A theory of transfer learning with applications to active learning
Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure
Forecasting electricity consumption by aggregating specialized experts
Quantum speed-up for unsupervised learning
Online Multiple Kernel Classification
Efficiently learning the preferences of people
Density estimation with minimization of U-divergence
New algorithms for budgeted learning
Learning figures with the Hausdorff metric by fractals—towards computable binary classification
Mass estimation
On evaluating stream learning algorithms
Multiclass classification with bandit feedback using adaptive regularization
TEXPLORE: real-time sample-efficient reinforcement learning for robots
Computational complexity of kernel-based density-ratio estimation: a condition number analysis