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152
Machine Learning and the Traveling Repairman
, 2000
"... The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but as in many real situations, the failure probabilities are not known and m ..."
Abstract

Cited by 2 (0 self)
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The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but as in many real situations, the failure probabilities are not known
The Machine Learning and Traveling Repairman Problem
, 2011
"... The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but the failure probabilities are not known and must be estimated. If there i ..."
Abstract

Cited by 1 (1 self)
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The goal of the Machine Learning and Traveling Repairman Problem (ML&TRP) is to determine a route for a “repair crew,” which repairs nodes on a graph. The repair crew aims to minimize the cost of failures at the nodes, but the failure probabilities are not known and must be estimated
Survey of clustering algorithms
 IEEE TRANSACTIONS ON NEURAL NETWORKS
, 2005
"... Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, primitive exploration with little or no prior knowledge, consists of research developed across a wide variety of communities. The diversity, on one hand, equips us with many tools. On the other hand, the ..."
Abstract

Cited by 499 (4 self)
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, the profusion of options causes confusion. We survey clustering algorithms for data sets appearing in statistics, computer science, and machine learning, and illustrate their applications in some benchmark data sets, the traveling salesman problem, and bioinformatics, a new field attracting intensive efforts
Rectified Linear Units Improve Restricted Boltzmann Machines Vinod Nair
"... Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all have the same weights but have progressively more negative biases. The learning and inference rules for these “Stepped Si ..."
Abstract

Cited by 154 (8 self)
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Restricted Boltzmann machines were developed using binary stochastic hidden units. These can be generalized by replacing each binary unit by an infinite number of copies that all have the same weights but have progressively more negative biases. The learning and inference rules for these “Stepped
A Racing Algorithm for Configuring Metaheuristics
, 2002
"... This paper describes a racing procedure for finding, in a limited amount of time, a configuration of a metaheuristic that performs as good as possible on a given instance class of a combinatorial optimization problem. Taking inspiration from methods proposed in the machine learning literature ..."
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Cited by 164 (34 self)
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This paper describes a racing procedure for finding, in a limited amount of time, a configuration of a metaheuristic that performs as good as possible on a given instance class of a combinatorial optimization problem. Taking inspiration from methods proposed in the machine learning literature
Travel Time Prediction using Machine Learning
"... This paper investigates the application of a Machine Learning technique to predict the time that will be spent by a vehicle between any two points in an approximated area. The prediction is based on a learning process based on historical data about the movements performed by the vehicles taking into ..."
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Cited by 1 (1 self)
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This paper investigates the application of a Machine Learning technique to predict the time that will be spent by a vehicle between any two points in an approximated area. The prediction is based on a learning process based on historical data about the movements performed by the vehicles taking
A Travel Time Prediciton with Machine Learning Algorithms
"... It is Friday afternoon. You have a blind date at San Francisco at 8:00pm. Since you don’t want to give a bad first impression, you plan to leave early enough not to be late for the appointment. However, the traffic on 101North on every ..."
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It is Friday afternoon. You have a blind date at San Francisco at 8:00pm. Since you don’t want to give a bad first impression, you plan to leave early enough not to be late for the appointment. However, the traffic on 101North on every
Machine Learning Approach to Report Prioritization with an Application to Travel Time Dissemination
"... This paper looks at the problem of data prioritization, commonly found in mobile adhoc networks. The proposed general solution uses a machine learning approach in order to learn the relevance value of reports, which represent sensed data. The general solution is then applied to a travel time dissem ..."
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Cited by 5 (5 self)
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This paper looks at the problem of data prioritization, commonly found in mobile adhoc networks. The proposed general solution uses a machine learning approach in order to learn the relevance value of reports, which represent sensed data. The general solution is then applied to a travel time
EDITORIAL ELearning Machines
"... I am delighted to write this editorial for the inaugural issue of ELearning. It is an exciting first issue with articles from a range of experts who analyse and discuss in critical and constructive terms some fundamental aspects of elearning – a concept whose time has come. Yet it has passed almos ..."
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Davis at the University of Glasgow, I was recently reminded of Jonathan Swift’s ‘writing machine ’ as he sketches it in Book 4 of Gulliver’s Travels: The first professor I saw was in a very large room, with forty pupils about him. After salutation, observing me to look earnestly upon a frame, which took
A Traveling Salesman Learns Bayesian Networks
"... Structure learning of Bayesian networks is an important problem that arises in numerous machine learning applications. In this work, we present a novel approach for learning the structure of Bayesian networks using the solution of an appropriately constructed traveling salesman problem. In our appro ..."
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Structure learning of Bayesian networks is an important problem that arises in numerous machine learning applications. In this work, we present a novel approach for learning the structure of Bayesian networks using the solution of an appropriately constructed traveling salesman problem. In our
Results 1  10
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152