neurips-hill.github.io

NeurIPS 2022 Workshop on Human in the Loop Learning

For in-person audiences, please join us in Room 396. The workshop schedule can be found here.

For online audiences, please click here to join the workshop. You can get the zoom link after registration.

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.

Call for Papers

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:

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, checklist and appendix) 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

Important Dates

Speakers of HILL Workshop @ NeurIPS 2022

We invite representative researchers from the related areas to give featured talks. We are honored to have the following speakers:


Alison Gopnik, Professor at
University of California, Berkeley

Peter Stone, Professor at
University of Texas at Austin

Dan Bohus, Senior Principal Researcher at
Microsoft Research

Samuel Kaski, Professor at
University of Manchester and Aalto University

Ding Zhao, Assistant Professor at
CMU

Danica Kragic, Professor at
Royal Institute of Technology, KTH

Cynthia Rudin, Professor at
Duke University

Jens Kober, Associate Professor at
Delft University of Technology

Dorsa Sadigh, Assistant Professor at
Stanford University

Brenna Argall, Associate Professor at
Northwestern University

Igor Mordatch at
Google Brain

Co-chairs


Shanghang Zhang, Assistant Professor at
Peking University

Hao Dong, Assistant Professor at
Peking University

Fisher Yu, Assistant Professor
at ETH Zurich

Pradeep Ravikumar,
Professor at CMU

Xin Wang, Senior Researcher
at Microsoft Research

Wei Pan, Assistant Professor
at University of Manchester

Vittorio Ferrari
Principal Scientist at Google
Honorary Professor at
University of Edinburgh

Zihan Ding
PhD at
Princeton University

Co-sponsor: Machine Intelligence Research

Machine Intelligence Research (original title: International Journal of Automation and Computing), published by Springer, and sponsored by Institute of Automation, Chinese Academy of Sciences, is formally released in 2022. The journal publishes high-quality papers on original theoretical and experimental research, targets special issues on emerging topics and specific subjects, and strives to bridge the gap between theoretical research and practical applications. The journal has been indexed by ESCI, EI, Scopus, CSCD, etc.