We invite submissions on a wide range of research topics, spanning both theoretical and systems research. The topics of interest include, but are not limited to:
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Algorithms and architectures for high-performance computation | Manifolds and embedding |
Approximate inference | Multi-agent systems |
Bayesian models and estimation | No-regret learning |
Business Process Intelligence | Non-Bayesian models and estimation |
Causality | Nonparametric models |
Classification | Regression |
Clustering | Reinforcement learning, planning, control |
Deep learning including optimization | Relational learning |
Density estimation | Software for and applications of AI and statistics |
Game theory | Solicited topics |
Gaussian processes | Sparsity and compressed sensing |
Generalization and architectures | Statistical and computational learning theory |
Graphical models | Structured prediction |
Including learning with privacy and fairness | Topic models |
Interpretability and robustness | Trustworthy learning |
Kernel methods | Unsupervised and semi-supervised learning |
Logic and probability |