an automated fashion, with little or
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Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
This paper presents the MAXQ approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into
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Hypermedia Learning Objects System - On the Way to a Semantic Educational Web
While eLearning systems become more and more popular in daily education, available applications lack opportunities to structure, annotate and manage
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Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with
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Kalman filter control in the reinforcement learning framework
There is a growing interest in using Kalman-filter models in brain modelling. In turn, it is of considerable importance to
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L1 regularization is better than L2 for learning and predicting chaotic systems
Emergent behaviors are in the focus of recent research interest. It is then of considerable importance to investigate what optimizations
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Lazy Transformation-Based Learning
We introduce a significant improvement for a relatively new machine learning method called Transformation-Based Learning. By applying a Monte Carlo
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Learning about Jets from Observations of Blazars
Jets, paving their way outward through the inner regions of active nuclei, Compton-interact with the UV radiation from an accretion
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Learning about the chiral structure of the proton from the hyperfine splitting
The complete analytical $O(m_l^3α^5/m_p^2\times (\log{m_π}, \logΔ, \log{m_l}))$ contribution to the Hyperfine splitting is given. It can explain about 2/3 of
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Learning Algorithms for Keyphrase Extraction
Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the
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Learning Analogies and Semantic Relations
We present an algorithm for learning from unlabeled text, based on the Vector Space Model (VSM) of information retrieval, that
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