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Algorithmic learning theory

Known as: Learning theory 
Algorithmic learning theory is a mathematical framework for analyzing machine learning problems and algorithms. Synonyms include formal learning… 
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Related topics

Related topics

18 relations
CN2 algorithmComputational epistemologyComputer memoryComputer program

Broader (1)

Computational learning theory

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Selectively Fine-Tuning Bayesian Network Learning Algorithm
In this work, we propose a Selective Fine-Tuning algorithm for Bayesian Networks (SFTBN). The aim is to enhance the accuracy of… 
2015
2015
A Modified Isomap Approach to Manifold Learning in Word Spotting
Word spotting is an effective paradigm for indexing document images with minimal human effort. Here, the use of the Bag-of… 
2014
2014
Anomaly Detection using Fuzzy Q-learning Algorithm
Wireless networks are increasingly overwhelmed by Distributed Denial of Service (DDoS) attacks by generating flooding packets… 
2011
2011
A co-training framework for visual tracking with multiple instance learning
This paper proposes a Co-training Multiple Instance Learning algorithm (CoMIL). Our framework is based on the co-training… 
2011
2011
Using Cases as Heuristics in Reinforcement Learning: A Transfer Learning Application
In this paper we propose to combine three AI techniques to speed up a Reinforcement Learning algorithm in a Transfer Learning… 
2010
2010
Autonomous Navigation in Dynamic Environments with Reinforcement Learning and Heuristic
Researchers have created machines which operate autonomously in complex and changing environments. An important problem that has… 
Highly Cited
2005
Highly Cited
2005
Interval Type-2 TSK Fuzzy Logic Systems Using Hybrid Learning Algorithm
This article presents a new learning methodology based on a hybrid algorithm for interval type-2 TSK fuzzy logic systems (FLS… 
2003
2003
Predicting Geomagnetic Activity Index by Brain Emotional Learning
The Emotional Learning Algorithm has been introduced to show the effect of emotions as well known stimuli in the quick and almost… 
2003
2003
Dynamic channel assignment in cellular networks: a reinforcement learning solution
The optimization of channel assignment in cellular networks is a very complex optimization problem and it becomes more difficult… 
1990
1990
Convergence properties and stationary points of a perceptron learning algorithm
An analysis of the stationary (convergence) points of an adaptive algorithm that adjusts the perceptron weights is presented… 
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