Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the ...
Alex J. Smola, Robert C. Williamson, Sebastian Mik...
In this paper, we study the dynamical properties of the population based incremental learning (PBIL) algorithm when it uses truncation, proportional, and Boltzmann selection schema...
We consider a bandit problem which involves sequential sampling from two populations (arms). Each arm produces a noisy reward realization which depends on an observable random cov...
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
Undoubtedly, a key feature in the popularity of smartmobile devices is the numerous applications one can install. Frequently, we learn about an application we desire by seeing it ...