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» Machine Learning of Temporal Relations
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MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 3 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
AAAI
2008
15 years 12 days ago
Learning to Connect Language and Perception
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
Raymond J. Mooney
CIARP
2008
Springer
15 years 1 days ago
Learning and Forgetting with Local Information of New Objects
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Fernando Vázquez, José Salvador S&aa...
AAAI
1996
14 years 11 months ago
Generation of Attributes for Learning Algorithms
Inductive algorithms rely strongly on their representational biases, Constructive induction can mitigate representational inadequacies. This paper introduces the notion of a relat...
Yuh-Jyh Hu, Dennis F. Kibler
NLP
2000
15 years 1 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...