International Conference on Frontiers of Artificial Intelligence and Statistics (CFAIS)

The International Conference on Frontiers of Artificial Intelligence and Statistics (CFAIS) covers topics such as:

• Algorithms and architectures for high-performance computation in AI and statistics
• Solicited topics include, but are not limited to:
• Bayesian models and estimation (graphical models, causality, Gaussian processes, approximate inference...)
• Algorithms and architectures for high-performance computation in AI and statistics
• Classification, regression, density estimation, unsupervised and semi-supervised learning, clustering, topic models..
• Classification, regression, density estimation, unsupervised and semi-supervised learning, clustering, topic models..
• Game theory, no-regret learning, multi-agent systems
• Deep learning including optimization, generalization and architectures
• Models and estimation: graphical models, causality, Gaussian processes, approximate inference, kernel methods, nonparametric models, statistical and computational learning theory, manifolds and embedding, sparsity and compressed sensing..
• Game theory, no-regret learning, multi-agent systems
• Reinforcement learning, planning, control
• Non-Bayesian models and estimation (kernel methods, nonparametric models, statistical and computational learning theory, manifolds and embedding, sparsity and compressed sensing...)
• Software for and applications of AI and statistics
• Reinforcement learning, planning, control
• Structured prediction, relational learning, logic and probability
• Software for and applications of AI and statistics
• Trustworthy learning, including learning with privacy and fairness, interpretability, and robustness
• Structured prediction, relational learning, logic and probability