Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...