Neil Ireson, Fabio Ciravegna, Marie Elaine Califf, Dayne Freitag, Nicholas Kushmerick, Alberto Lavelli: Evaluating Machine Learning for Information Extraction, 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 7-11 August, 2005
The aim of MLpedia is to provide comprehensive information on a range of machine learning methods and applications, written and maintained by researchers and practitioners. Find out how to take part.
Lush is an object-oriented programming language designed for researchers, experimenters, and engineers interested in large-scale numerical and graphic applications.
What's Torch ?
It's a machine-learning library, written in simple C++ and distributed now under a BSD license.
Torch is currently developed at IDIAP, in Switzerland mountains.
The mission of the Journal of Machine Learning Gossip (JMLG) is to provide an archival source of important information that is often discussed informally at conferences but is rarely, if ever, written down.
I'm interested in machine learning techniques (graphical models, kernel methods) applied to text understanding (entity and relation extraction, coreference resolution, document classification and clustering, confidence prediction, social network analysis, data mining).
38. H-M. Haav, An Application of Inductive Concept Analysis to Construction of Domain-specific Ontologies, In: B. Thalheim, Gunar Fiedler (Eds), Emerging Database Research in East Europe, Proceedings of the Pre-conference Workshop of VLDB 2003, Computer Science Reports, Brandenburg University of Technology at Cottbus, 2003, 14/3, pp 63-67
The mission of the Journal of Machine Learning Gossip (JMLG) is to provide an archival source of important information that is often discussed informally at conferences but is rarely, if ever, written down.
This is a repository of databases, domain theories and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms.
Within the TENCompetence project we aim to develop and integrate models and tools into an open source infrastructure for the creation, storage and exchange of learning objects, suitable knowledge resources as well as learning experiences. This paper analyzes the potential of social software tools for providing part of the required functionality using a detailed scenario. It then discusses the challenges involved, focusing on interoperability, identity management and providing the right Web 2.0 tools for the required functionalities. Finally, we sketch a possible infrastructure based on Facebook, providing information propagation along a social network graph.
The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning
Mahout currently has
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Parallel Frequent Pattern mining
Complementary Naive Bayes classifier
Random forest decision tree based classifier
High performance java collections (previously colt collections)
A vibrant community
and many more cool stuff to come by this summer thanks to Google summer of code
This list is intended to introduce some of the tools of Bayesian statistics and machine learning that can be useful to computational research in cognitive science.
Short introduction to Vector Space Model (VSM) In information retrieval or text mining, the term frequency - inverse document frequency also called tf-idf, is
The aim of this project is to produce age-appropriate non-fiction books for children from birth to age 12. These books are richly illustrated with photographs, diagrams, sketches, and original drawings. Wikijunior books are produced by a worldwide community of writers, teachers, students, and young people all working together. The books present factual information that is verifiable. You are invited to join in and write, edit, and rewrite each module and book to improve its content. Our books are distributed free of charge under the terms of the Creative Commons Attribution-ShareAlike License.
Mloss is a community effort at producing reproducible research via open source software, open access to data and results, and open standards for interchange.
J. Lin, R. Nogueira, and A. Yates. (2020)cite arxiv:2010.06467Comment: Final preproduction version of volume in Synthesis Lectures on Human Language Technologies by Morgan & Claypool.
M. Ferrari Dacrema, P. Cremonesi, and D. Jannach. Proceedings of the 13th ACM Conference on Recommender Systems, page 101–109. New York, NY, USA, Association for Computing Machinery, (2019)
D. Schlör, J. Pfister, and A. Hotho. 2023 the 7th International Conference on Medical and Health Informatics (ICMHI), page 136–141. New York, NY, USA, Association for Computing Machinery, (2023)