1 code implementation • 2 May 2022 • Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang
Most real-world knowledge graphs (KG) are far from complete and comprehensive.
no code implementations • 30 Apr 2022 • Yangcheng Gao, Zhao Zhang, Richang Hong, Haijun Zhang, Jicong Fan, Shuicheng Yan, Meng Wang
To this end, we propose a new and effective data-free quantization method termed ClusterQ, which utilizes the semantic feature distribution alignment for synthetic data generation.
no code implementations • 16 Apr 2022 • Suiyi Zhao, Zhao Zhang, Richang Hong, Mingliang Xu, Yi Yang, Meng Wang
Blind image deblurring (BID) remains a challenging and significant task.
no code implementations • 10 Apr 2022 • Ziyue Zhu, Zhao Zhang, Zheng Lin, Ruiqi Wu, Zhi Chai, Chun-Le Guo
To achieve visual consistency in composite images, recent image harmonization methods typically summarize the appearance pattern of global background and apply it to the global foreground without location discrepancy.
no code implementations • 25 Mar 2022 • Zheng Lin, Zhao Zhang, Kang-Rui Zhang, Bo Ren, Ming-Ming Cheng
Our IST method can serve as a brush, dip style from anywhere, and then paint to any region of the target content image.
no code implementations • 1 Feb 2022 • Zhao Zhang, Ding Zhao, Xianfeng Terry Yang
Full-field traffic state information (i. e., flow, speed, and density) is critical for the successful operation of Intelligent Transportation Systems (ITS) on freeways.
no code implementations • 27 Dec 2021 • Fuwei Zhang, Zhao Zhang, Xiang Ao, Dehong Gao, Fuzhen Zhuang, Yi Wei, Qing He
The proposed model encodes the textual information in queries, documents and the KG with multilingual BERT, and incorporates the KG information in the query-document matching process with a hierarchical information fusion mechanism.
no code implementations • 24 Nov 2021 • Yu Liu, Mingbo Zhao, Zhao Zhang, Haijun Zhang, Shuicheng Yan
Based on this dataset, we then propose the Arbitrary Virtual Try-On Network (AVTON) that is utilized for all-type clothes, which can synthesize realistic try-on images by preserving and trading off characteristics of the target clothes and the reference person.
no code implementations • 11 Nov 2021 • Zhao Zhang, Fuzhen Zhuang, HengShu Zhu, Chao Li, Hui Xiong, Qing He, Yongjun Xu
This will lead to low-quality and unreliable representations of KGs.
no code implementations • EMNLP 2021 • Baojun Wang, Zhao Zhang, Kun Xu, Guang-Yuan Hao, Yuyang Zhang, Lifeng Shang, Linlin Li, Xiao Chen, Xin Jiang, Qun Liu
Incorporating lexical knowledge into deep learning models has been proved to be very effective for sequence labeling tasks.
no code implementations • 31 Aug 2021 • Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu
Graph neural networks for heterogeneous graph embedding is to project nodes into a low-dimensional space by exploring the heterogeneity and semantics of the heterogeneous graph.
no code implementations • 23 Jul 2021 • Jicong Fan, Zhao Zhang, Mingbo Zhao, Yiheng Tu, Haijun Zhang
The main idea is to find the most reliable affinity matrix among a set of candidates given by different AMC methods with different hyperparameters, where the reliability is quantified by the \textit{relative-eigen-gap} of graph Laplacian introduced in this paper.
2 code implementations • 4 Jul 2021 • J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang
Kronecker-factored Approximate Curvature (K-FAC) has recently been shown to converge faster in deep neural network (DNN) training than stochastic gradient descent (SGD); however, K-FAC's larger memory footprint hinders its applicability to large models.
2 code implementations • ACL 2021 • Thamme Gowda, Zhao Zhang, Chris A Mattmann, Jonathan May
While there are more than 7000 languages in the world, most translation research efforts have targeted a few high-resource languages.
no code implementations • 2 Feb 2021 • Zhao Zhang, Chengfeng Cai, Xue-Min Jiang, Yi-Lei Tang, Zhao-Huan Yu, Hong-Hao Zhang
We investigate the potential stochastic gravitational waves from first-order electroweak phase transitions in a model with pseudo-Nambu-Goldstone dark matter and two Higgs doublets.
High Energy Physics - Phenomenology Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology
no code implementations • 24 Dec 2020 • P. J. Wang, L. D. Kong, S. Zhang, Y. P. Chen, S. N. Zhang, J. L. Qu, L. Ji, L. Tao, M. Y. Ge, F. J. Lu, L. Chen, L. M. Song, T. P. Li, Y. P. Xu, X. L. Cao, Y. Chen, C. Z. Liu, Q. C. Bu, C. Cai, Z. Chang, G. Chen, T. X. Chen, Y. B. Chen, W. Cui, W. W. Cui, J. K. Deng, Y. W. Dong, Y. Y. Du, M. X. Fu, G. H. Gao, H. Gao, M. Gao, Y. D. Gu, J. Guan, C. C. Guo, D. W. Han, Y. Huang, J. Huo, S. M. Jia, L. H. Jiang, W. C. Jiang, J. Jin, Y. J. Jin, B. Li, C. K. Li, G. Li, M. S. Li, W. Li, X. Li, X. B. Li, X. F. Li, Y. G. Li, Z. W. Li, X. H. Liang, J. Y. Liao, B. S. Liu, G. Q. Liu, H. W. Liu, X. J. Liu, Y. N. Liu, B. Lu, X. F. Lu, Q. Luo, T. Luo, X. Ma, B. Meng, Y. Nang, J. Y. Nie, G. Ou, N. Sai, R. C. Shang, X. Y. Song, L. Sun, Y. Tan, Y. L. Tuo, C. Wang, G. F. Wang, J. Wang, L. J. Wang, W. S. Wang, Y. S. Wang, X. Y. Wen, B. Y. Wu, B. B. Wu, M. Wu, G. C. Xiao, S. Xiao, S. L. Xiong, J. W. Yang, S. Yang, Yan Ji Yang, Yi Jung Yang, Q. B. Yi, Q. Q. Yin, Y. You, A. M. Zhang, C. M. Zhang, F. Zhang, H. M. Zhang, J. Zhang, T. Zhang, W. C. Zhang, W. Zhang, W. Z. Zhang, Y. F. Zhang, Y. J. Zhang, Y. Zhang, Zhao Zhang, Zhi Zhang, Z. L. Zhang, H. S. Zhao, X. F. Zhao, S. J. Zheng, Y. G. Zheng, D. K. Zhou, J. F. Zhou, Y. X. Zhu, Y. Zhu, R. L. Zhuang
The results show a general trend of the pulse fraction increasing with luminosity and energy at super-critical luminosity.
High Energy Astrophysical Phenomena
no code implementations • 8 Sep 2020 • Yan Zhang, Zhao Zhang, Yang Wang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang
Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within both the basis and representation spaces.
no code implementations • 31 Jul 2020 • Zhao Zhang, Yan Zhang, Mingliang Xu, Li Zhang, Yi Yang, Shuicheng Yan
In this paper, we therefore survey the recent advances on CF methodologies and the potential benchmarks by categorizing and summarizing the current methods.
no code implementations • 14 Jul 2020 • Yun Yuan, Zhao Zhang, Xianfeng Terry Yang
This novel approach can encode physics models, i. e., classical traffic flow models, into the Gaussian process architecture and so as to regularize the ML training process.
2 code implementations • 1 Jul 2020 • J. Gregory Pauloski, Zhao Zhang, Lei Huang, Weijia Xu, Ian T. Foster
Training neural networks with many processors can reduce time-to-solution; however, it is challenging to maintain convergence and efficiency at large scales.
no code implementations • 20 Jun 2020 • Jinjia Peng, Yang Wang, Huibing Wang, Zhao Zhang, Xianping Fu, Meng Wang
For PAL, a data adaptation module is employed for source domain, which generates the images with similar data distribution to unlabeled target domain as ``pseudo target samples''.
no code implementations • 15 Jun 2020 • Yang You, Yuhui Wang, huan zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh
For the first time we scale the batch size on ImageNet to at least a magnitude larger than all previous work, and provide detailed studies on the performance of many state-of-the-art optimization schemes under this setting.
1 code implementation • 30 Apr 2020 • Zhao Zhang, Zheng Lin, Jun Xu, Wenda Jin, Shao-Ping Lu, Deng-Ping Fan
To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task.
Ranked #3 on
RGB-D Salient Object Detection
on SIP
RGB-D Salient Object Detection
RGB Salient Object Detection
+1
1 code implementation • ECCV 2020 • Zhao Zhang, Wenda Jin, Jun Xu, Ming-Ming Cheng
Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group of relevant images.
Ranked #2 on
Co-Salient Object Detection
on CoCA
no code implementations • 6 Feb 2020 • Yun Yuan, Xianfeng Terry Yang, Zhao Zhang, Shandian Zhe
To address this issue, this study presents a new modeling framework, named physics regularized machine learning (PRML), to encode classical traffic flow models (referred as physical models) into the ML architecture and to regularize the ML training process.
no code implementations • 23 Jan 2020 • Yanyan Wei, Zhao Zhang, Yang Wang, Haijun Zhang, Mingbo Zhao, Mingliang Xu, Meng Wang
Although supervised deep deraining networks have obtained impressive results on synthetic datasets, they still cannot obtain satisfactory results on real images due to weak generalization of rain removal capacity, i. e., the pre-trained models usually cannot handle new shapes and directions that may lead to over-derained/under-derained results.
no code implementations • 23 Jan 2020 • Zhao Zhang, Zemin Tang, Yang Wang, Zheng Zhang, Choujun Zhan, ZhengJun Zha, Meng Wang
To construct FDRN, we propose a new fast residual dense block (f-RDB) to retain the ability of local feature fusion and local residual learning of original RDB, which can reduce the computing efforts at the same time.
no code implementations • 26 Dec 2019 • Jiahuan Ren, Zhao Zhang, Sheng Li, Yang Wang, Guangcan Liu, Shuicheng Yan, Meng Wang
Specifically, J-RFDL performs the robust representation by DL in a factorized compressed space to eliminate the negative effects of noise and outliers on the results, which can also make the DL process efficient.
no code implementations • 17 Dec 2019 • Zhao Zhang, Yulin Sun, Yang Wang, Zheng-Jun Zha, Shuicheng Yan, Meng Wang
To address this issue, we propose a novel generalized end-to-end representation learning architecture, dubbed Convolutional Dictionary Pair Learning Network (CDPL-Net) in this paper, which integrates the learning schemes of the CNN and dictionary pair learning into a unified framework.
no code implementations • 15 Dec 2019 • Yanyan Wei, Zhao Zhang, Yang Wang, Mingliang Xu, Yi Yang, Shuicheng Yan, Meng Wang
However, in practice it is rather common to have no un-paired images in real deraining task, in such cases how to remove the rain streaks in an unsupervised way will be a very challenging task due to lack of constraints between images and hence suffering from low-quality recovery results.
no code implementations • 15 Dec 2019 • Zhao Zhang, Zemin Tang, Yang Wang, Haijun Zhang, Shuicheng Yan, Meng Wang
LDB is a convolutional block similarly as dense block, but it can reduce the computation cost and weight size to (1/L, 2/L), compared with original ones, where L is the number of layers in blocks.
no code implementations • 13 Dec 2019 • Xianzhen Li, Zhao Zhang, Yang Wang, Guangcan Liu, Shuicheng Yan, Meng Wang
In this paper, we explore the deep multi-subspace recovery problem by designing a multilayer architecture for latent LRR.
no code implementations • 13 Dec 2019 • Zhao Zhang, Zemin Tang, Zheng Zhang, Yang Wang, Jie Qin, Meng Wang
But existing CNNs based frameworks still have several drawbacks: 1) the traditaional pooling operation may lose important feature information and is unlearnable; 2) the tradi-tional convolution operation optimizes slowly and the hierar-chical features from different layers are not fully utilized.
no code implementations • 13 Dec 2019 • Yan Zhang, Zhao Zhang, Zheng Zhang, Mingbo Zhao, Li Zhang, Zheng-Jun Zha, Meng Wang
In this paper, we investigate the unsupervised deep representation learning issue and technically propose a novel framework called Deep Self-representative Concept Factorization Network (DSCF-Net), for clustering deep features.
no code implementations • 1 Dec 2019 • Biao Qian, Yang Wang, Zhao Zhang, Richang Hong, Meng Wang, Ling Shao
We intuitively find that M$^2$Net can essentially promote the diversity of the inference path (selected blocks subset) selection, so as to enhance the recognition accuracy.
no code implementations • 23 Nov 2019 • Huibing Wang, Yang Wang, Zhao Zhang, Xianping Fu, Zhuo Li, Mingliang Xu, Meng Wang
With the popularity of multimedia technology, information is always represented or transmitted from multiple views.
no code implementations • 20 Nov 2019 • Yulin Sun, Zhao Zhang, Weiming Jiang, Zheng Zhang, Li Zhang, Shuicheng Yan, Meng Wang
In this paper, we propose a structured Robust Adaptive Dic-tionary Pair Learning (RA-DPL) framework for the discrim-inative sparse representation learning.
no code implementations • 20 Nov 2019 • Huan Zhang, Zhao Zhang, Mingbo Zhao, Qiaolin Ye, Min Zhang, Meng Wang
Our method can jointly re-cover the underlying clean data, clean labels and clean weighting spaces by decomposing the original data, predicted soft labels or weights into a clean part plus an error part by fitting noise.
no code implementations • 2 Sep 2019 • Zhao Zhang, Yan Zhang, Sheng Li, Guangcan Liu, Dan Zeng, Shuicheng Yan, Meng Wang
For auto-weighting, RFA-LCF jointly preserves the manifold structures in the basis concept space and new coordinate space in an adaptive manner by minimizing the reconstruction errors on clean data, anchor points and coordinates.
no code implementations • 28 Aug 2019 • Yanyan Wei, Zhao Zhang, Haijun Zhang, Richang Hong, Meng Wang
To obtain the negative rain streaks during training process more accurately, we present a new module named dual path residual dense block, i. e., Residual path and Dense path.
no code implementations • 21 Aug 2019 • Zhao Zhang, Yulin Sun, Zheng Zhang, Yang Wang, Guangcan Liu, Meng Wang
In this setting, our TP-DPL integrates the twin-incoherence based latent flexible DPL and the joint embedding of codes as well as salient features by twin-projection into a unified model in an adaptive neighborhood-preserving manner.
no code implementations • 21 Aug 2019 • Zhao Zhang, Lei Wang, Sheng Li, Yang Wang, Zheng Zhang, Zheng-Jun Zha, Meng Wang
Specifically, AS-LRC performs the latent decomposition of given data into a low-rank reconstruction by a block-diagonal codes matrix, a group sparse locality-adaptive salient feature part and a sparse error part.
no code implementations • 4 Aug 2019 • Zhao Zhang, Jiahuan Ren, Sheng Li, Richang Hong, Zheng-Jun Zha, Meng Wang
Leveraging on the Frobenius-norm based latent low-rank representation model, rBDLR jointly learns the coding coefficients and salient features, and improves the results by enhancing the robustness to outliers and errors in given data, preserving local information of salient features adaptively and ensuring the block-diagonal structures of the coefficients.
2 code implementations • 15 Jul 2019 • Deng-Ping Fan, Zheng Lin, Jia-Xing Zhao, Yun Liu, Zhao Zhang, Qibin Hou, Menglong Zhu, Ming-Ming Cheng
The use of RGB-D information for salient object detection has been extensively explored in recent years.
Ranked #4 on
RGB-D Salient Object Detection
on RGBD135
RGB-D Salient Object Detection
RGB Salient Object Detection
+1
no code implementations • 11 Jun 2019 • Zhao Zhang, Jiahuan Ren, Weiming Jiang, Zheng Zhang, Richang Hong, Shuicheng Yan, Meng Wang
We propose a joint subspace recovery and enhanced locality based robust flexible label consistent dictionary learning method called Robust Flexible Discriminative Dictionary Learning (RFDDL).
no code implementations • 29 May 2019 • Zhao Zhang, Lei Jia, Mingbo Zhao, Guangcan Liu, Meng Wang, Shuicheng Yan
A Kernel-Induced Label Propagation (Kernel-LP) framework by mapping is proposed for high-dimensional data classification using the most informative patterns of data in kernel space.
no code implementations • 27 May 2019 • Zhao Zhang, Weiming Jiang, Jie Qin, Li Zhang, Fanzhang Li, Min Zhang, Shuicheng Yan
Then we compute a linear classifier based on the approximated sparse codes by an analysis mechanism to simultaneously consider the classification and representation powers.
no code implementations • 25 May 2019 • Zhao Zhang, Yan Zhang, Sheng Li, Guangcan Liu, Meng Wang, Shuicheng Yan
RFA-LCF integrates the robust flexible CF, robust sparse local-coordinate coding and the adaptive reconstruction weighting learning into a unified model.
no code implementations • 25 May 2019 • Zhao Zhang, Weiming Jiang, Zheng Zhang, Sheng Li, Guangcan Liu, Jie Qin
More importantly, LC-PDL avoids using the complementary data matrix to learn the sub-dictionary over each class.
no code implementations • 25 May 2019 • Zhao Zhang, Yan Zhang, Guangcan Liu, Jinhui Tang, Shuicheng Yan, Meng Wang
To enrich prior knowledge to enhance the discrimination, RS2ACF clearly uses class information of labeled data and more importantly propagates it to unlabeled data by jointly learning an explicit label indicator for unlabeled data.
no code implementations • 17 May 2019 • Shuaifeng Pang, Xiaodong Qi, Zhao Zhang, Cheqing Jin, Aoying Zhou
Although the emergence of the programmable smart contract makes blockchain systems easily embrace a wider range of industrial areas, how to execute smart contracts efficiently becomes a big challenge nowadays.
Databases Distributed, Parallel, and Cluster Computing
no code implementations • EMNLP 2018 • Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, Qing He
To this end, in this paper, we extend existing KGE models TransE, TransH and DistMult, to learn knowledge representations by leveraging the information from the HRS.
1 code implementation • 27 Sep 2018 • Zhao Zhang, Lei Huang, Uri Manor, Linjing Fang, Gabriele Merlo, Craig Michoski, John Cazes, Niall Gaffney
Our experiments with benchmarks and real applications show that FanStore can scale DL training to 512 compute nodes with over 90\% scaling efficiency.
Distributed, Parallel, and Cluster Computing
no code implementations • 20 Sep 2018 • Yong Zhang, Yu Zhang, Zhao Zhang, Jie Bao, Yunpeng Song
Traditional human activity recognition (HAR) based on time series adopts sliding window analysis method.
no code implementations • 30 Mar 2018 • Guangcan Liu, Zhao Zhang, Qingshan Liu, Kongkai Xiong
Dimension reduction is widely regarded as an effective way for decreasing the computation, storage and communication loads of data-driven intelligent systems, leading to a growing demand for statistical methods that allow analysis (e. g., clustering) of compressed data.
1 code implementation • 14 Sep 2017 • Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
If we can make full use of the supercomputer for DNN training, we should be able to finish the 90-epoch ResNet-50 training in one minute.
2 code implementations • 12 Sep 2014 • Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez, Haoyuan Li, Zhao Zhang, Michael J. Franklin, Ali Ghodsi, Michael. I. Jordan
In this work, we present Velox, a new component of the Berkeley Data Analytics Stack.
Databases