Call for Papers

Reinforcement learning (RL) and multi-armed bandits (MAB) have been powering e-Commerce and other industrial applications since the early days of the field. Today, MAB and RL already play a significant role in e-commerce tasks, including product search, recommender systems, advertising, and pricing, among many other tasks. With the exploding popularity of stochastic optimization and decision-making under uncertainty, RL and MAB researchers are poised to transform e-commerce once again but requires a forum where new and unfinished ideas could be discussed. This workshop aims to provide a venue for the dissemination of late-breaking research results and ideas related to e-commerce and other application fields, bringing together researchers from both academia and industry. The workshop welcomes the submission of late-breaking and preliminary research results, as well as opinion and position papers.

All submissions will undergo a double-blind review process, and accepted submissions will be presented at the workshop. Based on length, the submissions can be long papers (without length restrictions), short papers (3-8 pages), and extended abstracts (1-2 pages). Specifically and not exclusively, we invite research contributions in different formats:

• Original research papers

• Vision, opinion, and position papers

• System Demonstrations

• Extended abstracts for talks or panel discussion proposals

Original research papers

Original research papers are solicited for the following set of non-exhaustive topics:

• Theories and applications of reinforcement learning and multi-armed bandits

• Recommender systems and product suggestions, semantic recommendation

• Search and product query auto-completion

• Supply-chain optimization

• Fraud and spam detection in e-commerce

• Computational advertising

• Deep reinforcement learning for microeconomics theory

• Multi-armed ​bandit​s for online advertising and pricing

• Contextual MAB for personalized dynamic recommendations

 
Additionally, we also encourage topics from the following areas:

• ML applications in e-commerce and industries

• AI chatbot voice-mining for promo and recommendations

• AI for ad creatives and publishers

• AI algorithm bias, interpretable ML

• Shopping assistants, agents, and chat bots

• E-commerce-related social media processing

• ML applications in web search, question answering, personalization

Vision, Opinion, and Position Papers

We will also accept a small number of vision, opinion, and position papers that provide discussions on challenges and roadmaps (for MAB or RL-centric systems, applications, and emerging models for e-commerce and product data).

System Demonstrations

We encourage system demonstration papers dedicated to illustrating how MAB or RL systems are designed, implemented, maintained. Related topics include:

• Design and implementation of scalable RL or MAB systems

• Data and privacy protection

• Addressing bias and vulnerabilities in deployed systems

• Improving the reliability of deployed systems

Extended Abstracts

The extended abstract should clearly explain the motivation, research problem, methodology, results, and contributions.

Key Dates: 

• Submission Deadline: June 6, 2023 (Anywhere on Earth)

• Acceptance Notification:  June 23, 2023

• Camera Ready: July 6, 2023

• Workshop: August 7, 2023

Submission Directions

Submissions may take the form of long papers (without length restrictions), short papers (3-8 pages), and extended abstracts (1-2 pages), including all content and references, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip acmart-master.zip and use sample-sigconf.tex as a template.

The review process is single-round and double-blind (submission files have to be anonymized). Accepted papers will be presented during the workshop and listed on the workshop website (non-archival). Papers that do not meet the formatting requirements will be rejected without review. The accepted papers will be published online and will not be considered archival. Proceedings will be available for download after the conference.

We are using the CMT system for submissions. Please visit https://cmt3.research.microsoft.com/MarbleKDD2023/Track/1/Submission for your submission.

If you have any question, please email marble-kdd@googlegroups.com.