We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Obtaining an accurate multiple alignment of protein sequences is a difficult computational problem for which many heuristic techniques sacrifice optimality to achieve reasonable r...
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...