A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
In contrast to traditional terascale simulations that have known, fixed data inputs, dynamic data-driven (DDD) applications are characterized by unknown data and informed by dynam...
Volkan Akcelik, George Biros, Andrei Draganescu, J...
This paper presents a very low bit-rate F0 coding technique for speaker-dependent phonetic vocoder based on hidden Markov model (HMM) using quantized F0 context. In the proposed t...
Demand forecast plays a critical role to determine capital investment for capacity planning. Given the involved uncertainties and long lead-time for capacity expansion, semiconduc...
— Cultured natural cortical neurons form functional networks through a complex set of developmental steps during the first weeks in vitro. The dynamic behavior of the network in...
Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...