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FILM 2016 : Future of Interactive Learning Machines Workshop @ NIPS 2016

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Link: http://www.filmnips.com/
 
When Dec 5, 2016 - Dec 10, 2016
Where Barcelona, Spain
Submission Deadline Oct 14, 2016
Categories    artificial intelligence   machine learning   robotics   HCI
 

Call For Papers

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NIPS 2016 Workshop: Future of Interactive Learning Machines
Barcelona, Spain
http://www.filmnips.com/
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Important Dates
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Paper submission deadline: *Oct 14th 2016*
Notification of acceptance: Oct 29th 2016
Camera-ready submission deadline: Nov 11th 2016
FILM workshop at NIPS 2016 in Barcelona, Spain: Dec 9th or 10th 2016

Overview
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Interactive machine learning (IML) explores how intelligent agents solve a task together, often focusing on adaptable collaboration over the course of sequential decision making tasks. Past research in the field of IML has investigated how autonomous agents can learn to solve problems more effectively by making use of interactions with humans. Designing and engineering fully autonomous agents is a difficult and sometimes intractable challenge. As such, there is a compelling need for IML algorithms that enable artificial and human agents to collaborate and solve independent or shared goals. The range of real-world examples of IML spans from web applications such as search engines, recommendation systems and social media personalization, to dialog systems and embodied systems such as industrial robots and household robotic assistants, and to medical robotics (e.g. bionic limbs, assistive devices, and exoskeletons). As intelligent systems become more common in industry and in everyday life, the need for these systems to interact with and learn from the people around them will also increase.

This workshop seeks to brings together experts in the fields of IML, reinforcement learning (RL), human-computer interaction (HCI), robotics, cognitive psychology and the social sciences to share recent advances and explore the future of IML. Some questions of particular interest for this workshop include: How can recent advancements in machine learning allow interactive learning to be deployed in current real world applications? How do we address the challenging problem of seamless communication between autonomous agents and humans? How can we improve the ability to collaborate safely and successfully across a diverse user set?

We hope that this workshop will produce several outcomes:

- A review of current algorithms and techniques for IML, and a focused perspective on what is lacking
- A formalization of the main challenges for deploying modern interactive learning algorithms in the real world
- A forum for interdisciplinary researchers to discuss open problems and challenges, present new ideas on IML and plan for future collaborations

Relevant Topics
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- Human-robot interaction
- Collaborative and/or shared control
- Semi-supervised learning with human intervention
- Learning from demonstration, interaction and/or observation
- Reinforcement learning with human-in-the-loop
- Active learning, Preference learning
- Transfer learning (human-to-machine, machine-to-machine)
- Natural language processing for dialog systems
- Computer vision for human interaction with autonomous systems
- Transparency and feedback in machine learning
- Computational models of human teaching
- Intelligent personal assistants and dialog systems
- Adaptive user interfaces
- Brain-computer interfaces (e.g. human-semi-autonomous system interfaces)
- Intelligent medical robots (e.g. smart wheelchairs, prosthetics, exoskeletons)

We seek broad participation from researchers in the fields of artificial intelligence, machine learning, human-computer interaction, cognitive science, robotics, intelligent interface design, adaptive systems and related fields.

Submission Details
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We encourage submissions covering new ideas in interactive learning, reports on research in progress as well as discussions of open problems and challenges facing interactive machine learning. We are particularly interested in research regarding the practical application of interactive learning systems (for robotics, virtual agents, online education, dialog systems, health care, security, transportation, etc.), and the ability of these systems to handle the complexity of real world problems. We also encourage submissions bringing perspectives from the fields of psychology and social science, and from human computer interaction.

Authors are invited to submit long papers (8 pages for main text and 1 page for references) or short papers (2 to 4 pages for main text and 1 page for references) on research relevant to the theme of the workshop. The papers should be formatted according to NIPS formatting guidelines and submitted as a PDF document. All submissions are handled electronically through EasyChair (https://easychair.org/conferences/?conf=filmnips2016).

Papers will be subject to a single-blind peer review, i.e. authors can keep their names and affiliations on their submitted papers. Papers will be evaluated based on originality, technical soundness, clarity and potential impact on the field of interactive machine learning. Accepted papers will be made publicly available on the workshop website. Accepted papers will be presented as talks and/or posters at the workshop.

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Contact: If you have any questions, comments or concerns, please contact the organizers at film.nips2016@gmail.com.

Looking forward to seeing you in Barcelona!

- FILM Organizers

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