Aug. 5, 2022, 1:11 a.m. | Tomer Meir, Rom Gutman, Malka Gorfine

stat.ML updates on arXiv.org arxiv.org

Time-to-event analysis (survival analysis) is used when the outcome or the
response of interest is the time until a pre-specified event occurs.
Time-to-event data are sometimes discrete either because time itself is
discrete or due to grouping of failure times into intervals or rounding off
measurements. In addition, the failure of an individual could be one of several
distinct failure types; known as competing risks (events). This work focuses on
discrete-time regression with competing events. We emphasize the main
difference …

arxiv ml package python regression risks survival time

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Principal Engineer, Deep Learning

@ Outrider | Remote

Data Analyst (Bangkok based, relocation provided)

@ Agoda | Bangkok (Central World Office)

Data Scientist II

@ MoEngage | Bengaluru

Machine Learning Engineer

@ Sika AG | Welwyn Garden City, United Kingdom