Parameterized heuristics abound in computer aided design and verification, and manual tuning of the respective parameters is difficult and time-consuming. Very recent results from ...
Frank Hutter, Domagoj Babic, Holger H. Hoos, Alan ...
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Abstract—Service requests are the origin of every service provisioning process and therefore the entities to be considered first. Similar to Physics and Engineering Sciences, ser...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...