Publication schedule (as of May 8, 2011)
- Jan 7, 2011: Paper submission due (closed)
- March 5: Author notification
- May 5: Paper revision due
- Jun 14: Final author notification
- Oct. 1: Publication
The Institute of Electronics, Information and Communication Engineers (IEICE) Transactions on Information and Systems announces a forthcoming special issue on Information-Based Induction Sciences and Machine Learning to be published in October 2011.
Recently, a huge mount of data becomes readily available through the internet and various sensors, and machine learning technology for finding underlying rules and acquiring useful knowledge gathers considerable attention. From the theoretical side, machine learning has close connection to basic science such as information theory, statistics, computer science, and statistical physics. Thus, fundamental theory of machine learning is expected to be further developed through interdisciplinary collaboration. On the other hand, from the application side, machine learning technology plays an important role in various fields including signal processing, natural language processing, speech processing, image processing, biology, robot control, financial engineering, and data mining. These application areas possess high potential for real-world industry, and will be further expanded by sharing common methodological challenges.
Following the growing interests in the area of machine learning, the new technical group named Information-Based Induction Sciences and Machine Learning (IBISML) has started since April 2010 as a successor of IEICE SIG-IBIS and JSAI SIG-DMSM. Also, in November 2010, the IBISML technical group will host the 13th IBIS Workshop (Workshop on Information-Based Induction Sciences), which is one of the most vital machine learning events in the world. The objective of this special issue is to publish and overview recent advances in the interdisciplinary area of machine learning.
We solicit papers on various disciplines of machine learning including, but not limited to the following topics:
- Theory of machine learning including information theoretic, statistical, computational, and statistical physical approaches.
- Applications of machine learning including data mining, signal processing, pattern recognition, natural language, speeches, images, bioinformatics, financial engineering, robot control, life science, and brain science.
2. Submission Guidelines
A manuscript should be prepared according to the guideline given in “The Information for Authors”. We encourage the authors to use the IEICE Style File. The preferred length of the manuscript is 8 pages for a PAPER and 2 pages for a LETTER with the format determined by the IEICE Style File.
Submit the manuscript through the IEICE Web site. Choose “[Special-ED] Information-Based Induction Sciences and Machine Learning” in the menu of “Type of Issue (Section) / Transactions”in the submission page.
Submission deadline of the manuscript is
December 31, 2010. (extended Jan. 7, 2011) closed.
By the submission deadline, send
- “Confirmation Sheet of Manuscript Registration” and
- “Copyright Transfer and Page Charge Agreement”
to the Guest Editor-in-Chief by post, fax or e-mail:
- Tsuyoshi Ide
- Email: goodidea [at] jp.ibm.com (replace [at] with @)
- Postal address: IBM Research – Tokyo, LAB-S7B, 1623-14, Shimotsuruma, Yamato, Kanagawa 242-8502, Japan
- Fax: +81-46-273-7428
3. Notice to the Authors
If the paper is accepted, authors are requested to pay for the page charge which covers reprints of the paper and partial cost of publications.
The standard period of 60 days between the notification (of conditional accept) and the second submission can be shortened according as the review schedule.
At least one of the authors must be an IEICE member when the manuscript is submitted for review. We recommend authors unaffiliated with IEICE to apply for the membership. For the details of the IEICE Membership, visit here.
4. Special Section Editorial Committee
Masashi Sugiyama (Tokyo Institute of Technology)
Guest Editorial Manager
Tsuyoshi Ide (IBM Research – Tokyo)
Guest Associate Editors:
- Kenji Yamanishi (University of Tokyo)
- Naonori Ueda (NTT)
- Tomoyuki Higuchi (The Institute of Statistical Mathematics)
- Toshiyuki Tanaka (Kyoto University)
- Shin Ishii (Kyoto University)
- Kenji Fukumizu (The Institute of Statistical Mathematics)
- Yuji Matsumoto (Nara Institute of Science and Technology)
- Shotaro Akaho (National Institute of Advanced Industrial Science and Technology)
- Takashi Washio (Osaka University)
- Kazushi Ikeda (Nara Institute of Science and Technology)
- Daichi Mochihashi (NTT)
- Hisashi Kashima (University of Tokyo)
- Toshihiro Kamishima (National Institute of Advanced Industrial Science and Technology)
- Shigeyuki Oba (Kyoto University)
- Koji Tsuda (National Institute of Advanced Industrial Science and Technology)
- Akisato Kimura (NTT)