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Eager learning

Known as: Eager 
In artificial intelligence, eager learning is a learning method in which the system tries to construct a general, input-independent target function… 
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Related topics

Related topics

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Artificial intelligenceArtificial neural networkLazy learningOffline learning

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Evaluation of optimization techniques for aggregation
Aggregations are almost always done at the top of operator tree after all selections and joins in a SQL query. But actually they… 
2015
2015
Distributed Stream Processing of RNN Query in Mobile Computing
Reverse Nearest Neighbor (RNN) queries are a pipeline of complimentary problems, and have aroused a vast concern in the world in… 
2013
2013
Tensor Voting based Lazy Learner for Pattern Classification
In this paper, we propose a lazy learning classifier based on tensor voting framework for supervised binary and multiclass… 
2011
2011
Reinforcement Learning in Constructive Languages
We present different ways of measuring reinforcement for eager learning methods and constructive languages. The problem of… 
2008
2008
A modular approach to learning Dutch co-reference
This paper presents the first machine learning approach to the resolution of co-referential relations between nominal… 
2007
2007
A Deterministic Database Replication Protocol Where Multicast Writesets Never Got Aborted
Database replication protocols based on a certification app ro ch are usually the best ones for achieving good performance when… 
2006
2006
ENHANCING LOAD DISTRIBUTION STRATEGIES THROUGH SIMULATION
Load distribution is a well known critical problem in every distributed system. From operating systems to agent oriented… 
2005
2005
Lazy Learning for Classification Based on Query Projections
We propose a novel lazy learning method called QPAL. QPAL does not simply utilize a kind of distance measure between the query… 
2005
2005
Eager Learning in Two-Stages for Precise and Complete Web Personalization
We present a systematic approach to automatic Web recommender systems based on Web usage mining in a first stage to learn user… 
1994
1994
Derivation Replay for
Derivation replay was first proposed by Carbonell as a method of transferring guidance from a previous problemsolving episode to…