posted by user: gonzo1453 || 1323 views || tracked by 6 users: [display]

CHIL 2020 : ACM Conference on Health, Inference, and Learning

FacebookTwitterLinkedInGoogle

Link: https://www.chilconference.org/
 
When Apr 2, 2020 - Apr 4, 2020
Where Toronto, Canada
Submission Deadline Jan 13, 2020
Notification Due Feb 17, 2020
Final Version Due Mar 6, 2020
Categories    bayesian learning   causal inference   explainability   inference
 

Call For Papers

There are 4 tracks:

Track 1: Machine Learning
Track 2 Applications: Investigation, Evaluation, and Interpretation
Track 3 Policy: Impact, Economics, and Society
Track 4: Practice

Advances in machine learning are critical for a better understanding of health. Track 1 Machine Learning seeks contributions in modeling, inference, and estimation in health-focused or health-inspired settings. We welcome submissions that develop novel methods and algorithms, introduce relevant machine learning tasks, or identify challenges with prevalent approaches. Submissions focused more on health applications, for example establishing baselines or suggesting new evaluation metrics for assessing algorithmic advances are encouraged to submit to Track 2 instead.

While submissions should address problems relevant to health, the contributions themselves are not required to be directly applied to health. For example, authors may use synthetic datasets and experiments to demonstrate the properties of algorithms.

Authors may consider one or more machine learning sub-discipline(s) from the following list: .

Bayesian learning
Causal inference
Computer vision
Deep learning architectures
Evaluation methods
Inference
Knowledge graphs
Natural language processing
Reinforcement Learning
Representation learning
Robust learning
Structured learning
Supervised learning
Survival analysis
Time series
Transfer learning
Unsupervised learning
Explainability
Algorithmic Fairness

Authors may also consider sub-disciplines not listed here.

The goal of Track 2 Applications is to highlight works applying robust methods, models, or practices to identify, characterize, audit, evaluate, or benchmark systems. Whereas the goal of Track 1 is to select papers that show significant technical novelty, submit your work here if the contribution is more focused on solving a carefully motivated problem grounded in applications.

Related Resources

XKDD 2020   2nd International Workshop on eXplainable Knowledge Discovery in Data Mining
ACM--NLPIR--Ei Compendex and Scopus 2020   ACM--2020 4th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2020)--Scopus, Ei Compendex
ICGI 2020   The 15th International Conference on Grammatical Inference
ICSIE--ACM, Ei Compendex, Scopus 2020   2020 9th International Conference on Software and Information Engineering (ICSIE 2020)--ACM, Ei Compendex, Scopus
3rd ICTEL 2021   International Conference on Teaching, Education & Learning, 23-24 March, Singapore
AICA 2020   O'Reilly AI Conference San Jose
ACM--ICCCR--Ei Compendex, Scopus 2021   ACM--2021 International Conference on Computer, Control and Robotics (ICCCR 2021)--Ei Compendex, Scopus
6th ICTEL May, Berlin 2021   6th ICTEL 2021 – International Conference on Teaching, Education & Learning, 11-12 May, Berlin
ICCCR--IEEE, Ei, Scopus 2020   IEEE--2021 International Conference on Computer, Control and Robotics (ICCCR 2021)--Ei Compendex, Scopus
Fintech 2020   Sustainaility (Q2): Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions