This introductory course on machine learning will give an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting,
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic. Minho Sung, Abhishek Kumar, Li Li, Jia Wang, Jun Xu. To appear in the Proc. of 2nd IEEE International Workshop on Networking Meets Databases (NetDB'06), April 2006. Sketch Guided Sampling -- Using On-Line Estimates of Flow Size for Adaptive Data Collection. Abhishek Kumar, Jun (Jim) Xu. To appear in the proceedings of IEEE Infocom'06, Barcelona, Spain, April 2006.
Xstructure is a service for browsing and searching papers in arxiv.org
Among the features of this service are:
* Automated generation of hierarchical classification scheme for the papers. The scheme results from classification of the papers in the arxiv database. The only input for the classification is the citation graph. The number of the levels in the hierarchy and the number of the clusters is determined by the algorithm. The algorithm creates the classification scheme, and indexes the papers by the created classification;
* The classification is used to index the new papers. We plan to rebuild the classification scheme regularly. In this way, we will take into account that appearance of new papers may lead to emergence of new themes. Detection of new themes is one of our objectives;
* A number of extra attributes (e.g. Theme name, Authority and Review Articles, etc.) for the elements (themes) of the classification (see Help);
* Accessability of the classification in response to search requests via display options, e.g., display as Tree of Themes, and Refrerence (Citation) Tree.
About 10% of papers from arxiv are missed in our database. We work on decreasing this number.
Comments, questions, and suggestions are to be sent to Grigorii Pivovarov
The aim of the International Journal of Advances in Internet of Things is to provide a forum for scientists and social workers to present and discuss issues in the impact of the Internet to the society and disseminate findings in scientific research on related subjects.
R. Neßelrath, und J. Alexandersson. Proceedings of the 6th IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems. Twenty-First International Joint Conference On Artificial Intelligence (IJCAI -09), in Conjunction with 6th IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems (KRPD-09), July 12, Pasadena, California, United States, Seite 46-51. IJCAI 2009, (Juli 2009)
M. Sahami, S. Dumais, D. Heckerman, und E. Horvitz. Learning for Text Categorization: Papers from the 1998 Workshop, Madison, Wisconsin, AAAI Technical Report WS-98-05, (1998)
D. Willems, und L. Vuurpijl. Proceedings of the Ninth international conference on document analysis and recognition, Seite 869-873. Curitiba, Brazil, (2007)
J. Esparza, und F. Reiter. 31st International Conference on Concurrency Theory (CONCUR 2020), Volume 171 von Leibniz International Proceedings in Informatics (LIPIcs), Seite 10:1--10:16. Dagstuhl, Germany, Schloss Dagstuhl--Leibniz-Zentrum für Informatik, (2020)Preprint: <a href="https://arxiv.org/abs/2007.03291">Link</a><br>#conference.
Y. Yang, und J. Pedersen. Proceedings of ICML-97, 14th International Conference on Machine Learning, Seite 412--420. Nashville, US, Morgan Kaufmann Publishers, San Francisco, US, (1997)
Y. Yang, und J. Pedersen. Proceedings of ICML-97, 14th International Conference on Machine Learning, Seite 412--420. Nashville, US, Morgan Kaufmann Publishers, San Francisco, US, (1997)