Call for papers

Please download the CFP flyer here (Click).

All papers submitted to the conference will undergo rigorous and unbiased peer review process conducted by experts of the research area that the work of authors focuses. We invite submissions on theoretical and applicable research falls within the conference scope. The topics of interest include, but are not limited to:

Approximate inference

Bayesian learning

Business process intelligence

Causal models



Density estimation

Federated learning

Gaussian processes

Generalization and regularization

Graphical models

High-performance computation

Intelligent optimization

Kernel and spectral methods

Large-scale optimization algorithm

Logic and probability

Manifolds learning

Multi-agent systems

Non-Bayesian models and estimation

Nonparametric models

No-regret learning

Optimization for deep learning

Privacy-preserving learning

Reinforcement learning

Software and applications of artificial intelligence

Sparsity and compressed sensing

Statistical and computational learning theory

Statistical optimization

Structural learning and prediction

Unsupervised and semi-supervised learning