Timezone: »

Multi-level Inference Workshop and Model Selection Game
Isabelle Guyon

Sat Dec 09 12:00 AM -- 12:00 AM (PST) @ Callaghan
Event URL: http://clopinet.com/isabelle/Projects/NIPS2006/ »

When training a learning machine, both practical and theoretical considerations may yield to split the problem into multiple levels of inference. Typically, at the lower level, the parameters of individual models are optimized and at the second level the best model is selected, e.g. via cross-validation. But, there may be more than two levels of inference and cross-validation is not the only way of addressing the resulting optimization problem. This workshop will revisit the problem of model selection, with the goal of bridging the gap between theory and practice. A * game of model selection is organized *, check the web-site!

Author Information

Isabelle Guyon (Google and ChaLearn)

Isabelle Guyon recently joined Google Brain as a research scientist. She is also professor of artificial intelligence at Université Paris-Saclay (Orsay). Her areas of expertise include computer vision, bioinformatics, and power systems. She is best known for being a co-inventor of Support Vector Machines. Her recent interests are in automated machine learning, meta-learning, and data-centric AI. She has been a strong promoter of challenges and benchmarks, and is president of ChaLearn, a non-profit dedicated to organizing machine learning challenges. She is community lead of Codalab competitions, a challenge platform used both in academia and industry. She co-organized the “Challenges in Machine Learning Workshop” @ NeurIPS between 2014 and 2019, launched the "NeurIPS challenge track" in 2017 while she was general chair, and pushed the creation of the "NeurIPS datasets and benchmark track" in 2021, as a NeurIPS board member.

More from the Same Authors