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Jiaqian Yu, Matthew B Blaschko
Learning with non-modular losses is an important problem when sets of predictions are made simultaneously. The main tools for constructing convex surrogate loss functions for set prediction are margin rescaling and slack rescaling. In this work, we show that these strategies lead to tight convex surrogates iff the underlying loss function is increasing in the number of incorrect predictions. However, gradient or cutting-plane computation for these functions is NP-hard for non-supermodular loss functions. We propose instead a novel surrogate loss function for submodular losses, the Lovász hinge, which leads to O(p log p) complexity with O(p) oracle accesses to the loss function to compute a gradient or cutting-plane...
November 23, 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Leiquan Wang, Xiaoliang Chu, Weishan Zhang, Yiwei Wei, Weichen Sun, Chunlei Wu
Image captioning with a natural language has been an emerging trend. However, the social image, associated with a set of user-contributed tags, has been rarely investigated for a similar task. The user-contributed tags, which could reflect the user attention, have been neglected in conventional image captioning. Most existing image captioning models cannot be applied directly to social image captioning. In this work, a dual attention model is proposed for social image captioning by combining the visual attention and user attention simultaneously...
February 22, 2018: Sensors
Brian H May, Mei Feng, Iris W Zhou, Su-Yueh Chang, Shao-Chen Lu, Anthony L Zhang, Xin-Feng Guo, Chuan-Jian Lu, Charlie C L Xue
OBJECTIVES: To identify and analyze records of the treatment of dementia and memory disorders in the classical Chinese medical literature that were consistent with the signs and symptoms of Alzheimer's disease (AD), with the aim of determining which traditional medicines have histories of use for these disorders. METHODS: Encyclopedia of Traditional Chinese Medicine (Zhong Hua Yi Dian), a database of more than 1000 classical and premodern Chinese medical books, was systematically searched...
September 2016: Journal of Alternative and Complementary Medicine: Research on Paradigm, Practice, and Policy
Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. In this paper, we present a generative model based on a deep recurrent architecture that combines recent advances in computer vision and machine translation and that can be used to generate natural sentences describing an image. The model is trained to maximize the likelihood of the target description sentence given the training image. Experiments on several datasets show the accuracy of the model and the fluency of the language it learns solely from image descriptions...
July 7, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
Yuntao Dai, Zhenyu Li, Liming Xue, Chunyan Dou, Yuzhi Zhou, Lizeng Zhang, Xuemei Qin
ETHNOPHARMACOLOGY: Xiaoyaosan, a famous Chinese prescription, composed of Poria (Poria cocos (Schw.) Wolf), Radix Paeoniae Alba (Paeonia lactiflora Pall.), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Rhizoma Atractylodis Macrocephalae (Atractylodes macrocephala Koidz.), Herba Menthae (Mentha haplocalyx Briq.), and Rhizoma Zingiberis Recens (Zingiber officinale Rosc.), has been widely used in the clinic for treating mental disorders...
March 24, 2010: Journal of Ethnopharmacology
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