The Experts below are selected from a list of 74313 Experts worldwide ranked by ideXlab platform
Yefei Chen - One of the best experts on this subject based on the ideXlab platform.
-
domain adaptation via Identical Distribution across models and tasks
International Conference on Neural Information Processing, 2018Co-Authors: Xuhong Wei, Yefei ChenAbstract:Deep convolution neural network (CNN) models with millions of parameters trained in large-scale datasets make domain adaptation difficult to be realized. In order to be applied for different application scenarios, various light weight network models have been proposed. These models perform well in large-scale datasets but are hard to train from randomly initialized weights when lack of data. Our framework is proposed to connect a pre-trained deep model with a light weight model by enforcing feature Distributions of the two models being Identical. It is proved in our work that knowledge in source model can be transferred to target light weight model by Identical Distribution loss. Meanwhile, Distribution loss allows training dataset to utilize sparse labeled data in semi-supervised classification task. Moreover, Distribution loss can be applied to large amount of unlabeled data from target domain. In the experiments, several standard benchmarks on domain adaptation are evaluated and our work gets state-of-the-art performance.
Hengguang Zhao - One of the best experts on this subject based on the ideXlab platform.
-
CASE REPORT Autoerythrocyte Sensitization Syndrome Presenting with General Neurodermatitis: Factitious Purpura
2015Co-Authors: Or Psychophysiological Entity, Hengguang Zhao, Fuling LuoAbstract:The Author(s) 2012. This article is published with open access at Springerlink.com Autoerythrocyte sensitization syndrome (AES) is a disorder characterized by recurrent, spontaneous, painful bruising in patients with underlying psychosis and neurosis. Its pathogenesis is uncertain. Purpuric lesions reproduced by injections of washed autologous erythrocytes suggest an autoimmune etiology. The authors described a 50-year-old woman who presented with recurrent episodes of painful bruising for 8 months, along with a 2-year history of general chronic neurodermatitis. A diagnosis of AES was made on the basis of the clinical symptoms and laboratory examinations results: the positive autoerythrocyte sensitization test and psychophysiologic derangement. However, the noticeable symptoms, simultaneously Identical Distribution of the ecchymosis and neurodermatitis lesions, as well as concomitant symptom of itching over the ecchymosis, created doubts regarding the real etiopathogenesis of the ecchymosis and whether the ecchymosis in the present patient were just factitious purpura. The authors discuss the rarity of this case, which to the authors’ knowledge, had not been previously reported in the literature
-
autoerythrocyte sensitization syndrome presenting with general neurodermatitis factitious purpura or psychophysiological entity
Dermatologic Therapy, 2012Co-Authors: Hengguang Zhao, Fuling LuoAbstract:Autoerythrocyte sensitization syndrome (AES) is a disorder characterized by recurrent, spontaneous, painful bruising in patients with underlying psychosis and neurosis. Its pathogenesis is uncertain. Purpuric lesions reproduced by injections of washed autologous erythrocytes suggest an autoimmune etiology. The authors described a 50-year-old woman who presented with recurrent episodes of painful bruising for 8 months, along with a 2-year history of general chronic neurodermatitis. A diagnosis of AES was made on the basis of the clinical symptoms and laboratory examinations results: the positive autoerythrocyte sensitization test and psychophysiologic derangement. However, the noticeable symptoms, simultaneously Identical Distribution of the ecchymosis and neurodermatitis lesions, as well as concomitant symptom of itching over the ecchymosis, created doubts regarding the real etiopathogenesis of the ecchymosis and whether the ecchymosis in the present patient were just factitious purpura. The authors discuss the rarity of this case, which to the authors’ knowledge, had not been previously reported in the literature.
Xuhong Wei - One of the best experts on this subject based on the ideXlab platform.
-
domain adaptation via Identical Distribution across models and tasks
International Conference on Neural Information Processing, 2018Co-Authors: Xuhong Wei, Yefei ChenAbstract:Deep convolution neural network (CNN) models with millions of parameters trained in large-scale datasets make domain adaptation difficult to be realized. In order to be applied for different application scenarios, various light weight network models have been proposed. These models perform well in large-scale datasets but are hard to train from randomly initialized weights when lack of data. Our framework is proposed to connect a pre-trained deep model with a light weight model by enforcing feature Distributions of the two models being Identical. It is proved in our work that knowledge in source model can be transferred to target light weight model by Identical Distribution loss. Meanwhile, Distribution loss allows training dataset to utilize sparse labeled data in semi-supervised classification task. Moreover, Distribution loss can be applied to large amount of unlabeled data from target domain. In the experiments, several standard benchmarks on domain adaptation are evaluated and our work gets state-of-the-art performance.
Monte S. Buchsbaum - One of the best experts on this subject based on the ideXlab platform.
-
Diametrical relationship between gray and white matter volumes in autism spectrum disorder and schizophrenia
Brain Imaging and Behavior, 2017Co-Authors: Serge A. Mitelman, Marie-cecile Bralet, M. Mehmet Haznedar, Eric Hollander, Lina Shihabuddin, Erin A. Hazlett, Monte S. BuchsbaumAbstract:Autism spectrum disorders and schizophrenia have been variously characterized as separate nosological entities with overlapping deficits in social cognition or diametrical extremes of a phenotypic continuum. This study aimed to determine how these models apply to comparative morphometric data. MRI scans of the brain were obtained in 49 subjects with schizophrenia, 20 subjects with autism and 39 healthy controls. Images were parcellated into 40 Brodmann areas and entered into repeated-measures ANOVA for between-group comparison of global and localized gray and white matter volumes. A pattern of lower gray mater volumes and greater white matter volumes was found in subjects with schizophrenia in comparison to subjects with autism. For both gray and white matter, this pattern was most pronounced in regions associated with motor-premotor and anterior frontal cortex, anterior cingulate, fusiform, superior and middle temporal gyri. Patient groups tended to diverge from healthy controls in opposite directions, with greater-than-normal gray matter volumes and lower-than-normal white matter volumes in subjects with autism and reversed patterns in subjects with schizophrenia. White matter reductions in subjects with autism were seen in posterior frontal lobe and along the cingulate arch. Normal hemispheric asymmetry in the temporal lobe was effaced in subjects with autism and schizophrenia, especially in the latter. Nearly Identical Distribution of changes and diametrically divergent volumetry suggest that autism and schizophrenia may occupy opposite extremes of the same cognitive continuum.
Abdulmotaleb El Saddik - One of the best experts on this subject based on the ideXlab platform.
-
modeling and stability analysis of automatic generation control over cognitive radio networks in smart grids
Systems Man and Cybernetics, 2015Co-Authors: Shichao Liu, Peter X Liu, Abdulmotaleb El SaddikAbstract:Due to its great potential to improve the overall performance of data transmission with its dynamic and adaptive spectrum allocation capability in comparison with many other networking technologies, cognitive radio (CR) networking technology has been increasingly employed in networking and communication infrastructures for smart grids. However, a secondary user (SU) of a CR network has to be squeezed out from a channel when a primary user reclaims the channel, which may occur in a randomized fashion. The random interruption of SU traffic may cause packet losses and delays for SU data, and it will in turn affect the stability of the monitoring and control of smart grids. In this paper, we address this problem and investigate the modeling and stability analysis of the automatic generation control (AGC) of a smart grid for which CR networks are used as the infrastructure for the aggregation and communication of both system-wide information and local measurement data. For this purpose, a randomly switched power system model is proposed for the AGC of the smart grid. By modeling the CR network as an On–Off switch with sojourn times, the stability of the AGC of the smart grid is analyzed. In particular, we investigate the smart grid with two main types of CR networks: 1) the sojourn times are arbitrary but bounded and 2) the sojourn times follow an independent and Identical Distribution process. The sufficient conditions are obtained for the stability of the AGC of the smart grid with these two CR networks, respectively. Simulation results show the effects of the CR networks on the dynamic performance of the AGC of the smart grid and illustrate the usefulness of the developed sufficient conditions in the design of CR networks in order to ensure the stability of the AGC of the smart grid.
