Top: Computer Science: Machine Learning:
Description
As a broad subfield of artificial intelligence, machine learning is concerned with the development of algorithms and techniques that allow computers to "learn". At a general level, there are two types of learning: inductive, and deductive. Inductive machine learning methods extract rules and patterns out of massive data sets. Some parts of machine learning are closely related to data mining and statistics. Machine learning research is focused on the computational properties of the statistical methods, such as their computational complexity. Machine learning has a wide spectrum of applications including natural language processing,syntactic pattern recognition, search engines, medical diagnosis, bioinformatics and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing and robot locomotion.From Wikipedia, the free encyclopedia
Subcategories
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Active Learning (14)
Bayesian Learning (78)
Boosting (8)
Clustering (90)
Ensemble Methods (6)
Gaussian Processes (51)
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Graphical Models (25)
Kernel Methods (125)
Linear Models (9)
Markov Processes (30)
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Neural Networks (10)
On-line Learning (8)
Pattern Recognition (26)
Preprocessing (20)
Regression (4)
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Software (5)
Statistical Learning (42)
Structured data (21)
Structured Output (22)
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References
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The 13th Machine Learning Summer School
The 13th Machine Learning Summer School was held in Cambridge, UK. This year's edition was organized by the University of ... |
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PASCAL Bootcamp in Machine Learning
Pascal Boot camp is meant to be a crossroad between a summer school and a strong workshop session. ;And the ... |
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Machine Learning Summer School 2008 - Kioloa
This school is suitable for all levels, both for people without previous knowledge in Machine Learning, and those wishing to ... |
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Machine Learning over Text & Images - Autumn School
Machine learning approaches to natural language processing problems such as information retrieval, document classification, and information extraction have developed rapidly ... |
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Machine Learning seminars at the Cambridge University Engineering Department
Machine Learning is a multidisciplinary field which aims to understand and design algorithms that automatically extract useful information from data. ... |
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Machine Learning Summer School 2004 - Berder Island
The fourth Machine Learning Summer School was held in Berder Island, France between the 12th and the 25th of September, ... |
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Summer Schools in Logic and Learning
The Summer Schools in Logic and Learning bring together two annual summer schools in the area of logic and machine ... |
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Machine Learning Summer School 2006 - Taipei
The two-week summer school program consists of about 40+ hours of lectures from 7/24 to 8/4. The late afternoon sessions ... |
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Machine Learning Summer School 2007 - Tuebingen
Machine Learning is a foundational discipline of the Information Sciences. It combines theory from areas as diverse as Statistics, Mathematics, ... |
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Machine Learning Summer School 2003 - Tuebingen
Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, ... |
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Machine Learning Summer School 2005 - Canberra
Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, ... |
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Stanford Engineering Everywhere CS229 - Machine Learning
This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric ... |
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Machine Learning Summer School 2006 - Canberra
This school is suitable for all levels, both for people without previous knowledge in Machine Learning, and those wishing to ... |
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Machine Learning Summer School 2005 - Chicago
Machine learning is a field focused on making machines learn to make predictions from examples. It combines elements of mathematics, ... |
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Carnegie Mellon Machine Learning Lunch seminar
The Machine Learning lunch is a weekly seminar which has the goal of bringing together the different people at CMU ... |
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ICML 2007 - The 24th Annual International Conference on Machine Learning
The 24th Annual International Conference on Machine Learning is being held in conjunction with the 2007 International Conference on Inductive ... |
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NIPS '07 Workshop on Efficient Machine Learning
The ever increasing size of available data to be processed by machine learning algorithms has yielded several approaches, from online ... |
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Machine Learning Workshop - Sheffield 2004
Machine Learning is the study of computer algorithms that improve automatically through experience. Applications range from datamining programs that discover ... |
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International Conference on Machine Learning - Bonn 2005
ICML (= International Conference on Machine Learning) is worldwide the largest international conference on machine learning research and applications. ICML ... |
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The 25th International Conference on Machine Learning (ICML 2008)
The 25th International Conference on Machine Learning (ICML 2008) was organized in Helsinki, Finland on July 5-9, 2008. ICML is ... |
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Machine Learning Summer School 2002 - Canberra
Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, ... |
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The 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)
The 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery ... |
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NIPS ´08 Workshop: Machine Learning in Computational Biology
The field of computational biology has seen dramatic growth over the past few years, both in terms of new available ... |
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Probabilistic Modeling and Machine Learning in Structural and Systems Biology
The aim of this workshop is to provide a broad look at the state of the art in the probabilistic ... |
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NIPS ´08 Workshop: New Challenges in Theoretical Machine Learning: Learning with Data-dependent Concept Spaces
This workshop aims at collecting theoretical insights in the design of data-dependent learning strategies. Specifically we are interested in how ... |
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Machine Learning in Systems Biology
Molecular biology and also all the biomedical sciences are undergoing a true revolution as a result of the emergence and ... |
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ECML/PKDD Conference
The 14th European Conference on Machine Learning (ECML) and the 7th European Conference on Principles and Practice of Knowledge Discovery ... |
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