# Machine Learning conference info

**URL:** <http://discourse.iapct.org/t/machine-learning-conference-info/6660>\
**Category:** CSG1993\
**Created:** [October 5, 1993, 11:24am UTC](http://discourse.iapct.org/t/machine-learning-conference-info/6660 "1993-10-05T11:24:55Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![bnhpct](http://discourse.iapct.org/user_avatar/discourse.iapct.org/bnhpct/32/34_2.png) [@bnhpct](http://discourse.iapct.org/u/bnhpct)\
**Post date:** [October 5, 1993, 11:24am UTC](http://discourse.iapct.org/t/machine-learning-conference-info/6660/1 "1993-10-05T11:24:55Z")

</div>

Please delete if not interested in Machine Learning conferences.  
I'm just passing this along for those who might want to attend or  
submit a paper on a PCT account of learning and how it might be  
modelled in a machine.

&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Bruce

------- Forwarded Message

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> **···**
>
> To: ML-LIST: ;  
> Subject: Machine Learning List: Vol. 5 No. 21  
> Reply-to: ml@ics.uci.edu  
> Date: Mon, 04 Oct 1993 16:25:21 -0700  
> From: Michael Pazzani \<pazzani@ics.uci.edu\>  
> Message-ID: \<9310041654.aa01992@q2.ics.uci.edu\>
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Machine Learning List: Vol. 5 No. 21  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Monday, October 4, 1993
> 
> Contents:  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ML '94 conference announcement  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;COLT'94: call for papers  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;CFP: AAAI-94 Spring Symposium on Goal-Driven Learning  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;PEBLS 2.0  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ML '94 conference announcement (latex format)
> 
> The Machine Learning List is moderated. Contributions should be relevant to  
> the scientific study of machine learning. Mail contributions to ml@ics.uci.edu.  
> Mail requests to be added or deleted to ml-request@ics.uci.edu. Back issues  
> may be FTP'd from ics.uci.edu in pub/ml-list/V\<X\>/\<N\> or N.Z where X and N are  
> the volume and number of the issue; ID: anonymous PASSWORD: \<your mail address\>
> 
> - ----------------------------------------------------------------------
> 
> Date: Wed, 29 Sep 93 13:23 EDT  
> From: William Cohen \<[wcohen@research.att.COM](mailto:wcohen@research.att.COM)\>  
> To: ml@ics.uci.edu  
> Subject: ML '94 conference announcement
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;CALL FOR PAPERS - ML94  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Eleventh International Conference on Machine Learning  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;New Brunswick, New Jersey  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;July 10-13, 1994
> 
> The Eleventh International Conference on Machine Learning (ML94) will  
> be held at the New Brunswick campus of Rutgers University during July  
> 11-13, 1994, with workshops taking place on July 10th. The  
> conference will be co-located with the Seventh Annual Conference on  
> Computational Learning Theory (COLT94), which will be held July  
> 12-15. We invite submissions to ML94 from researchers in machine  
> learning or related fields, such as psychology, statistics, or  
> neuroscience. The conference will include presentations of refereed  
> papers and invited talks.
> 
> REVIEW CRITERIA. Each submitted paper will be reviewed by at least two  
> members of the program committee, and be judged on clarity,  
> significance, and originality. Submissions should contain new results  
> that have not been published previously. Submissions to ML94 may be  
> submitted to other conferences, but if so a statement to this effect  
> must appear on the title page.
> 
> PAPER FORMAT. Submissions must be clearly legible, with good quality  
> print. Papers are limited to a total of twelve (12) pages, excluding  
> title page and bibligraphy, but including all tables and figures.  
> Papers must be printed on 8 1/2" x 11" or A4 paper using 12 point type  
> (10 characters per inch for typewriters). Each page must have a  
> maximum of 38 lines and an average of 75 characters per line  
> (corresponding to the LaTeX article style, 12 point). Papers not  
> adhering to this format may be returned without review. Double-sided  
> printing is strongly encouraged. The title page of each paper must  
> include the e-mail and postal addresses of all authors, an abstract,  
> and one or more keywords from the following list to aid in the  
> reviewing process: analogy, Bayesian learning, case-based reasoning,  
> cognitive modeling, computational learning theory, concept formation,  
> decision trees, discovery, explanation-based learning, genetic  
> algorithms, inductive logic programming, instance-based learning,  
> knowledge acquisition, minimum description length, neural networks,  
> reformulation, reinforcement learning, scientific theory formation,  
> speedup learning, theory refinement, unsupervised learning,  
> constructive induction, multi-strategy learning.
> 
> REQUIREMENTS FOR SUBMISSION. Authors must submit five copies of their  
> papers to the address below; electronic or FAX submission is not  
> acceptable. Papers must be received by February 8, 1994. Notification  
> of acceptance or rejection will be mailed to the first (or designated)  
> author by March 25, 1994. Camera-ready copy of accepted papers will  
> be due April 26, 1994. Send conference paper submissions to: William  
> W. Cohen, ATT Bell Laboratories, 600 Mountain Avenue, Room 2A-427,  
> Murray Hill, NJ 07974 (908)-582-2092.
> 
> INFORMAL WORKSHOPS. Proposals are invited for informal workshops in  
> areas of interest related to machine learning. Send a two-page  
> proposal to: Russell Greiner, ML94 Workshop Chair, Siemens Corporate  
> Research, 755 College Road East, Princeton, NJ 08540, by December 1,  
> 1993, indicating the organizer(s), nature and objective of the  
> proposed workshop, and the likely number of attendees.
> 
> GENERAL INQUIRIES:  
> ml94@cs.rutgers.edu
> 
> CONFERENCE CO-CHAIRS:  
> William W. Cohen Haym Hirsh  
> ATT Bell Laboratories Department of Computer Science  
> 600 Mountain Avenue Rutgers University  
> Murray Hill, NJ 07974 New Brunswick, NJ 08903  
> [wcohen@research.att.com](mailto:wcohen@research.att.com) hirsh@cs.rutgers.edu
> 
> PROGRAM COMMITTEE:  
> David Aha, NRL  
> Yuichiro Anzai, Keio U.  
> Eric Baum, NEC  
> Francesco Bergadano, U. Torino  
> Wray Buntine, NASA  
> Jason Catlett, ATT  
> Marie des Jardins, SRI  
> Tom Dietterich, Oregon St. U.  
> Doug Fisher, Vanderbilt U.  
> John Grefenstette, NRL  
> Russ Greiner, Siemens  
> Geoff Hinton, U. Toronto  
> Leslie Kaelbling, Brown U.  
> Dennis Kibler, UCI  
> John Laird, U. Michigan  
> Sridhar Mahadevan, S. Florida  
> Hiroshi Motoda, Hitachi  
> Ray Mooney, U. Texas  
> Katharina Morik, U. Dortmund  
> Mike Pazzani, UCI  
> Lenny Pitt, U. Illinois  
> Lorien Pratt, Colorado S. of Mines  
> Armand Prieditis, UC/Davis  
> Paul Rosenbloom, USC/ISI  
> Stuart Russell, UCB  
> Lorenza Saitta, U. Torino  
> Claude Sammut, U. New S. Wales  
> Cullen Schaffer, Hunter College  
> Rich Sutton, GTE  
> Paul Utgoff, U. Mass  
> Stefan Wrobel, GMD  
> Steve Whitehead, GTE  
> Manuela Veloso, CMU  
> Kenji Yamanishi, NEC
> 
> WORKSHOP CHAIR:  
> Russell Greiner  
> Siemens Corporate Research  
> 755 College Road East  
> Princeton, NJ 08540  
> [greiner@learning.scr.siemens.com](mailto:greiner@learning.scr.siemens.com)
> 
> LOCAL ARRANGEMENTS:  
> Priscilla Rasmussen  
> Department of Computer Science  
> Rutgers University  
> New Brunswick, NJ 08903  
> rasmusse@cs.rutgers.edu
> 
> - ------------------------------
> 
> Date: Sat, 2 Oct 93 01:56:58 -0400  
> From: Ming Li \<mli@math.uwaterloo.ca\>  
> Subject: COLT'94: call for papers
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;CALL FOR PAPERS---COLT 94  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Seventh ACM Conference on  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Computational Learning Theory
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;New Brunswick, New Jersey  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;July 12--15, 1994
> 
> The Seventh ACM Conference on Computational Learning Theory (COLT  
> 94) will be held at the New Brunswick campus of Rutgers  
> University from Tuesday, July 12, through Friday, July 15, 1994.  
> The conference will be co-located with the Eleventh International  
> Conference on Machine Learning (ML 94), which will be held from  
> Sunday, July 10, through Wednesday, July 13. So the two  
> conferences overlap on Tuesday and Wednesday.
> 
> The COLT 94 conference is sponsored jointly by the ACM Special  
> Interest Groups for Algorithms and Computation Theory (SIGACT)  
> and Artificial Intelligence (SIGART).
> 
> We invite papers in all areas that relate directly to the  
> analysis of learning algorithms and the theory of machine  
> learning, including artificial and biological neural networks,  
> robotics, pattern recognition, inductive inference, information  
> theory, decision theory, Bayesian/MDL estimation, statistical  
> physics, and cryptography. We look forward to a lively,  
> interdisciplinary meeting. In particular we expect some fruitful  
> interaction between the research communities of the two  
> overlapping conferences. There will be a number of joint invited  
> talks. Prof. Michael Jordan from MIT will be one of the invited  
> speakers; the others will be announced at a later date.
> 
> Abstract Submission: Authors should submit twelve copies  
> (preferably two-sided copies) of an extended abstract to be  
> received by Thursday, February 3, 1994, to
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Manfred Warmuth - COLT 94  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;225 Applied Sciences  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Department of Computer Science  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;University of California  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Santa Cruz, California 95064
> 
> An abstract must be received by February 3, 1994 (or  
> postmarked January 23 and sent airmail, or sent overnight  
> delivery on February 2). This deadline is FIRM! Papers that have  
> appeared in journals or other conferences, or that are being  
> submitted to other conferences, are not appropriate for  
> submission to COLT.
> 
> Abstract Format: The abstract should consist of a cover page with  
> title, authors' names, postal and e-mail addresses, and a 200-  
> word summary. The body of the abstract should be no longer than  
> 10 pages with roughly 35 lines/page in 12-point font. Papers  
> deviating significantly from this length constraint will not be  
> considered. The body should include a clear definition of the  
> theoretical model used, an overview of the results, and some  
> discussion of their significance, including comparison to other  
> work. Proofs or proof sketches should be included in the  
> technical section. Experimental results are welcome, but are  
> expected to be supported by theoretical analysis.
> 
> Notification: Authors will be notified of acceptance or rejection  
> by a letter mailed on or before Monday, April 4, with possible  
> earlier notification via e-mail. Final camera-ready papers will  
> be due on Tuesday, May 3.
> 
> Program Format: Depending on submissions, and in order to  
> accommodate a broad variety of papers, the final program may  
> consist of both "long" talks, and "short" talks, corresponding to  
> longer and shorter papers in the proceedings. The short talks  
> will also be coupled with a poster presentation in special poster  
> sessions. By default, all papers will be considered for both  
> categories. Authors who do \*not\* want their papers considered  
> for the short category should indicate that fact in the cover  
> letter. The cover letter should also specify the contact author  
> and give his/her e-mail.
> 
> Program Chair: Manfred Warmuth (UC Santa Cruz, e-mail to  
> colt94@cse.ucsc.edu).
> 
> Conference and Local Arrangements Co-Chairs: Robert Schapire and  
> Michael Kearns (AT&T Bell Laboratories, e-mail to  
> [colt94@research.att.com](mailto:colt94@research.att.com)).
> 
> Program Committee: Shun'ichi Amari (U. Tokyo), Avrim Blum  
> (Carnegie Mellon), Nader Bshouty (U. Calgary), Bill Gasarch (U.  
> Maryland), Tom Hancock (Siemens), Michael Kearns (AT&T), Sara  
> Solla (Holmdel), Prasad Tadepalli (Oregon St. U.), Jeffrey  
> Vitter (Duke U.), Thomas Zeugmann (TU. Darmstadt).
> 
> - ------------------------------
> 
> Date: Mon, 4 Oct 93 15:29:22 EDT  
> From: Ashwin Ram \<ashwin@cc.gatech.EDU\>  
> Subject: CFP: AAAI-94 Spring Symposium on Goal-Driven Learning
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;CFP: AAAI-94 Spring Symposium on Goal-Driven Learning
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;AAAI-94 SPRING SYMPOSIUM ON  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;GOAL-DRIVEN LEARNING  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Stanford University  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;March 21-23, 1994
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;CALL FOR PARTICIPATION
> 
> Program Committee:  
> &nbsp;&nbsp;&nbsp;&nbsp;Marie desJardins (co-chair) Lawrence Hunter  
> &nbsp;&nbsp;&nbsp;&nbsp;Foster John Provost Ashwin Ram (co-chair)
> 
> Goal-driven learning refers to the process of using the overall goals  
> of an intelligent system to make decisions about when learning should  
> occur, what should be learned, and which learning strategies are  
> appropriate in a given context. This focusing process may take place  
> at any decision point during learning---for example, when determining  
> what to learn, selecting a bias, pruning the space of theories to be  
> considered, or generating experiments for data gathering. Research in  
> psychology, education, and AI has shown the need for intelligent  
> systems to make decisions about what and how to learn. The common  
> rationale, and the principle around which the symposium will be  
> organized, is that the value of learning depends on how well it  
> satisfies the goals of the system. The symposium will bring together  
> researchers from diverse research areas to discuss issues in how  
> learning goals arise, how they affect learner decisions of when and  
> what to learn, and how they guide the learning process.
> 
> Topics addressed by the symposium will span the diverse work in this  
> area, which includes research in formulating learning goals,  
> experiment generation, utility of knowledge assessment, evaluating and  
> selecting learning biases, explanation-based learning, learning from  
> texts, active learning, case-based reasoning, formal analyses of  
> decision making, automated question generation, knowledge acquisition  
> planning, reinforcement learning, and control theory. We encourage  
> researchers from fields other than these to submit papers on related  
> research.
> 
> In addition to technical presentations, the symposium will include a  
> session of invited talks on relevant topics, such as formal utility  
> analyses of learning, automated experiment planning, psychological  
> evidence for goal-driven learning behavior in humans, human  
> educational motivation, and question generation. Depending on the  
> number and quality of submitted papers, we may include a poster  
> session as well. If there is sufficient overlap, we will arrange a  
> joint session with the symposium on Decision-Theoretic Planning.
> 
> Time will be set aside for debate and discussion during the technical  
> sessions, and the symposium will conclude with a panel and audience  
> discussion of the issues raised during the symposium. Members of the  
> concluding panel will be selected during the meeting, with the  
> intention of creating a panel representative of the viewpoints  
> expressed at the symposium.
> 
> In order to stimulate debate and discussion on future directions for  
> research as well as evaluation of existing approaches to goal-driven  
> learning, we encourage the submission of extended abstracts describing  
> work in progress, position papers, and papers describing innovative  
> unexplored approaches, as well as papers describing mature research  
> results.
> 
> If you wish to present a paper, please submit four hardcopies of a  
> paper or extended abstract by October 15 to:  
> &nbsp;&nbsp;&nbsp;&nbsp;Prof. Ashwin Ram  
> &nbsp;&nbsp;&nbsp;&nbsp;College of Computing  
> &nbsp;&nbsp;&nbsp;&nbsp;Georgia Institute of Technology  
> &nbsp;&nbsp;&nbsp;&nbsp;Atlanta, GA 30332-0280  
> &nbsp;&nbsp;&nbsp;&nbsp;(404) 853-9372  
> Shorter submissions (under five pages) are encouraged; however, longer  
> submissions (up to ten pages) will be accepted.
> 
> If you wish only to participate in the workshop, please submit two  
> hardcopies of a research summary describing your relevant research  
> interests.
> 
> Questions may directed to Ashwin Ram (ashwin@cc.gatech.edu) or to  
> Marie desJardins ([marie@erg.sri.com](mailto:marie@erg.sri.com)).
> 
> SCHEDULE:  
> &nbsp;&nbsp;&nbsp;&nbsp;October 15, 1993 Papers due  
> &nbsp;&nbsp;&nbsp;&nbsp;November 15, 1993 Acceptance/rejection notices mailed  
> &nbsp;&nbsp;&nbsp;&nbsp;January 31, 1994 Camera-ready papers due  
> &nbsp;&nbsp;&nbsp;&nbsp;February 15, 1994 Registration deadline for invitees  
> &nbsp;&nbsp;&nbsp;&nbsp;March 1, 1994 Final registration deadline  
> &nbsp;&nbsp;&nbsp;&nbsp;March 21-23 Symposium at Stanford Univ.
> 
> - ------------------------------
> 
> Date: Fri, 1 Oct 93 17:11:43 EDT  
> From: salzberg@blaze.cs.jhu.EDU  
> Subject: PEBLS 2.0
> 
> \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ANNOUNCEMENT
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;PEBLS 2.0 is now available via Anonymous FTP.  
> \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;PEBLS (Parallel Exemplar-Based Learning System) is a  
> nearest-neighbor learning system designed for applications  
> where the instances have symbolic feature values. PEBLS has  
> been applied to the prediction of protein secondary  
> structure based on the primary amino acid sequence of  
> protein sub-units, and to the identification of DNA promoter  
> sequences. A technical description appears in the article  
> by Cost and Salzberg, Machine Learning journal 10:1 (1993).
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;PEBLS 2.0 is a serial version written entirely in ANSI  
> C. PEBLS 2.0 incorporates a number of features intended  
> to support flexible experimentation in symbolic domains. We  
> have provided support for k-nearest neighbor learning, and  
> the ability to choose among different techniques for  
> weighting both exemplars and individual features. A number  
> of post-processing techniques specific to the domain of  
> protein secondary structure have also been provided.
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;TO OBTAIN PEBLS BY ANONYMOUS FTP  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The latest version of PEBLS is available free of charge, and  
> may be obtained via anonymous FTP from the Johns Hopkins  
> University Computer Science Department.
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;To obtain a copy of PEBLS, type the following commands:
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;UNIX\_prompt\> ftp blaze.cs.jhu.edu  
> [Note: the Internet address of blaze.cs.jhu.edu is 128.220.13.50]  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Name: anonymous  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Password: [enter your email address]
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\> bin  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\> cd pub/pebls  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\> get pebls.tar.Z  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\> bye
> 
> [Place the file pebls.tar.Z in a convenient subdirectory.]
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;UNIX\_prompt\> uncompress pebls.tar.Z  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;UNIX\_prompt\> tar -xf pebls.tar
> 
> [Read the files "README" and "pebls.doc"]
> 
> For further information, contact:
> 
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Prof. Steven Salzberg  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Dept. of Computer Science  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;The Johns Hopkins University  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Baltimore, MD 21210  
> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Email: salzberg@cs.jhu.edu
> 
> PEBLS 2.0 IS INTENDED FOR RESEARCH PURPOSES ONLY. PEBLS 2.0 may be  
> used, copied, and modified for this purpose. Any commercial use of  
> PEBLS 2.0 is strictly prohibited without the express written consent  
> of Prof. Steven Salzberg, Department of Computer Science, The Johns  
> Hopkins University.
> 
> - ------------------------------
> 
> Date: Thu, 30 Sep 93 09:49 EDT  
> From: William Cohen \<[wcohen@research.att.COM](mailto:wcohen@research.att.COM)\>  
> Subject: ML '94 conference announcement (latex format)
> 
> \documentstyle{article}
> 
> \setlength\topmargin{-0.8in}  
> \setlength\oddsidemargin{-0.2in}  
> \setlength\textheight{9.6in}  
> \setlength\textwidth{7.1in}  
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> 
> \begin{document}  
> %\setlength{\baselineskip}{0.9\baselineskip}  
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> 
> \newcommand{\myheading}[3]{\vspace{#1pt}{\large\bf #2.}}
> 
> \begin{minipage}[t]{4.5in}  
> %\fbox{%  
> \begin{minipage}[t]{4.4in}  
> \begin{center}  
> \ \hrulefill\  
> \\  
> \vspace\*{5pt}  
> {\large\bf CALL FOR PAPERS---ML94}\\%  
> \vspace\*{2pt}  
> {\LARGE\bf{Eleventh International Conference on Machine Learning}\\%  
> \vspace\*{2pt}  
> \Large\bf{New Brunswick, New Jersey\\  
> July 10--13, 1994}\\%  
> }\ \hrulefill\  
> \\  
> \vspace\*{7pt}  
> \end{center}  
> \end{minipage}%}
> 
> The Eleventh International Conference on Machine Learning (ML94) will  
> be held at the New Brunswick campus of Rutgers University during July  
> 11--13, 1994, with workshops taking place on July 10th. The  
> conference will be co-located with the Seventh Annual Conference on  
> Computational Learning Theory (COLT94), which will be held July  
> 12--15. We invite submissions to ML94 from researchers in machine  
> learning or related fields, such as psychology, statistics, or  
> neuroscience. The conference will include presentations of refereed  
> papers and invited talks.
> 
> \myheading{7}{Review Criteria}{2}  
> Each submitted paper will be reviewed by at least two members of the  
> program committee, and be judged on clarity, significance, and  
> originality. Submissions should contain new results that have not  
> been published previously. Submissions to ML94 may be submitted to  
> other conferences, but if so a statement to this effect must appear on  
> the title page.
> 
> \myheading{7}{Paper Format}{2}  
> Submissions must be clearly legible, with good quality print. Papers  
> are limited to a total of twelve (12) pages, excluding title page and  
> bibligraphy, but including all tables and figures. Papers must be  
> printed on 8 1/2" x 11" or A4 paper using 12 point type (10 characters  
> per inch for typewriters). Each page must have a maximum of 38 lines  
> and an average of 75 characters per line (corresponding to the  
> \LaTeX{} article style, 12 point). Papers not adhering to this format  
> may be returned without review. Double-sided printing is strongly  
> encouraged. The title page of each paper must include the e-mail and  
> postal addresses of all authors, an abstract, and one or more keywords  
> from the following list to aid in the reviewing process: analogy,  
> Bayesian learning, case-based reasoning, cognitive modeling,  
> computational learning theory, concept formation, decision trees,  
> discovery, explanation-based learning, genetic algorithms, inductive  
> logic programming, instance-based learning, knowledge acquisition,  
> minimum description length, neural networks, reformulation,  
> reinforcement learning, scientific theory formation, speedup learning,  
> theory refinement, unsupervised learning, constructive induction,  
> multi-strategy learning.
> 
> \myheading{7}{Requirements for Submission}{2}  
> Authors must submit five copies of their papers to the address below;  
> electronic or FAX submission is not acceptable. Papers must be  
> received by February 8, 1994. Notification of acceptance or rejection  
> will be mailed to the first (or designated) author by March 25, 1994.  
> Camera-ready copy of accepted papers will be due April 26, 1994. Send  
> conference paper submissions to: William W. Cohen, AT\&T Bell  
> Laboratories, 600 Mountain Avenue, Room 2A-427, Murray Hill, NJ 07974  
> (908)-582-2092.
> 
> \myheading{7}{Informal Workshops}{2}  
> Proposals are invited for informal workshops in areas of interest  
> related to machine learning. Send a two-page proposal to: Russell  
> Greiner, ML94 Workshop Chair, Siemens Corporate Research, 755 College  
> Road East, Princeton, NJ 08540, by December 1, 1993, indicating the  
> organizer(s), nature and objective of the proposed workshop, and the  
> likely number of attendees.  
> \end{minipage}~~~  
> \begin{small}  
> \begin{minipage}[t]{2in}  
> \begin{tabbing}  
> ~\\[-0.5\baselineskip]  
> {\bf General Inquiries:}\\  
> ml94@cs.rutgers.edu\\  
> ~\\[-0.5\baselineskip]  
> {\bf Conference Co-Chairs:}\\  
> William W. Cohen\\  
> AT\&T Bell Laboratories\\  
> 600 Mountain Avenue\\  
> Murray Hill, NJ 07974\\  
> {\tt [wcohen@research.att.com](mailto:wcohen@research.att.com)}\\  
> ~\\[-0.75\baselineskip]  
> Haym Hirsh\\  
> Department of Computer Science\\  
> Rutgers University\\New Brunswick, NJ 08903\\  
> {\tt hirsh@cs.rutgers.edu}\\  
> ~\\[-0.5\baselineskip]  
> {\bf Program Committee:}\\  
> David Aha, NRL \\  
> Yuichiro Anzai, Keio U. \\  
> Eric Baum, NEC \\  
> Francesco Bergadano, U. Torino \\  
> Wray Buntine, NASA\\  
> Jason Catlett, AT\&T \\  
> Marie des Jardins, SRI \\  
> Tom Dietterich, Oregon St. U. \\  
> Doug Fisher, Vanderbilt U. \\  
> John Grefenstette, NRL \\  
> Russ Greiner, Siemens \\  
> Geoff Hinton, U. Toronto \\  
> Leslie Kaelbling, Brown U. \\  
> Dennis Kibler, UCI \\  
> John Laird, U. Michigan \\  
> Sridhar Mahadevan, S. Florida \\  
> Hiroshi Motoda, Hitachi \\  
> Ray Mooney, U. Texas \\  
> Katharina Morik, U. Dortmund \\  
> Mike Pazzani, UCI \\  
> Lenny Pitt, U. Illinois \\  
> Lorien Pratt, Colorado S. of Mines \\  
> Armand Prieditis, UC/Davis \\  
> Paul Rosenbloom, USC/ISI \\  
> Stuart Russell, UCB \\  
> Lorenza Saitta, U. Torino \\  
> Claude Sammut, U. New S. Wales \\  
> Cullen Schaffer, Hunter College \\  
> Rich Sutton, GTE \\  
> Paul Utgoff, U. Mass \\  
> Stefan Wrobel, GMD \\  
> Steve Whitehead, GTE \\  
> Manuela Veloso, CMU \\  
> Kenji Yamanishi, NEC\\  
> ~\\[-0.5\baselineskip]  
> {\bf Workshop Chair:}\\  
> Russell Greiner\\  
> Siemens Corporate Research\\  
> 755 College Road East\\  
> Princeton, NJ 08540\\  
> {\tt [greiner@learning.scr.siemens.com](mailto:greiner@learning.scr.siemens.com)}\\  
> ~\\[-0.5\baselineskip]  
> {\bf Local Arrangements:}\\  
> Priscilla Rasmussen\\  
> Department of Computer Science\\  
> Rutgers University\\  
> New Brunswick, NJ 08903\\  
> {\tt rasmusse@cs.rutgers.edu}  
> \end{tabbing}  
> \end{minipage}\end{small}
> 
> \end{document}
> 
> - ------------------------------
> 
> End of ML-LIST (Digest format)  
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