no code implementations • 10 Sep 2018 • Ji Wang, Jian-Guo Zhang, Weidong Bao, Xiaomin Zhu, Bokai Cao, Philip S. Yu
To benefit from the cloud data center without the privacy risk, we design, evaluate, and implement a cloud-based framework ARDEN which partitions the DNN across mobile devices and cloud data centers.
no code implementations • 10 Sep 2018 • Ji Wang, Bokai Cao, Philip S. Yu, Lichao Sun, Weidong Bao, Xiaomin Zhu
In this paper, we provide an overview of the current challenges and representative achievements about pushing deep learning on mobile devices from three aspects: training with mobile data, efficient inference on mobile devices, and applications of mobile deep learning.
no code implementations • 11 Sep 2018 • Jian-Guo Zhang, Ji Wang, Lifang He, Zhao Li, Philip S. Yu
Then, it is possible to utilize unlabeled data that have a potential of failure to further improve the performance of the model.
no code implementations • 13 Nov 2018 • Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao, Philip S. Yu
To benefit from the on-device deep learning without the capacity and privacy concerns, we design a private model compression framework RONA.
no code implementations • 17 Nov 2018 • Chengdong Feng, Zhenbang Chen, Weijiang Hong, Hengbiao Yu, Wei Dong, Ji Wang
How to ensure the safety of DNN-based system is a critical problem for the research and application of DNN.
no code implementations • 5 Jun 2019 • Lichao Sun, Yingbo Zhou, Ji Wang, Jia Li, Richard Sochar, Philip S. Yu, Caiming Xiong
Privacy-preserving deep learning is crucial for deploying deep neural network based solutions, especially when the model works on data that contains sensitive information.
no code implementations • 6 Sep 2019 • Ji Wang, Qi Jing, Jianbo Gao
To address the challenge, we propose a robust Android malware detection approach based on selective ensemble learning, trying to provide an effective solution not that limited to the quality of datasets.
no code implementations • 9 Feb 2020 • Jiangchao Liu, Liqian Chen, Antoine Mine, Ji Wang
We observe that the robustness radii of correctly classified inputs are much larger than that of misclassified inputs which include adversarial examples, especially those from strong adversarial attacks.
no code implementations • 9 Feb 2020 • Yufeng Zhang, Jialu Pan, Wanwei Liu, Zhenbang Chen, Ji Wang, Zhiming Liu, Kenli Li, Hongmei Wei
For point-wise anomaly detection, our method achieves 90. 7\% AUROC on average and outperforms the baseline by 5. 2\% AUROC.
no code implementations • 24 Oct 2020 • Haoyu Zhang, Dingkun Long, Guangwei Xu, Pengjun Xie, Fei Huang, Ji Wang
Keyphrase extraction (KE) aims to summarize a set of phrases that accurately express a concept or a topic covered in a given document.
no code implementations • 17 Nov 2020 • J. G. Schulze, Ji Wang, J. A. Johnson, C. T. Unterborn, W. R. Panero
We find that these two measures are unlikely to be resolvable as statistically different unless the bulk density CMF is at least 40% greater than or 50% less than the CMF as inferred from the host star.
Earth and Planetary Astrophysics Solar and Stellar Astrophysics
no code implementations • 19 Oct 2022 • Longyuan Zhang, Ziyue Hou, Ji Wang, Ziang Liu, Wei Li
Multiple predictive path points are dynamically generated by a deep Markov model optimized using RL approach for robot to track.
1 code implementation • 28 Oct 2022 • Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai
In this paper, we present a scalable algorithm for spectral clustering (SC) with group fairness constraints.
no code implementations • 1 Dec 2022 • Chengbo Qiu, Kai Yang, Ji Wang, Shenjie Zhao
6G is envisioned to offer higher data rate, improved reliability, ubiquitous AI services, and support massive scale of connected devices.
no code implementations • 29 Jul 2023 • Ye Tao, Wanwei Liu, Fu Song, Zhen Liang, Ji Wang, Hongxu Zhu
Quantized neural networks (QNNs) have been developed, with binarized neural networks (BNNs) restricted to binary values as a special case.
no code implementations • 7 Oct 2023 • Shuyang Liu, Zixuan Chen, Ge Shi, Ji Wang, Changjie Fan, Yu Xiong, Runze Wu Yujing Hu, Ze Ji, Yang Gao
Thus, we propose a novel baseline construction method called Shapley Integrated Gradients (SIG) that searches for a set of baselines by proportional sampling to partly simulate the computation path of Shapley Value.
no code implementations • 23 Jan 2024 • Zhen Liang, Taoran Wu, Ran Zhao, Bai Xue, Ji Wang, Wenjing Yang, Shaojun Deng, Wanwei Liu
However, these strategies face challenges in addressing the "unknown dilemma" concerning whether the exact output region or the introduced approximation error violates the property in question.
no code implementations • 13 Apr 2024 • Taoran Wu, Yiqing Yu, Bican Xia, Ji Wang, Bai Xue
Ensuring safety through set invariance has proven to be a valuable method in various robotics and control applications.
1 code implementation • 9 Oct 2022 • Zhen Liang, Dejin Ren, Wanwei Liu, Ji Wang, Wenjing Yang, Bai Xue
The homeomorphism property exists in some widely used NNs such as invertible NNs.
1 code implementation • 27 Jun 2023 • Zhen Liang, Dejin Ren, Bai Xue, Ji Wang, Wenjing Yang, Wanwei Liu
Moreover, for NNs that do not feature these properties with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property and then abandon these subsets for reachability computations.
1 code implementation • 6 Aug 2023 • Peiguang Jing, Xianyi Liu, Ji Wang, Yinwei Wei, Liqiang Nie, Yuting Su
Emotion distribution learning has gained increasing attention with the tendency to express emotions through images.
1 code implementation • 5 May 2023 • Zhen Liang, Taoran Wu, Changyuan Zhao, Wanwei Liu, Bai Xue, Wenjing Yang, Ji Wang
For the fine-tuning repair process, BIRDNN analyzes the behavior differences of neurons on positive and negative samples to identify the most responsible neurons for the erroneous behaviors.
1 code implementation • ACL 2019 • Haoyu Zhang, Jingjing Cai, Jianjun Xu, Ji Wang
We conduct experiments on COMPLEXWEBQUESTIONS which is a large scale complex question semantic parsing dataset, results show that our model achieves significant improvement compared to state-of-the-art methods.
Ranked #1 on Semantic Parsing on complexWebQuestions-V1.0
4 code implementations • CONLL 2019 • Haoyu Zhang, Jianjun Xu, Ji Wang
For the decoder, there are two stages in our model, in the first stage, we use a Transformer-based decoder to generate a draft output sequence.
Ranked #30 on Abstractive Text Summarization on CNN / Daily Mail
1 code implementation • CVPR 2019 • Kean Chen, Jianguo Li, Weiyao Lin, John See, Ji Wang, Ling-Yu Duan, Zhibo Chen, Changwei He, Junni Zou
For this purpose, we develop a novel optimization algorithm, which seamlessly combines the error-driven update scheme in perceptron learning and backpropagation algorithm in deep networks.
1 code implementation • 17 Aug 2020 • Kean Chen, Weiyao Lin, Jianguo Li, John See, Ji Wang, Junni Zou
This paper alleviates this issue by proposing a novel framework to replace the classification task in one-stage detectors with a ranking task, and adopting the Average-Precision loss (AP-loss) for the ranking problem.
2 code implementations • 12 Mar 2017 • Tien Tuan Anh Dinh, Ji Wang, Gang Chen, Rui Liu, Beng Chin Ooi, Kian-Lee Tan
However, there is a clear lack of a systematic framework with which different systems can be analyzed and compared against each other.
Databases Cryptography and Security Distributed, Parallel, and Cluster Computing
1 code implementation • 17 Aug 2017 • Tien Tuan Anh Dinh, Rui Liu, Meihui Zhang, Gang Chen, Beng Chin Ooi, Ji Wang
Blockchain technologies are gaining massive momentum in the last few years.
Databases Cryptography and Security
1 code implementation • 26 Dec 2018 • Lichao Sun, Yingtong Dou, Carl Yang, Ji Wang, Yixin Liu, Philip S. Yu, Lifang He, Bo Li
Therefore, this review is intended to provide an overall landscape of more than 100 papers on adversarial attack and defense strategies for graph data, and establish a unified formulation encompassing most graph adversarial learning models.