Fwd: SDM 19: MLRec 19 CFP

[Deguang Kong]

Apologize if not interested.

SDM 2019 : MLRec 2019 : 5th International Workshop on Machine Learning
Methods for Recommender Systems

CALL FOR PAPER

http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=84278&copyownerid=72965

Following the success of the several editions of MLRec in 2015, 2016, 2017,
and 2018, the fifth edition of the MLRec workshop focuses on developing
novel, and applying existing Machine Learning (ML) and Data Mining (DM)
methods to improve recommender systems. This workshop also highly
encourages applying ML-based recommendation algorithms in novel application
domains (e.g., precision medicine), deep learning for recommendation, and
solving novel recommendation problems formulated from industry. The
ultimate goal of the MLRec workshop series is to promote the advancement
and implementation of new, effective and efficient ML and DM techniques
with high translational potential for real and large-scale recommender
systems, and to expand the territory of ML-based recommender system
research toward non-conventional application areas where recommendation
problems largely exist but haven't been fully recognized.

* Topics of Interest

We encourage submissions on a variety of topics, including but not limited
to:

-- Novel machine learning algorithms for recommender systems, e.g., new
content-based or context-aware recommendation algorithms, new algorithms
for matrix factorization, tensor-based approaches for recommender systems,
etc.

-- Novel applications of existing machine learning and data mining
algorithms for recommender systems, e.g., applying bilinear models,
(non-convex) sparse learning, metric learning, low-rank
approximation/PCA/SVD, neural networks and deep learning, etc.

-- Novel optimization techniques for improving recommender systems, e.g.,
parallel/distributed optimization techniques, efficient stochastic gradient
descent, etc.

-- Industrial practices and implementations of recommendation systems,
e.g., feature engineering, model ensemble, large-scale implementations of
recommender systems, etc.

-- Emerging recommendation problems and scenarios in industry and their
ML-based solutions, e.g., recommendation for e-fashion, etc.

-- Novel recommendation problems in non-conventional recommender system
research areas (e.g., precision medicine, health informatics) and their
ML-based solutions, e.g., recommendation of physicians, recommendation of
healthy life-styles for seniors, etc.

-- Enhanced deep learning methods for recommender systems, e.g., word
embedding techniques, CNN, RNN and LSTM, Generative Advertiseral Networks
(GAN), auto-encoder, RBM, etc.

-- Recommendation in Information Retrieval, ad industry, targeting ad,
search ad, etc.

* Submission Instructions

The workshop accepts long paper and short (demo/poster) papers. Short
papers submitted to this workshop should be limited to 4 pages while long
papers should be limited to 8 pages. All papers should be formatted using
the SIAM SODA macro. Authors are required to submit their papers
electronically in PDF format to the submission site by 11:59pm MDT, March
10, 2019. The site has started to accept manuscripts. At least one author
of each accepted paper should be registered to the conference.

* Important Dates

Paper Submission Deadline: March 10, 2019
Author Notification: Mar 25, 2019
Camera Ready Paper Due: Apr 15, 2019
Workshop: May 4, 2018



Xia Ning, Ohio State University
Deguang Kong, Yahoo Research
George Karypis, University of Minnesota

https://doogkong.github.io/2019/
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