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AFair-AMLD 2023 : Workshop on Algorithmic Fairness in Artificial intelligence, Machine learning and Decision making (In conjuction with SIAM Data Mining - SDM23)

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Link: https://algfair-siam23.netlify.app
 
When Apr 27, 2023 - Apr 27, 2023
Where Graduate Minneapolis Hotel, Minneapolis,
Submission Deadline Feb 15, 2023
Notification Due Mar 1, 2023
Final Version Due Mar 20, 2023
Categories    computer science   machine learning   artificial intelligence   decision making
 

Call For Papers

Algorithmic Fairness in Artificial intelligence, Machine learning and Decision making (AFair-AMLD23) will be held in conjuction with SIAM Data Mining International Conference (SIAM23).

Venue: Graduate Minneapolis Hotel, Minneapolis, Minnesota, USA
Important dates:
Paper submission deadline: 15.02.2023
Decision notification: 01.03.2023
Camera ready paper due: 20.03.2023
Application for travel awards 26.01.2023
Workshop date: 27.04.2023


Important note: if you plan to apply for travel award, paper has to be submited by 25.01.2023.
Application for travel award may be submitted here: https://www.siam.org/conferences/cm/lodging-and-support/travel-support/sdm23-conference-support

Workshop scope:

The workshop addresses the problems of development and application of fair algorithms in areas of Artificial intelligence (AI), Machine learning (ML) and Decision making (DM).
We welcome submissions of novel work in the area of fairness with a special interest on (but not limited to):

Fair classification, regression and clustering algorithms
Envy free classification, regression and clustering algorithms
Pre-processing, in-processing, post-processing techniques in fair AI/ML/DM
Fair ranking algorithms
Fairness in recommendations and recommender systems
Fair classification and regression on graphs
Fair deep learning algorithms
Novel measures of group and individual fairness
Fairness and causal inference
Novel mathematical formulations of fairness concepts
Trade-offs between fairness metrics
Trade-offs between algorithmic performance and fairness metrics.
Fair embeddings
Fair data imputation
Fair algorithm applications
Fairness-sensitive algorithms in practice
Benchmark datasets for AI/ML/DM
Applications and case studies of fair AI/ML/DM models in different domains (marketing, healthcare, law, banking etc.)

Submission guidelines:
Paper length: 5-9 pages including abstract, bibliography and appendices. Papers must have an abstract with a maximum of 300 words and a keyword list with no more than six keywords.
Review: Double blind.
Format: Papers should be submitted in pdf format. Papers must be prepared in LaTeX2e, and formatted using SIAM’s double column template. Latex template is available here. Submission: All papers should be submitted through EasyChair submission system.
Dual-submission policy: we accept submissions of ongoing unpublished work as well as work submitted elsewhere (FAccT, ICLR, SaTML, etc), or substantial extensions of works presented at other venues (not in proceedings). We however do not accept work that has been previously accepted as a journal or conference proceedings (including the main SDM conference).

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