This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the not...
As ever-larger training sets for learning to rank are created, scalability of learning has become increasingly important to achieving continuing improvements in ranking accuracy [...
This paper presents a community of communicating embodied agents which learn an adjacency-based grammar from user interactions. The agents act as intelligent fridge magnets, each ...