Search Results for author: Ji Wang

Found 24 papers, 8 papers with code

AI Empowered Net-RCA for 6G

no code implementations1 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.


Scalable Spectral Clustering with Group Fairness Constraints

1 code implementation28 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.

Fairness Stochastic Block Model

Robot Navigation with Reinforcement Learned Path Generation and Fine-Tuned Motion Control

no code implementations19 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.

Reinforcement Learning (RL) Robot Navigation

On the Probability that a Rocky Planet's Composition Reflects its Host Star

no code implementations17 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

Keyphrase Extraction with Dynamic Graph Convolutional Networks and Diversified Inference

no code implementations24 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.

Keyphrase Extraction Representation Learning

AP-Loss for Accurate One-Stage Object Detection

1 code implementation17 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.

Classification General Classification +2

Input Validation for Neural Networks via Runtime Local Robustness Verification

no code implementations9 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.

SEdroid: A Robust Android Malware Detector using Selective Ensemble Learning

no code implementations6 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.

Android Malware Detection Ensemble Learning +1

Complex Question Decomposition for Semantic Parsing

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.

Semantic Parsing

Private Deep Learning with Teacher Ensembles

no code implementations5 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.

Ensemble Learning Knowledge Distillation +2

Towards Accurate One-Stage Object Detection with AP-Loss

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.

Classification General Classification +2

Pretraining-Based Natural Language Generation for Text Summarization

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.

Abstractive Text Summarization Text Generation

Adversarial Attack and Defense on Graph Data: A Survey

1 code implementation26 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.

Adversarial Attack Image Classification +1

Boosting the Robustness Verification of DNN by Identifying the Achilles's Heel

no code implementations17 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.

Private Model Compression via Knowledge Distillation

no code implementations13 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.

Knowledge Distillation Model Compression +1

Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction

no code implementations11 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.

Anomaly Detection

Deep Learning Towards Mobile Applications

no code implementations10 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.

BIG-bench Machine Learning

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud

no code implementations10 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.

Privacy Preserving

Untangling Blockchain: A Data Processing View of Blockchain Systems

1 code implementation17 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

BLOCKBENCH: A Framework for Analyzing Private Blockchains

2 code implementations12 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

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