检索结果-内蒙古大学图书馆

From social to individuals: A parsimonious path of multi-level models for crowdsourced preference aggregation

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Xu, Qianqian Xiong, Jiechao Cao, Xiaochun Huang, Qingming Yao, Yuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing1000190 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Tencent AI Lab Shenzhen518057 BICMR-LMAM-LMEQF-LMP School of Mathematical Sciences Peking University Beijing100871 China University of Chinese Academy of Sciences Institute of Computing Technology of Chinese Academy of Sciences Beijing100190 China Department of Mathematics and by courtesy Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or social utility function which generates their comparison behaviors in experiments. However, in reality annotators are subject to variations due to multi-criteria, abnormal, or a mixture of such behaviors. In this paper, we propose a parsimonious mixed-effects model, which takes into account both the fixed effect that the majority of annotators follows a common linear utility model, and the random effect that some annotators might deviate from the common significantly and exhibit strongly personalized preferences. The key algorithm in this paper establishes a dynamic path from the social utility to individual variations, with different levels of sparsity on personalization. The algorithm is based on the Linearized Bregman Iterations, which leads to easy parallel implementations to meet the need of large-scale data analysis. In this unified framework, three kinds of random utility models are presented, including the basic linear model with L2 loss, Bradley-Terry model, and Thurstone-Mosteller model. The validity of these multi-level models are supported by experiments with both simulated and real-world datasets, which shows that the parsimonious multi-level models exhibit improvements in both interpretability and predictive precision compared with traditional HodgeRank. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

Shape-color differential moment invariants under affine transformations

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Mo, Hanlin Li, Shirui Hao, You Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

We propose the general construction formula of shape-color primitives by using partial differentials of each color channel in this paper. By using all kinds of shape-color primitives, shape-color differential moment invariants can be constructed very easily, which are invariant to the shape affine and color affine transforms. 50 instances of SCDMIs are obtained finally. In experiments, several commonly used color descriptors and SCDMIs are used in image classification and retrieval of color images, respectively. By comparing the experimental results, we find that SCDMIs get better results. Copyright © 2017, The Authors. All rights reserved.

关键词： Color

Isometrically subdivisible tetrahedra

学校读者我要写书评

暂无评论

Computer Aided Drafting,Design and Manufacturing 2017年第2期27卷 24-31页

作者： Li Erbo Li Zhi Li Hua EON Reality Inc Liaoning Center for Disease Prevention and Control Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences University of Chinese Academy of Sciences

It is well known that a triangle can be divided by mid-point refinement into four sub-triangles with the same shape. Similarly, a tetrahedron can be parted into eight subtetrahedra, which are generally not uniform in shape. This paper proves that there exist a set of tetrahedra, which is called isometrically subdivisible tetrahedra(IST) and can be divided into eight isometric subtetrahedra, including identical and reflection ones. And a new classification of tetrahedra is put forward, based on which all tetrahedra can be categorized into 26 classes according to both the number of maximum equal edges and topological relations. The IST belongs only to three of the classes. That result provides a new viewpoint of spatial structure and may be used to tile or subdivide space uniformly or isometrically.

关键词： regular subdivision isometric identical tetrahedra classification tetrahedra direction

Research on high-accuracy gait recognition technique based on parallel genetic algorithm

学校读者我要写书评

暂无评论

Journal of information Hiding and Multimedia Signal processing 2018年第1期9卷 244-255页

作者： Lin, Xiao Jia Zhang, Fu Quan Xu, Lin Department of Computing and Information Technology Fujian Business University No. 19 Huang Pu Road Gulou District Fuzhou350012 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University School of Software Beijing Institute of Technology Room A9. 301 Juyuan Jinshan Jiyuan Fuzhou350008 China Innovative Information Industry Research Institute Fujian Normal University Fuqing Brunch of Fujian Normal University Campus County 1. Longjiang Road Fuqing Fuzhou350300 China

In the field of sports science, gait recognition has a wide range of applications. However, compared to other biometric technologies, it has the problem of low recognition accuracy. Therefore, a technique combining the parallel genetic algorithm based on hierarchical fair competition with neural network ensemble is proposed to be applied in gait recognition. First, parallel genetic algorithm is adopted to increase individual diversity, and only appropriate features are selected to train each neural network candidate. Then, a set of individual neural networks are selected to complete the neural network ensemble so as to minimize the generalization error and maximize the negative correlation. Experiments on the CASIA gait database demonstrate the effectiveness of the proposed gait recognition method. The results show that the proposed method has a higher recognition rate than the existing methods. © 2018, Ubiquitous International. All rights reserved.

关键词： Genetic algorithms

Collab.rative model in brain-computer integration 2nd

学校读者我要写书评

暂无评论

Collaborative model in brain-computer integration

2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017

作者： Shi, Zhongzhi Ma, Gang Li, Jianqing Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Shandong University No. 27 Shan Da Nan Road JinanShandong China

ISBN: (纸本)9783319681207

Brain-computer integration is a new intelligent system based on brain-computer interface technology, which is integrated with biological intelligence and artificial intelligence. In order to make this integration effective and co-adaptive biological brain and machine should work collab.ratively. ABGP-CNN based environment awareness and motivation driven collab.ration will be presented in the paper. Motivation is the cause of action and plays important roles in collab.ration. The motivation leaning method and algorithm will be explored in terms of event curiosity, which is useful for sharing common interest situations. © IFIP International Federation for information processing 2017.

关键词： Motivation

Corrections to “Iris Center Localization Using Energy Map With Image Inpaint technology and Post-processing Correction”

学校读者我要写书评

暂无评论

IEEE Access 2020年 8卷 76595-76595页

作者： Lihong Dai Jinguo Liu Zhaojie Ju Yang Gao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan China School of Computing University of Portsmouth Portsmouth U.K. Space Technology for Autonomous and Robotic Systems Laboratory (STAR LAB) Surrey Space Centre University of Surrey Guildford U.K.

In the above article [1] , the affiliations of authors Lihong Dai and Yang Gao need to be corrected. Moreover, the biography of Yang Gao needs to be corrected. The specific corrections are as follows.

关键词： Robots Biographies Aerospace electronics Automation Manufacturing Research and development Object recognition

CASICT Tibetanword segmentation system for MLWS2017

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Hu, Jiawei Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Adapt Centre School of Computing Dublin City University

We participated in the MLWS 2017 on Tibetan word segmentation task, our system is trained in a unrestricted way, by introducing a baseline system and 76w tibetan segmented sentences of ours. In the system character sequence is processed by the baseline system into word sequence, then a subword unit (BPE algorithm 1) split rare words into subwords with its corresponding features, after that a neural network classifier is adopted to token each subword into "B,M,E,S" lab.l, in decoding step a simple rule is used to recover a final word sequence. The candidate system for submition is selected by evaluating the F-score in dev set pre-extracted from the 76w sentences. Experiment shows that this method can fix segmentation errors of baseline system and result in a significant performance gain. Copyright © 2017, The Authors. All rights reserved.

关键词：

Refining source representations with relation networks for neural machine translation

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Zhang, Wen Hu, Jiawei Feng, Yang Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China ADAPT Centre School of Computing Dublin City University Ireland

Although neural machine translation (NMT) with the encoder-decoder framework has achieved great success in recent times, it still suffers from some drawbacks: RNNs tend to forget old information which is often useful and the encoder only operates through words without considering word relationship. To solve these problems, we introduce a relation networks (RN) into NMT to refine the encoding representations of the source. In our method, the RN first augments the representation of each source word with its neighbors and reasons all the possible pairwise relations between them. Then the source representations and all the relations are fed to the attention module and the decoder together, keeping the main encoder-decoder architecture unchanged. Experiments on two Chinese-to-English data sets in different scales both show that our method can outperform the competitive baselines significantly. Copyright © 2017, The Authors. All rights reserved.

关键词： Neural machine translation

information-propogation-enhanced neural machine translation by relation model

学校读者我要写书评

暂无评论

arXiv 2017年

Even though sequence-to-sequence neural machine translation (NMT) model have achieved state-of-art performance in the recent fewer years, but it is widely concerned that the recurrent neural network (RNN) units are very hard to capture the long-distance state information, which means RNN can hardly find the feature with long term dependency as the sequence becomes longer. Similarly, convolutional neural network (CNN) is introduced into NMT for speeding recently, however, CNN focus on capturing the local feature of the sequence;To relieve this issue, we incorporate a relation network into the standard encoder-decoder framework to enhance information-propogation in neural network, ensuring that the information of the source sentence can flow into the decoder adequately. Experiments show that proposed framework outperforms the statistical MT model and the state-of-art NMT model significantly on two data sets with different scales. Copyright © 2017, The Authors. All rights reserved.

关键词： Neural machine translation