Call for Posters

Registration is free, but spaces are limited.

When registering, participants can also choose to present a poster and/or give a short talk.

Topics of interest include (but are not limited to):

General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, supervised, semi- and self-supervised learning, time series analysis, etc.)
Deep Learning (architectures, generative models, deep reinforcement learning, etc.)
Learning Theory (bandits, game theory, statistical learning theory, etc.)
Optimization (convex and non-convex optimization, matrix/tensor methods, stochastic, online, non-smooth, composite, etc.)
Probabilistic Inference (Bayesian methods, graphical models, Monte Carlo methods, etc.)
Trustworthy Machine Learning (accountability, causality, fairness, privacy, robustness, etc.)
Applications (computational biology, crowdsourcing, healthcare, neuroscience, social good, climate science, etc.)

Poster Dimensions

We will reach out to poster presenters via email with guidelines on poster dimensions.

Questions?

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