​Workshop官网：

https://neurips-hill.github.io/ 

Workshop联合承办方：

Machine Intelligence Research (MIR)

Recent years have witnessed the rising need for machine learning systems that can interact with humans in the learning loop. Such systems can be applied to computer vision, natural language processing, robotics, and human-computer interaction. Creating and running such systems call for interdisciplinary research of artificial intelligence, machine learning, and software engineering design, which we abstract as Human in the Loop Learning (HiLL).

The HiLL workshop aims to bring together researchers and practitioners working on the broad areas of HiLL, ranging from interactive/active learning algorithms for real-world decision-making systems (e.g., autonomous driving vehicles, robotic systems, etc.), human-inspired learning that mitigates the gap between human intelligence and machine intelligence, human-machine collaborative learning that creates a more powerful learning system, lifelong learning that transfers knowledge to learn new tasks over a lifetime, as well as interactive system designs (e.g., data visualization, annotation systems, etc.).

The HiLL workshop continues the previous effort to provide a platform for researchers from interdisciplinary areas to share their recent research. In this year’s workshop, a special feature is to encourage the discussion on the interactive and collaborative learning between human and machine learning agents: Can they be organically combined to create a more powerful learning system? We believe the theme of the workshop will be of interest to broad NeurIPS attendees, especially those who are interested in interdisciplinary study.

​We welcome high-quality submissions on algorithms and system designs in the broad area of human in the loop learning.

The topics of HiLL include but are not limited to:

Human-machine collaborative learning,

Human-inspired learning,

Interactive robot learning,

Interactive machine learning algorithms for autonomous decision-making systems,

Lifelong learning systems,

Online learning and active learning,

Psychology driven human concept learning,

Design, testing, and assessment of interactive systems for data analytics.

These topics span a variety of scientific disciplines and application domains like machine learning, human-computer interaction, cognitive science, and robotics. It is an opportunity for scientists in these disciplines to share their perspectives, discuss solutions to common problems and highlight the challenges in the field to help guide future research. The target audience for the workshop includes people who are interested in using machines to solve problems by having a human be an integral part of the learning process.

We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. While original contributions are preferred, we also invite submissions of high-quality work that has recently been published in other venues or is concurrently submitted. We encourage creative ML approaches, as well as interdisciplinarity and perspectives from outside traditional ML. Papers should be 4-8 pages in length (excluding references) formatted using the NeurIPS template. All the submissions should be anonymous. The accepted papers are allowed to get submitted to other conference venues.

Papers can be submitted through CMT:

https://cmt3.research.microsoft.com/NeurIPSHILL2022  

Contact chairs: 

hill_neurips22@googlegroups.com

​Submission deadline: Sep  29, 2022

Acceptance notification: Oct 14, 2022

Workshop data: Dec 2, 2022

We will select best paper this year.

High-quality papers of NeurIPS 2022 Workshop on Human in the Loop Learning will be recommended to publish with Machine Intelligence Research (EI and ESCI indexed journal).

Speakers of HILL Workshop @ NeurIPS 2022

Machine Intelligence Research（简称MIR，原刊名International Journal of Automation and Computing）由中国科学院自动化研究所主办，于2022年正式出版。MIR立足国内、面向全球，着眼于服务国家战略需求，刊发机器智能领域最新原创研究性论文、综述、评论等，全面报道国际机器智能领域的基础理论和前沿创新研究成果，促进国际学术交流与学科发展，服务国家人工智能科技进步。期刊入选"中国科技期刊卓越行动计划"，已被ESCI、EI、Scopus、中国科技核心期刊、CSCD等数据库收录。