We solicit four types of submissions:
1.Journal track submissions: accepted papers will be published in the Machine Learning Journal Special Issue on ILP 2019.
The journal track has three cutoff dates: 18 Jan 2019, 1 Feb 2019 and 25 Feb 2019 (extended). Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. All papers will be reviewed following standard reviewing procedures for the Machine Learning Journal. The editorial team will be aiming for a turnround time of 10 weeks for most submissions. If a rejected submission is later resubmitted to the conference track, the authors must specify how they have taken into account the journal track reviews.
Papers must be prepared in accordance with the Journal guidelines: http://www.springer.com/10994
Manuscripts must be submitted to: http://MACH.edmgr.com
An article is submitted to this special issue by choosing “S.I. : ILP 2019” as the article type. Articles should preferably be no longer than 20 pages, and submissions exceeding this length will not be given priority during reviews and may be under review for a longer period.
2.Conference papers describing original work containing appropriate experimental evaluation and/or representing a self-contained theoretical contribution. Submissions to this category of papers must not have been published or be under review for a journal or for another conference with published proceedings. Submissions can be in the form of long papers of up to 15 pages (including references) or short papers of between 6 and 9 pages (incl. references). Papers making a more focussed contribution should be submitted as short papers, while the long paper format is expected to be reserved for submissions reporting a substantial volume of work, e.g. detailed proofs or extensive experimental studies. All submissions must show rigour and novelty and/or impact. Reviewers will be asked to consider whether the chosen page limit is appropriate, and authors may be requested to revise the length of their paper before it is published. Accepted paper submissions will be published as a volume of Springer LNAI proceedings. Conference paper abstracts need to be registered by
25 30 May 2019, with full submissions due by 1 June 3 June 2019.
3.Late breaking abstracts not exceeding 4 pages (incl. references) in the Springer LNCS/LNAI format, and outlining original work in progress, brief accounts of original ideas without conclusive experimental evaluation, and other relevant work of potentially high scientific interest but not yet ready for publication. Late-breaking abstracts will be accepted/rejected on the grounds of relevance. Authors of these submissions will be assigned a reduced time slot for presentation. The late breaking abstracts will be published on the conference web site only.
Late breaking abstracts deadline: 15 July 2019.
4.Papers relevant to the conference topics and recently published or accepted for publication by highly rated conferences such as ECML/PKDD, ICML, KDD, ICDM, AAAI, IJCAI or journals, such as MLJ, DMKD or JMLR. These should be submitted in their original format and will be accepted/rejected on the grounds of relevance and quality of the original publication venue. Authors of such papers will be assigned a reduced time slot for presentation and will not appear in the conference proceedings, however a link to the original work will be published on the conference web site.
Published papers deadline: 15 July 2019.
For all types of submissions (including the journal track), at least one of the authors of accepted papers must register for the conference, and present the work.
Submissions must describe relevant and novel results on the following typical, but not exclusive, topics:
Learning in logics: logical-foundations of learning; computational/statistical learning theory; specialisation and generalisation; probabilistic logic-based learning; graph and tree mining; algorithms and approaches for learning with (semi-)structured data; (semi-)supervised and unsupervised relational learning; relational reinforcement learning; predicate invention; propositionalization approaches; multi-instance learning; learning in the presence of uncertainty; meta-level learning.
Knowledge Representation: logic programming; Datalog; first-order logic; description logics and ontologies; higher-order logic; Answer Set Programming; probabilistic logic languages; constraint logic programming; knowledge graphs.
Applications of learning: art; bioinformatics; systems biology; games; medical informatics; robotics; natural language processing; web-mining; software engineering; financial applications; modelling and adaptation of control systems; socio-technical systems.
Submissions on theoretical and applied work bridging into areas such as cognitive technologies, neural networks and deep relational learning, knowledge acquisition from big data and the cloud are also encouraged.
Awards and Sponsors
The conference will give best paper awards in the following categories:
- the Best Paper Award will be chosen among the long papers submitted at the conference and the papers accepted in the journal track. The prize fund of €1,000 is kindly sponsored by Springer;
- Best Student Paper Awards, namely:
- Best Student Paper (long papers) (for submissions to the journal track or long paper/conference track)
- Best Student Paper (short papers) (for submissions to the short paper/conference track).
To qualify for either student paper award, the first author must be a student at the time of submitting the paper. The option “Enlist for the Student Paper Award” should be checked when submitting eligible papers. Each award is worth $750. These awards are kindly provided by the Machine Learning Journal.