1 code implementation • 24 Aug 2023 • Bin Wang, Fan Wu, Xiao Han, Jiahui Peng, Huaping Zhong, Pan Zhang, Xiaoyi Dong, Weijia Li, Wei Li, Jiaqi Wang, Conghui He
A practical solution to this problem would be to utilize the available multimodal large language models (MLLMs) to generate instruction data for vision-language tasks.
no code implementations • NeurIPS 2020 • Zhen Zhang, Mohammed Haroon Dupty, Fan Wu, Javen Qinfeng Shi, Wee Sun Lee
In recent years, we have witnessed a surge of Graph Neural Networks (GNNs), most of which can learn powerful representations in an end-to-end fashion with great success in many real-world applications.
no code implementations • 5 Jul 2023 • Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David Forsyth, Bo Li, Dawn Song
As the prevalence of data analysis grows, safeguarding data privacy has become a paramount concern.
no code implementations • 1 Jun 2023 • Mst Shapna Akter, Hossain Shahriar, Sheikh Iqbal Ahamed, Kishor Datta Gupta, Muhammad Rahman, Atef Mohamed, Mohammad Rahman, Akond Rahman, Fan Wu
Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems.
1 code implementation • 31 May 2023 • Mst Shapna Akter, Md Jobair Hossain Faruk, Nafisa Anjum, Mohammad Masum, Hossain Shahriar, Akond Rahman, Fan Wu, Alfredo Cuzzocrea
Our goal is to distinguish the performance between QNN and NN and to conduct the experiment, we develop two different models for QNN and NN by utilizing Pennylane for quantum and TensorFlow and Keras for traditional respectively.
no code implementations • 18 Mar 2023 • Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Guihai Chen
In this work, we propose a device-cloud collaborative controlled learning framework, called DC-CCL, enabling a cloud-side large vision model that cannot be directly deployed on the mobile device to still benefit from the device-side local samples.
no code implementations • 4 Mar 2023 • Fan Wu, Zhanhong Cheng, Huiyu Chen, Tony Z. Qiu, Lijun Sun
This method can be applied to impute traffic state data from fixed sensors or probe vehicles.
no code implementations • 20 Dec 2022 • Lingbo Li, Leslie Kanthan, Michail Basios, Fan Wu, Manal Adham, Vitali Avagyan, Alexis Butler, Paul Brookes, Rafail Giavrimis, Buhong Liu, Chrystalla Pavlou, Matthew Truscott, Vardan Voskanyan
Additionally, a key feature of evoML is that it embeds code and model optimisation into the model development process, and includes multi-objective optimisation capabilities.
no code implementations • 3 Dec 2022 • Jiangcong Liu, Hao Ma, Yun Guan, Fan Wu, Le Xu, Yang Zhang, Lixia Tian
We evaluated the effectiveness of AINS with both statistical and predictive analyses on individual differences in sex and intelligence quotient (IQ), based on the four movie fMRI runs included in the Human Connectome Project dataset.
1 code implementation • 28 Nov 2022 • Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao
More specifically, we demonstrate that while the constraint of adversarial robustness consistently degrades the standard accuracy in the balanced class setting, the class imbalance ratio plays a fundamentally different role in accuracy disparity compared to the Gaussian case, due to the heavy tail of the stable distribution.
no code implementations • 11 Nov 2022 • Yikai Yan, Chaoyue Niu, Fan Wu, Qinya Li, Shaojie Tang, Chengfei Lyu, Guihai Chen
The mainstream workflow of image recognition applications is first training one global model on the cloud for a wide range of classes and then serving numerous clients, each with heterogeneous images from a small subset of classes to be recognized.
no code implementations • 21 Oct 2022 • Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Guihai Chen
To meet the practical requirements of low latency, low cost, and good privacy in online intelligent services, more and more deep learning models are offloaded from the cloud to mobile devices.
no code implementations • 10 Oct 2022 • Fan Wu, Sanghyun Hong, Donsub Rim, Noseong Park, Kookjin Lee
However, parameterization of dynamics using a neural network makes it difficult for humans to identify causal structures in the data.
no code implementations • 1 Sep 2022 • Chen Gong, Zhenzhe Zheng, Yunfeng Shao, Bingshuai Li, Fan Wu, Guihai Chen
We first define a new data valuation metric for data evaluation and selection in FL with theoretical guarantees for speeding up model convergence and enhancing final model accuracy, simultaneously.
1 code implementation • 25 Jul 2022 • Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li
We first explore different statistical information which can discriminate the private training distribution from other distributions.
1 code implementation • 19 Jul 2022 • Niraj Gupta, Eric J. Roberts, Song Pang, C. Shan Xu, Harald F. Hess, Fan Wu, Abby Dernburg, Danielle Jorgens, Petrus H. Zwart, Vignesh Kasinath
Lastly, we highlight specific aspects of the model that can be optimized for its broad application to other volumetric imaging data as well as in situ cryo-electron tomography.
no code implementations • 26 Jun 2022 • Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero, Farhat Lamia Barsha, Shahriar Sobhan, Md Abdullah Khan, Michael Whitman, Alfredo Cuzzocreak, Dan Lo, Akond Rahman, Fan Wu
The comprehension of this synthesis shall help researchers for further research on malware detection and prevention using AI.
no code implementations • 30 May 2022 • Chengfei Lv, Chaoyue Niu, Renjie Gu, Xiaotang Jiang, Zhaode Wang, Bin Liu, Ziqi Wu, Qiulin Yao, Congyu Huang, Panos Huang, Tao Huang, Hui Shu, Jinde Song, Bin Zou, Peng Lan, Guohuan Xu, Fei Wu, Shaojie Tang, Fan Wu, Guihai Chen
Walle consists of a deployment platform, distributing ML tasks to billion-scale devices in time; a data pipeline, efficiently preparing task input; and a compute container, providing a cross-platform and high-performance execution environment, while facilitating daily task iteration.
1 code implementation • ICLR 2022 • Fan Wu, Linyi Li, Chejian Xu, huan zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li
We leverage COPA to certify three RL environments trained with different algorithms and conclude: (1) The proposed robust aggregation protocols such as temporal aggregation can significantly improve the certifications; (2) Our certification for both per-state action stability and cumulative reward bound are efficient and tight; (3) The certification for different training algorithms and environments are different, implying their intrinsic robustness properties.
no code implementations • 9 Feb 2022 • Kang Wei, Jun Li, Chuan Ma, Ming Ding, Sha Wei, Fan Wu, Guihai Chen, Thilina Ranbaduge
As a special architecture in FL, vertical FL (VFL) is capable of constructing a hyper ML model by embracing sub-models from different clients.
no code implementations • 24 Jan 2022 • Renjie Gu, Chaoyue Niu, Yikai Yan, Fan Wu, Shaojie Tang, Rongfeng Jia, Chengfei Lyu, Guihai Chen
Data heterogeneity is an intrinsic property of recommender systems, making models trained over the global data on the cloud, which is the mainstream in industry, non-optimal to each individual user's local data distribution.
no code implementations • IEEE International Conference on Bioinformatics and Biomedicine 2022 • Lei Xu, Jianhong Cheng, Jin Liu, Hulin Kuang, Fan Wu, Jianxin Wang
The two types of features are entered into the parallel encoders paths with residual attention for extracting feature representation, and then fused into a channel-spatial attention module to adaptively focus on the important features between channel and spatial part for the classification task.
Ranked #5 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
1 code implementation • 16 Sep 2021 • Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lv, Yanghe Feng, Guihai Chen
We theoretically proved the convergence rate of FedSubAvg by deriving an upper bound under a new metric called the element-wise gradient norm.
1 code implementation • 25 Aug 2021 • Chao Hu, Fan Wu, Weijie Wu, Weibin Qiu, Shengxin Lai
With models trained on the normal data, the reconstruction errors of anomalous scenes are usually much larger than those of normal ones.
no code implementations • 24 Aug 2021 • Hongtao Lv, Zhenzhe Zheng, Tie Luo, Fan Wu, Shaojie Tang, Lifeng Hua, Rongfei Jia, Chengfei Lv
We evaluate the performance of PCA and Fed-PCA using the MNIST dataset and a large industrial product recommendation dataset.
no code implementations • 14 Aug 2021 • Fan Wu, Yunhui Long, Ce Zhang, Bo Li
We show that these DP GCN mechanisms are not always resilient against LinkTeller empirically under mild privacy guarantees ($\varepsilon>5$).
no code implementations • 22 Jul 2021 • Fan Wu, Min Gao, Junliang Yu, Zongwei Wang, Kecheng Liu, Xu Wange
To explore the robustness of recommender systems, researchers have proposed various shilling attack models and analyzed their adverse effects.
2 code implementations • ICLR 2022 • Fan Wu, Linyi Li, Zijian Huang, Yevgeniy Vorobeychik, Ding Zhao, Bo Li
We then develop a local smoothing algorithm for policies derived from Q-functions to guarantee the robustness of actions taken along the trajectory; we also develop a global smoothing algorithm for certifying the lower bound of a finite-horizon cumulative reward, as well as a novel local smoothing algorithm to perform adaptive search in order to obtain tighter reward certification.
1 code implementation • 11 Jun 2021 • Chao Wen, Miao Xu, Zhilin Zhang, Zhenzhe Zheng, Yuhui Wang, Xiangyu Liu, Yu Rong, Dong Xie, Xiaoyang Tan, Chuan Yu, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu, Bo Zheng
Third, to deploy MAAB in the large-scale advertising system with millions of advertisers, we propose a mean-field approach.
no code implementations • 7 Jun 2021 • Xiangyu Liu, Chuan Yu, Zhilin Zhang, Zhenzhe Zheng, Yu Rong, Hongtao Lv, Da Huo, YiQing Wang, Dagui Chen, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu
In e-commerce advertising, it is crucial to jointly consider various performance metrics, e. g., user experience, advertiser utility, and platform revenue.
1 code implementation • NeurIPS 2021 • Fan Wu, Patrick Rebeschini
We study discrete-time mirror descent applied to the unregularized empirical risk in matrix sensing.
no code implementations • 25 May 2021 • Liyi Guo, Junqi Jin, Haoqi Zhang, Zhenzhe Zheng, Zhiye Yang, Zhizhuang Xing, Fei Pan, Lvyin Niu, Fan Wu, Haiyang Xu, Chuan Yu, Yuning Jiang, Xiaoqiang Zhu
To achieve this goal, the advertising platform needs to identify the advertiser's optimization objectives, and then recommend the corresponding strategies to fulfill the objectives.
1 code implementation • 8 May 2021 • Fan Wu, Patrick Rebeschini
This paper studies early-stopped mirror descent applied to noisy sparse phase retrieval, which is the problem of recovering a $k$-sparse signal $\mathbf{x}^\star\in\mathbb{R}^n$ from a set of quadratic Gaussian measurements corrupted by sub-exponential noise.
no code implementations • 15 Apr 2021 • Yuben Qu, Haipeng Dai, Yan Zhuang, Jiafa Chen, Chao Dong, Fan Wu, Song Guo
Unmanned aerial vehicles (UAVs), or say drones, are envisioned to support extensive applications in next-generation wireless networks in both civil and military fields.
1 code implementation • 20 Mar 2021 • Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
In this paper, we aim to explore the power of generative models and gradient sparsity, and propose a scalable privacy-preserving generative model DATALENS.
no code implementations • 14 Jan 2021 • Yi Su, Wenhao fan, Yuan'an Liu, Fan Wu
In this paper, we formulate a distributed mechanism to analyze the interaction between OSPs and IoT MDs in the MEC enabled edge-cloud system by appling multi-leader multi-follower two-tier Stackelberg game theory.
Edge-computing
Computer Science and Game Theory
no code implementations • 11 Jan 2021 • Wenhao fan, Liang Zhao, Jiayang Wang, Ye Chen, Fan Wu, Yuan'an Liu
At present, the main problem of existing research works on Android malware family classification lies in that the extracted features are inadequate to represent the common behavior characteristics of the malware in malicious families, and leveraging a single classifier or a static ensemble classifier is restricted to further improve the accuracy of classification.
Malware Detection
Cryptography and Security
no code implementations • 22 Dec 2020 • Hamed Pourbeyram, Pavel Sidorenko, Fan Wu, Logan Wright, Demetrios Christodoulides, Frank Wise
Recent years have witnessed a resurgence of interest in nonlinear multimode optical systems where a host of intriguing effects have been observed that are impossible in single-mode settings.
Optics
no code implementations • 20 Dec 2020 • Yihao Xue, Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Chengfei Lv, Fan Wu, Guihai Chen
Federated learning allows mobile clients to jointly train a global model without sending their private data to a central server.
no code implementations • 5 Dec 2020 • Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai
In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue.
no code implementations • 8 Nov 2020 • Taha Ameen ur Rahman, Alton S. Barbehenn, Xinan Chen, Hassan Dbouk, James A. Douglas, Yuncong Geng, Ian George, John B. Harvill, Sung Woo Jeon, Kartik K. Kansal, Kiwook Lee, Kelly A. Levick, Bochao Li, Ziyue Li, Yashaswini Murthy, Adarsh Muthuveeru-Subramaniam, S. Yagiz Olmez, Matthew J. Tomei, Tanya Veeravalli, Xuechao Wang, Eric A. Wayman, Fan Wu, Peng Xu, Shen Yan, Heling Zhang, Yibo Zhang, Yifan Zhang, Yibo Zhao, Sourya Basu, Lav R. Varshney
Many information sources are not just sequences of distinguishable symbols but rather have invariances governed by alternative counting paradigms such as permutations, combinations, and partitions.
Information Theory Information Theory
1 code implementation • NeurIPS 2020 • Fan Wu, Patrick Rebeschini
We analyze continuous-time mirror descent applied to sparse phase retrieval, which is the problem of recovering sparse signals from a set of magnitude-only measurements.
no code implementations • 16 Sep 2020 • Fan Fang, Carmine Ventre, Lingbo Li, Leslie Kanthan, Fan Wu, Michail Basios
Feature importance aims at measuring how crucial each input feature is for model prediction.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+3
no code implementations • 10 Sep 2020 • Yuxi Huan, Fan Wu, Michail Basios, Leslie Kanthan, Lingbo Li, Baowen Xu
In this paper, we introduce an intelligent evolutionary optimisation algorithm which applies machine learning technique to the traditional evolutionary algorithm to accelerate the overall optimisation process of tuning machine learning models in classification problems.
no code implementations • 20 Aug 2020 • Liyi Guo, Rui Lu, Haoqi Zhang, Junqi Jin, Zhenzhe Zheng, Fan Wu, Jin Li, Haiyang Xu, Han Li, Wenkai Lu, Jian Xu, Kun Gai
For e-commerce platforms such as Taobao and Amazon, advertisers play an important role in the entire digital ecosystem: their behaviors explicitly influence users' browsing and shopping experience; more importantly, advertiser's expenditure on advertising constitutes a primary source of platform revenue.
no code implementations • 5 Aug 2020 • Yijiang Lian, Zhenjun You, Fan Wu, Wenqiang Liu, Jing Jia
Firstly, we devise a Trie-based translation model to make a data increment.
no code implementations • 26 Jul 2020 • Yuben Qu, Chao Dong, Jianchao Zheng, Qihui Wu, Yun Shen, Fan Wu, Alagan Anpalagan
Ubiquitous intelligence has been widely recognized as a critical vision of the future sixth generation (6G) networks, which implies the intelligence over the whole network from the core to the edge including end devices.
Networking and Internet Architecture
2 code implementations • 1 Jun 2020 • Fan Wu, Patrick Rebeschini
We consider the problem of reconstructing an $n$-dimensional $k$-sparse signal from a set of noiseless magnitude-only measurements.
no code implementations • 25 Mar 2020 • Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu
This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e. g., cryptocurrency trading systems, bubble and extreme conditions, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
no code implementations • JOURNAL OF COMMUNICATIONS AND NETWORKS 2020 • Wenli Ning, Xiaoyan Huang, Kun Yang, Fan Wu, and Supeng Leng
In cognitive radio (CR) networks, fast and accurate spectrum sensing plays a fundamental role in achieving high spectral efficiency.
no code implementations • 18 Feb 2020 • Yucheng Ding, Chaoyue Niu, Yikai Yan, Zhenzhe Zheng, Fan Wu, Guihai Chen, Shaojie Tang, Rongfei Jia
We consider practical data characteristics underlying federated learning, where unbalanced and non-i. i. d.
1 code implementation • 18 Feb 2020 • Yikai Yan, Chaoyue Niu, Yucheng Ding, Zhenzhe Zheng, Fan Wu, Guihai Chen, Shaojie Tang, Zhihua Wu
In this work, we consider a practical and ubiquitous issue when deploying federated learning in mobile environments: intermittent client availability, where the set of eligible clients may change during the training process.
no code implementations • 9 Feb 2020 • Fan Fang, Waichung Chung, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, Fan Wu
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world.
1 code implementation • 28 Nov 2019 • Chaoyue Niu, Zhenzhe Zheng, Fan Wu, Shaojie Tang, Guihai Chen
The analysis and evaluation results reveal that our proposed pricing mechanism incurs low practical regret, online latency, and memory overhead, and also demonstrate that the existence of reserve price can mitigate the cold-start problem in a posted price mechanism, and thus can reduce the cumulative regret.
1 code implementation • CVPR 2021 • Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song
Quantifying the importance of each training point to a learning task is a fundamental problem in machine learning and the estimated importance scores have been leveraged to guide a range of data workflows such as data summarization and domain adaption.
3 code implementations • 9 Nov 2019 • Iddo Drori, Darshan Thaker, Arjun Srivatsa, Daniel Jeong, Yueqi Wang, Linyong Nan, Fan Wu, Dimitri Leggas, Jinhao Lei, Weiyi Lu, Weilong Fu, Yuan Gao, Sashank Karri, Anand Kannan, Antonio Moretti, Mohammed AlQuraishi, Chen Keasar, Itsik Pe'er
Our dataset consists of amino acid sequences, Q8 secondary structures, position specific scoring matrices, multiple sequence alignment co-evolutionary features, backbone atom distance matrices, torsion angles, and 3D coordinates.
1 code implementation • 6 Nov 2019 • Chaoyue Niu, Fan Wu, Shaojie Tang, Lifeng Hua, Rongfei Jia, Chengfei Lv, Zhihua Wu, Guihai Chen
Nevertheless, the "position" of a client's truly required submodel corresponds to her private data, and its disclosure to the cloud server during interactions inevitably breaks the tenet of federated learning.
no code implementations • 10 Oct 2019 • Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang
Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.
1 code implementation • 10 Oct 2019 • Samuel Sharpe, Jin Yan, Fan Wu, Iddo Drori
Given the complete query, we fine tune a BERT embedding for estimating probabilities of a broad set of instances.
no code implementations • 18 Sep 2019 • Renjie Gu, Chaoyue Niu, Fan Wu, Guihai Chen, Chun Hu, Chengfei Lyu, Zhihua Wu
Another benefit is the bandwidth reduction because various kinds of local data can be involved in the training process without being uploaded.
1 code implementation • 3 Jun 2019 • Zhen Zhang, Fan Wu, Wee Sun Lee
Most of the successful deep neural network architectures are structured, often consisting of elements like convolutional neural networks and gated recurrent neural networks.
1 code implementation • 25 Mar 2019 • Pengfei Yao, Zheng Fang, Fan Wu, Yao Feng, Jiwei Li
Recovering 3D human body shape and pose from 2D images is a challenging task due to high complexity and flexibility of human body, and relatively less 3D labeled data.
no code implementations • 29 Dec 2018 • Donghan Feng, Fan Wu, Yun Zhou, Usama Rahman, Xiaojin Zhao, Chen Fang
A multi-agent-based rolling optimization method for EDS restoration scheduling is proposed in this paper.
Signal Processing
no code implementations • 22 Jun 2018 • Fan Wu, Kai Tian, Jihong Guan, Shuigeng Zhou
In this paper, we propose an end-to-end framework, called Global Semantic Consistency Network (GSC-Net for short), which makes complete use of the semantic information of both seen and unseen classes, to support effective zero-shot learning.
4 code implementations • ECCV 2018 • Yao Feng, Fan Wu, Xiaohu Shao, Yan-Feng Wang, Xi Zhou
We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment.
Ranked #1 on
3D Face Reconstruction
on Florence
no code implementations • 22 Mar 2017 • Fan Wu, Zhongwen Xu, Yi Yang
We propose an end-to-end approach to the natural language object retrieval task, which localizes an object within an image according to a natural language description, i. e., referring expression.