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 • 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 • NeurIPS 2020 • 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.
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.
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.
2 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.