MLRec 2018

4^th International Workshop on Machine Learning Methods for Recommender Systems

In conjunction with 18th SIAM International Conference on Data Mining (SDM 2018)
May 3 - 5, 2018, San Diego, CA, USA

Following the success of the several editions of MLRec in 2015, 2016, 2017, the fourth 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. 

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. 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

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, Jan 15, 2018. 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: Jan 15 2018
• Author Notification: January 23, 2018
• Camera Ready Paper Due: February 1, 2018
• Workshop: May 5, 2018

Organizing committee

• Deguang Kong, Yahoo Research
• Xia Ning, Indiana University – Purdue University Indianapolis 
• George Karypis, University of Minnesota 

Venue

The conference will be held in In conjunction with 18th SIAM International Conference on Data Mining (SDM 2018)
May 3 - 5, 2018, San Diego, CA, USA

Contact

All questions about submissions should be emailed to doogkong@gmail.com, xning@iupui.edu.