In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...