Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
The Quantified Constraint Satisfaction Problem (QCSP) has been introduced to express situations in which we are not able to control the value of some of the variables (the universa...
Can we leverage learning techniques to build a fast nearest-neighbor (ANN) retrieval data structure? We present a general learning framework for the NN problem in which sample que...
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...