no code implementations • 14 May 2022 • Xiaohong Fan, Yin Yang, Ke Chen, Jianping Zhang, Ke Dong
CS is an efficient method to accelerate the acquisition of MR images from under-sampled k-space data.
no code implementations • 2 Feb 2022 • Jiawei Lu, He Wang, Tianjia Shao, Yin Yang, Kun Zhou
However, as source images are often misaligned due to the large disparities among the camera settings, strong assumptions have been made in the past with respect to the camera(s) or/and the object in interest, limiting the application of such techniques.
1 code implementation • 15 Nov 2021 • Bo Lyu, Shengbo Wang, Shiping Wen, Kaibo Shi, Yin Yang, TingWen Huang
But the exploration of the large-scale sparse graph computing on processing-in-memory (PIM) platforms (typically with memristive crossbars) is still in its infancy.
2 code implementations • 26 Oct 2021 • Prakhar Ganesh, Yao Chen, Yin Yang, Deming Chen, Marianne Winslett
Performance of object detection models has been growing rapidly on two major fronts, model accuracy and efficiency.
no code implementations • 29 Sep 2021 • Ergute Bao, Yizheng Zhu, Xiaokui Xiao, Yin Yang, Beng Chin Ooi, Benjamin Hong Meng Tan, Khin Mi Mi Aung
We point out a major challenge in this problem setting: that common mechanisms for enforcing DP in deep learning, which require injecting \textit{real-valued noise}, are fundamentally incompatible with MPC, which exchanges \textit{finite-field integers} among the participants.
1 code implementation • ICCV 2021 • Hui Ying, He Wang, Tianjia Shao, Yin Yang, Kun Zhou
Image generation has been heavily investigated in computer vision, where one core research challenge is to generate images from arbitrarily complex distributions with little supervision.
1 code implementation • 11 Jul 2021 • Xiaohong Fan, Yin Yang, Jianping Zhang
Compressed sensing (CS) is an efficient method to reconstruct MR image from small sampled data in $k$-space and accelerate the acquisition of MRI.
no code implementations • 28 Jun 2021 • Yin Yang
However, training / running large-scale DNNs as part of a smart contract is infeasible on today's blockchain platforms, due to two fundamental design issues of these platforms.
no code implementations • 8 Feb 2021 • Lijuan Liu, Yin Yang, Yi Yuan, Tianjia Shao, He Wang, Kun Zhou
In this paper, we propose an effective global relation learning algorithm to recommend an appropriate location of a building unit for in-game customization of residential home complex.
no code implementations • 7 Feb 2021 • Renchi Yang, Jieming Shi, Yin Yang, Keke Huang, Shiqi Zhang, Xiaokui Xiao
Given a graph G where each node is associated with a set of attributes, and a parameter k specifying the number of output clusters, k-attributed graph clustering (k-AGC) groups nodes in G into k disjoint clusters, such that nodes within the same cluster share similar topological and attribute characteristics, while those in different clusters are dissimilar.
1 code implementation • 4 Feb 2021 • Chi Wang, Yunke Zhang, Miaomiao Cui, Peiran Ren, Yin Yang, Xuansong Xie, Xiansheng Hua, Hujun Bao, Weiwei Xu
This paper proposes a novel active boundary loss for semantic segmentation.
1 code implementation • ICCV 2021 • Zheng Dong, Ke Xu, Yin Yang, Hujun Bao, Weiwei Xu, Rynson W. H. Lau
It is beneficial to strong reflection detection and substantially improves the quality of reflection removal results.
1 code implementation • 1 Dec 2020 • Fei Ding, Yin Yang, Hongxin Hu, Venkat Krovi, Feng Luo
While it is important to transfer the full knowledge from teacher to student, we introduce the Multi-level Knowledge Distillation (MLKD) by effectively considering both knowledge alignment and correlation.
no code implementations • 15 Sep 2020 • Siyuan Shen, Tianjia Shao, Kun Zhou, Chenfanfu Jiang, Feng Luo, Yin Yang
We believe our method will inspire a wide-range of new algorithms for deep learning and numerical optimization.
1 code implementation • 26 Jun 2020 • Hang Zhao, Qijin She, Chenyang Zhu, Yin Yang, Kai Xu
We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP).
no code implementations • 17 Jun 2020 • Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai
These stages usually allocate resource manually with specific computing power budgets, which requires the serving configuration to adapt accordingly.
no code implementations • 27 Feb 2020 • Prakhar Ganesh, Yao Chen, Xin Lou, Mohammad Ali Khan, Yin Yang, Hassan Sajjad, Preslav Nakov, Deming Chen, Marianne Winslett
Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks.
no code implementations • 19 Feb 2020 • Jieming Shi, Tianyuan Jin, Renchi Yang, Xiaokui Xiao, Yin Yang
Given a graph G and a node u in G, a single source SimRank query evaluates the similarity between u and every node v in G. Existing approaches to single source SimRank computation incur either long query response time, or expensive pre-computation, which needs to be performed again whenever the graph G changes.
no code implementations • 13 Nov 2019 • Fei Ding, Feng Luo, Yin Yang
We enforce the encoder and the generator of GAN to form an encoder-generator pair in addition to the generator-encoder pair, which enables us to avoid the low-diversity generation and the triviality of latent features.
no code implementations • WS 2019 • Shehel Yoosuf, Yin Yang
This paper presents the winning solution of the Fragment Level Classification (FLC) task in the Fine Grained Propaganda Detection competition at the NLP4IF{'}19 workshop.
no code implementations • 27 Sep 2019 • Jingwei Ma, Jiahui Wen, Mingyang Zhong, Liangchen Liu, Chaojie Li, Weitong Chen, Yin Yang, Honghui Tu, Xue Li
In addition, we propose to jointly learn user-user group (item-item group) hierarchies, so that we can effectively discover latent groups and learn compact user/item representations.
no code implementations • 28 Jun 2019 • Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao, Siu Cheung Hui, Hyejin Shin, Junbum Shin, Ge Yu
Motivated by this, we first propose novel LDP mechanisms for collecting a numeric attribute, whose accuracy is at least no worse (and usually better) than existing solutions in terms of worst-case noise variance.
no code implementations • 17 Jun 2019 • Renchi Yang, Jieming Shi, Xiaokui Xiao, Yin Yang, Sourav S. Bhowmick
Given an input graph G and a node v in G, homogeneous network embedding (HNE) maps the graph structure in the vicinity of v to a compact, fixed-dimensional feature vector.
1 code implementation • 24 Mar 2018 • Ran Luo, Tianjia Shao, Huamin Wang, Weiwei Xu, Kun Zhou, Yin Yang
DeepWarp is an efficient and highly re-usable deep neural network (DNN) based nonlinear deformable simulation framework.
Graphics
no code implementations • 16 Jun 2016 • Thông T. Nguyên, Xiaokui Xiao, Yin Yang, Siu Cheung Hui, Hyejin Shin, Junbum Shin
Organizations with a large user base, such as Samsung and Google, can potentially benefit from collecting and mining users' data.
Databases
no code implementations • 19 May 2016 • Kele Xu, Yin Yang, Clémence Leboullenger, Pierre Roussel, Bruce Denby
This article describes a contour-based 3D tongue deformation visualization framework using B-mode ultrasound image sequences.
no code implementations • 19 May 2016 • Kele Xu, Yin Yang, Aurore Jaumard-Hakoun, Clemence Leboullenger, Gerard Dreyfus, Pierre Roussel, Maureen Stone, Bruce Denby
This article describes the development of a platform designed to visualize the 3D motion of the tongue using ultrasound image sequences.
1 code implementation • 13 Feb 2016 • Ganzhao Yuan, Yin Yang, Zhenjie Zhang, Zhifeng Hao
This paper points out that under ($\epsilon$, $\delta$)-differential privacy, the optimal solution of the above constrained optimization problem in search of a suitable strategy can be found, rather surprisingly, by solving a simple and elegant convex optimization program.