alexa International Machine Learning Society (IMLS)

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

International Machine Learning Society (IMLS)

With the emergence of the need for a non-profit professional society which could  run the International Conference on Machine Learning (ICML) was recognized at the editorial board meetings of the Machine Learning journal and the open conference business meetings at the end of every conference finally led to the development of this society in 1980 in Pittsburg. The importance for such a society is to build a legal organization for managing the funds required to run the annual conference. Currently such funds are managed as a subordinate manner by passing money between the host academic institutions of the conference chairs. This often brought forth various logistic problems. A solution to this problem was  having a non-profit organization as a supporter of the conference. Related conferences such as NIPS, COLT, and UAI already have such supporting societies. Another need is to democratize the process of running the conference. After becoming a conference, ICML has been run by the editorial board of the Machine Learning journal (MLJ) which collects proposals and selects the conference and their venues each year. The recent development of the Journal of Machine Learning Research (JMLR) has made the MLJ board a potentially even less fully-representative body. At the recent ICML-2001 business meeting in Williamstown MA, a decision was  made to establish a reasonably democratic process by which such a society and its governing board could be established. The general idea was initially to elect a body of 10 established machine learning researchers to serve as a governing board. This board would then work to establish the society and elect a set of officers amongst themselves.

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