Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive p...
Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive p...
- Net4Voice project consists in testing voice recognition techniques and methods within learning contexts. The need to support learning process with non traditional technologies de...
Hardware implementations of cryptographic algorithms are still vulnerable to side-channel attacks. Side-channel attacks that are based on multiple measurements of the same operatio...