An Algorithmic Framework for Computing Validation Performance Bounds by Using Suboptimal Models

Practical model building processes are often time-consuming because many different models must be trained and validated. In this paper, we introduce a novel algorithm that can be used for computing the lower and the upper bounds of model validation errors without actually training the model itself. A key idea behind our algorithm is using a side information available from a suboptimal model. If a reasonably good suboptimal model is available, our algorithm can compute lower and upper bounds of many useful quantities for making inferences on the unknown target model. We demonstrate the advantage of our algorithm in the context of model selection for regularized learning problems

Electrospinning and Post-Spun Chain Conformations of Synthetic, Hydrophobic Poly(α-amino acid)s.

Electrospinning and post-spun conformations of hydrophobic poly(α-amino acid)s are described in this study. The poly(α-amino acid)s, poly(Gly), poly(L-Ala), poly(L-Val), and poly(L-Leu) were synthesized via corresponding N-carboxy-a-amino acid anhydrides. The average molecular weight and degree of polymerization of these polymers were determined by N-terminus labeling using 2,4-dinitrofluorobenzene and by viscometry in the case of poly(Gly). These poly(α-amino acid)s were electrospun from trifluoroacetic acid or trifluoroacetic acid/dichloromethane solutions. The FT-IR spectroscopy and wide-angle X-ray diffraction indicated that the electrospun poly(L-Ala) and poly(L-Leu) fibers predominantly adopts α-helical structure, whereas poly(L-Val) and poly(Gly) fibers exhibited mainly β-strand and random coil structures, respectively

Neural responses to feedback information produced by self-generated or other-generated decision-making and their impairment in schizophrenia

Several studies of self-monitoring dysfunction in schizophrenia have focused on the sense of agency to motor action using behavioral and psychophysiological techniques. So far, no study has ever tried to investigate whether the sense of agency or causal attribution for external events produced by self-generated decision-making is abnormal in schizophrenia. The purpose of this study was to investigate neural responses to feedback information produced by self-generated or other-generated decision-making in a multiplayer gambling task using even-related potentials and electroencephalogram synchronization. We found that the late positive component and theta/alpha synchronization were increased in response to feedback information in the self-decision condition in normal controls, but that these responses were significantly decreased in patients with schizophrenia. These neural activities thus reflect the self-reference effect that affects the cognitive appraisal of external events following decision-making and their impairment in schizophrenia