Architecture Digest
Feb 11, 2018 · Artificial Intelligence
Recent Advances in Bayesian Machine Learning: Foundations, Non‑Parametric Methods, and Large‑Scale Applications
This article reviews recent progress in Bayesian machine learning, covering foundational theory, non‑parametric approaches such as Dirichlet and Indian buffet processes, regularized Bayesian inference, and scalable techniques for big‑data environments including stochastic variational methods, distributed algorithms, and hardware acceleration.
Bayesian learningbig datamachine learning
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