The importance of top-level conferences in the field of computer vision and machine learning

Recently asked to pay attention to the visual attention of the "hot Research direction", "the latest method" and so on. Boss suggests Cnki, EI, or sci journals. I'm a little puzzled, why not go to the papers at the top conference?

In the field of machine learning, computer vision and artificial intelligence, top-level conferences are the way to feel. Some people will question that these meetings are only EI, indeed, in many other areas of China, the conference is a grand event, such as society of Neuroscience's meeting, the sea is too much to describe. However, the computer sector is indeed very special, and the importance of top-level meetings cannot be overemphasized.

Can be explained from the following points: (1) Because machine learning, computer vision and artificial intelligence in the field of rapid development, new work is endless, if the paper into the journal, a year or two after the publication of a little out. As a result, most of the latest work is first published in top-level meetings that reflect the "hot research direction" and "the latest approach". (2) A lot of classical work may lead to a paper in a top-level periodical, because the journal paper is more complete and full of experiments. But many are actually starting at the top of the conference. such as pLSA, latent Dirichlet allocation and so on. (3) If you pay attention to these areas Daniel's pulications, it is not difficult to find that they very much value these top meetings, many people are 80% of the conference +20% of the periodical. So why not go to top-level meetings when you're sending the latest work to a top-level meeting?

(1) The following is a list of several top-level meetings (incomplete, but basic coverage)

Machine Learning Top conferences: NIPS, ICML, Uai, aistats; (Issue: JMLR, ML, Trends in ML, IEEE t-nn)
Computer vision and image recognition: ICCV, CVPR, ECCV; (Journal: IEEE T-pami, IJCV, IEEE T-ip)
Artificial Intelligence: IJCAI, AAAI; (journal AI)
Also related to Sigraph, KDD, ACL, Sigir, www and so on.

In particular, if you do machine learning, must, the nearly 4 years of NIPS, ICML turn several times, if you do computer vision, to the nearly 4 years of ICCV, CVPR, NIPS, ICML turn several times.

(2) Add: Most of the top conference papers can be downloaded from the Internet for free,

For example CV aspect: http://www.cvpapers.com/index.html

nips:http://books.nips.cc/

JMLR (journal): http://jmlr.csail.mit.edu/papers/

Colt and ICML (annual official website): http://www.cs.mcgill.ca/~colt2009/proceedings.html

I hope this information will be of some help to everyone.

(3) say some of your feelings. In the field of computer vision and computational Neuroscience, statistical models (including probabilistic graphical model and statistical learning theory) are mainstream and very influential in terms of methods and models. There is a very obvious trend: important methods and models appear first in Nips or ICML, and then applied to cv,ir and MM. Although specific problems and applications are also important, it is also meaningful to focus on and combine these approaches.

The importance of top-level conferences in the field of computer vision and machine learning (RPM)