all AI news
On the Role of Channel Capacity in Learning Gaussian Mixture Models. (arXiv:2202.07707v2 [cs.IT] UPDATED)
June 15, 2022, 1:11 a.m. | Elad Romanov, Tamir Bendory, Or Ordentlich
cs.LG updates on arXiv.org arxiv.org
This paper studies the sample complexity of learning the $k$ unknown centers
of a balanced Gaussian mixture model (GMM) in $\mathbb{R}^d$ with spherical
covariance matrix $\sigma^2\mathbf{I}$. In particular, we are interested in the
following question: what is the maximal noise level $\sigma^2$, for which the
sample complexity is essentially the same as when estimating the centers from
labeled measurements? To that end, we restrict attention to a Bayesian
formulation of the problem, where the centers are uniformly distributed on the …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Data Analyst
@ Aviva | UK - Norwich - Carrara - 1st Floor
Werkstudent im Bereich Performance Engineering mit Computer Vision (w/m/div.) - anteilig remote
@ Bosch Group | Stuttgart, Lollar, Germany
Applied Research Scientist - NLP (Senior)
@ Snorkel AI | Hybrid / San Francisco, CA
Associate Principal Engineer, Machine Learning
@ Nagarro | Remote, India