We show that anomaly detection can be interpreted as a binary classification problem. Using this interpretation we propose a support vector machine (SVM) for anomaly detection. We...
This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage learning and directed exploration can...
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Abstract. Feature selection researchers often encounter a peaking phenomenon: a feature subset can be found that is smaller but still enables building a more accurate classifier th...
Compilability is a fundamental property of knowledge representation formalisms which captures how succinctly information can be expressed. Although many results concerning compila...