Beta distribution is ubiquitous in statistics, but particularly popular in real-world modeling. The beta-binomial model is perhaps the most known example, given the recent interest in Bayesian inference. But it was in use nearly 50 years ago, for example in toxicology. Unfortunately, computing probabilities from the density depends on intractable incomplete beta integrals. This creates …
Archiwum autora:mskorski
Improving State-of-Art on Sparse Random Projections
Random projections are widely used to reduce data dimension in various analyses. Provable guarantees were developed first in the important result of Johnson and Lindenstrauss on Lipschitz maps, but more recently there has been a lot of follow-up work in the context of machine-learning. Particularly attractive are sparse random projections, which share similar guarantees as …
Czytaj dalej Improving State-of-Art on Sparse Random Projections
Performance drawbacks of Tensorflow Datasets
Tensorflow, the popular framework for machine-learning, recommends its new dataset API for preprocessing and serving data. It supports useful tricks, such as caching data in memory, prefetching in parallel threads and others described in tutorials. Still, Tensorflow has issues with slow data slicing, so the dataset API may actually do harm in setups where computations …