no code implementations • ACL 2022 • Kunyuan Pang, Haoyu Zhang, Jie zhou, Ting Wang
In this work, we propose a clustering-based loss correction framework named Feature Cluster Loss Correction (FCLC), to address these two problems.
no code implementations • Findings (EMNLP) 2021 • Yi Feng, Ting Wang, Chuanyi Li, Vincent Ng, Jidong Ge, Bin Luo, Yucheng Hu, Xiaopeng Zhang
User targeting is an essential task in the modern advertising industry: given a package of ads for a particular category of products (e. g., green tea), identify the online users to whom the ad package should be targeted.
no code implementations • 28 May 2024 • Ting Wang, Zipei Yan, Jizhou Li, XiLe Zhao, Chao Wang, Michael Ng
This approach enables us to harness both the low rankness from the matrix factorization and the continuity from neural representation in a self-supervised manner.
no code implementations • 8 May 2024 • Pengyu Zhang, Yingjie Liu, Yingbo Zhou, Xiao Du, Xian Wei, Ting Wang, Mingsong Chen
Comprehensive experimental results obtained from simulation- and real test-bed-based platforms show that our federated foresight-pruning method not only preserves the ability of the dense model with a memory reduction up to 9x but also boosts the performance of the vanilla BP-Free method with dramatically fewer FLOPs.
1 code implementation • 16 Apr 2024 • Pancheng Wang, Shasha Li, Dong Li, Kehan Long, Jintao Tang, Ting Wang
Our insights are twofold: Firstly, summary candidates can provide instructive information from both positive and negative perspectives, and secondly, selecting higher-quality candidates from multiple options contributes to producing better summaries.
no code implementations • 24 Mar 2024 • Hideki Nishizawa, Giacomo Borraccini, Takeo Sasai, Yue-Kai Huang, Toru Mano, Kazuya Anazawa, Masatoshi Namiki, Soichiroh Usui, Tatsuya Matsumura, Yoshiaki Sone, Zehao Wang, Seiji Okamoto, Takeru Inoue, Ezra Ip, Andrea D'Amico, Tingjun Chen, Vittorio Curri, Ting Wang, Koji Asahi, Koichi Takasugi
We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario.
1 code implementation • 4 Mar 2024 • Kehan Long, Shasha Li, Pancheng Wang, Chenlong Bao, Jintao Tang, Ting Wang
To help improve citations of full papers, we first define a novel task of Recommending Missed Citations Identified by Reviewers (RMC) and construct a corresponding expert-labeled dataset called CitationR.
no code implementations • 20 Feb 2024 • Nan Xiao, Bo Lang, Ting Wang, Yikai Chen
Cyber threat intelligence (CTI), which involves analyzing multisource heterogeneous data from APTs, plays an important role in APT actor attribution.
no code implementations • 16 Feb 2024 • Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma
Correspondingly, we propose a novel VQAttack model, which can iteratively generate both image and text perturbations with the designed modules: the large language model (LLM)-enhanced image attack and the cross-modal joint attack module.
no code implementations • 30 Jan 2024 • Guangke Chen, Yedi Zhang, Fu Song, Ting Wang, Xiaoning Du, Yang Liu
To improve the imperceptibility of perturbations, we refine a psychoacoustic model-based loss with the backing track as an additional masker, a unique accompanying element for singing voices compared to ordinary speech voices.
1 code implementation • 20 Jan 2024 • Suhan Cui, Jiaqi Wang, Yuan Zhong, Han Liu, Ting Wang, Fenglong Ma
The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improving healthcare services through deep learning techniques.
no code implementations • 26 Dec 2023 • Panlong Wu, Kangshuo Li, Ting Wang, Fangxin Wang
In this paper, we propose a novel two-stage federated learning algorithm called FedMS.
no code implementations • 15 Dec 2023 • Xiao Du, Yutong Ye, Pengyu Zhang, Yaning Yang, Mingsong Chen, Ting Wang
To this end, in this paper, we propose a novel MARL algorithm named Situation-Dependent Causal Influence-Based Cooperative Multi-agent Reinforcement Learning (SCIC), which incorporates a novel Intrinsic reward mechanism based on a new cooperation criterion measured by situation-dependent causal influence among agents.
no code implementations • 14 Dec 2023 • Changjiang Li, Ren Pang, Bochuan Cao, Zhaohan Xi, Jinghui Chen, Shouling Ji, Ting Wang
Recent studies have shown that contrastive learning, like supervised learning, is highly vulnerable to backdoor attacks wherein malicious functions are injected into target models, only to be activated by specific triggers.
no code implementations • 8 Dec 2023 • Jiacheng Liang, Ren Pang, Changjiang Li, Ting Wang
Model extraction (ME) attacks represent one major threat to Machine-Learning-as-a-Service (MLaaS) platforms by ``stealing'' the functionality of confidential machine-learning models through querying black-box APIs.
no code implementations • 6 Dec 2023 • Ting Wang, Keith Stelter, Jenn Floyd, Thomas O'Neill, Nathaniel Hendrix, Andrew Bazemore, Kevin Rode, Warren Newton
In testing industry, precise item categorization is pivotal to align exam questions with the designated content domains outlined in the assessment blueprint.
no code implementations • 29 Nov 2023 • Lujia Shen, Yuwen Pu, Shouling Ji, Changjiang Li, Xuhong Zhang, Chunpeng Ge, Ting Wang
Extensive experiments demonstrate that dynamic attention significantly mitigates the impact of adversarial attacks, improving up to 33\% better performance than previous methods against widely-used adversarial attacks.
no code implementations • 14 Nov 2023 • Ting Wang, Weidong Chen, Yuanhe Tian, Yan Song, Zhendong Mao
Having the difficulty of solving the semantic gap between images and texts for the image captioning task, conventional studies in this area paid some attention to treating semantic concepts as a bridge between the two modalities and improved captioning performance accordingly.
no code implementations • 11 Nov 2023 • Xubo Yang, Jian Gao, Ting Wang, Yaozhen He
Individuals in the learning style use the Levy flight search strategy to learn from the best performer and form the closest relationships.
1 code implementation • NeurIPS 2023 • Bochuan Cao, Changjiang Li, Ting Wang, Jinyuan Jia, Bo Li, Jinghui Chen
IMPRESS is based on the key observation that imperceptible perturbations could lead to a perceptible inconsistency between the original image and the diffusion-reconstructed image, which can be used to devise a new optimization strategy for purifying the image, which may weaken the protection of the original image from unauthorized data usage (e. g., style mimicking, malicious editing).
1 code implementation • NeurIPS 2023 • Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma
In this paper, we aim to investigate a new yet practical task to craft image and text perturbations using pre-trained VL models to attack black-box fine-tuned models on different downstream tasks.
no code implementations • 4 Oct 2023 • Yuan Zhong, Suhan Cui, Jiaqi Wang, Xiaochen Wang, Ziyi Yin, Yaqing Wang, Houping Xiao, Mengdi Huai, Ting Wang, Fenglong Ma
Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in the future using their historical Electronic Health Records (EHR).
no code implementations • 1 Oct 2023 • Lauren Hong, Ting Wang
Parameter-efficient fine-tuning (PEFT) enables efficient adaptation of pre-trained language models (PLMs) to specific tasks.
1 code implementation • 25 Sep 2023 • Tianyu Du, Luca Melis, Ting Wang
We present ReMasker, a new method of imputing missing values in tabular data by extending the masked autoencoding framework.
no code implementations • 14 Sep 2023 • Hideki Nishizawa, Toru Mano, Thomas Ferreira de Lima, Yue-Kai Huang, Zehao Wang, Wataru Ishida, Masahisa Kawashima, Ezra Ip, Andrea D'Amico, Seiji Okamoto, Takeru Inoue, Kazuya Anazawa, Vittorio Curri, Gil Zussman, Daniel Kilper, Tingjun Chen, Ting Wang, Koji Asahi, Koichi Takasugi
Then, using field fibers deployed in the NSF COSMOS testbed (deployed in an urban area), a Linux-based transmission device software architecture, and coherent transceivers with different optical frequency ranges, modulators, and modulation formats, the fast WDM provisioning of an optical path was completed within 6 minutes (with a Q-factor error of about 0. 7 dB).
no code implementations • 25 Aug 2023 • Jiali Wang, Yuning Jiang, Xin Liu, Ting Wang, Yuanming Shi
In this context, we propose a customized federated linear bandits scheme, where each device transmits an analog signal, and the server receives a superposition of these signals distorted by channel noise.
no code implementations • 17 Aug 2023 • Junkai Qian, Yuning Jiang, Xin Liu, Qing Wang, Ting Wang, Yuanming Shi, Wei Chen
To effectively learn the optimal EV charging control strategy, a federated deep reinforcement learning algorithm named FedSAC is further proposed.
no code implementations • 11 Aug 2023 • Ken Power, Shailendra Deva, Ting Wang, Julius Li, Ciarán Eising
Computing platforms in autonomous vehicles record large amounts of data from many sensors, process the data through machine learning models, and make decisions to ensure the vehicle's safe operation.
no code implementations • 8 Aug 2023 • Ting Wang, Xiaotong Wu, Jizhou Li, Chao Wang
X-ray microspectroscopic techniques are essential for studying morphological and chemical changes in materials, providing high-resolution structural and spectroscopic information.
no code implementations • 11 Jul 2023 • Chunxi Guo, Zhiliang Tian, Jintao Tang, Shasha Li, Zhihua Wen, Kaixuan Wang, Ting Wang
Prompt learning with large language models (LLMs) has emerged as a recent approach, which designs prompts to lead LLMs to understand the input question and generate the corresponding SQL.
1 code implementation • 20 Jun 2023 • Yongzhu Miao, Shasha Li, Jintao Tang, Ting Wang
We evaluate the effectiveness of MuDPT on few-shot vision recognition and out-of-domain generalization tasks.
no code implementations • 10 May 2023 • Chengxian Zhang, Jintao Tang, Ting Wang, Shasha Li
There is evidence that address matching plays a crucial role in many areas such as express delivery, online shopping and so on.
1 code implementation • ICASSP 2023 • Wing W Y. Ng, Peixin Zheng, Ting Wang, Jianjun Zhang, Yinhao Liang, Hui Zhou, Dan Liang, Guangming Li, Xinhua Wei
Acute appendicitis (AA) is one of the most prevalent surgical acute abdominal condition diseases.
1 code implementation • 3 May 2023 • Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Xiapu Luo, Xusheng Xiao, Fenglong Ma, Ting Wang
Knowledge graph reasoning (KGR) -- answering complex logical queries over large knowledge graphs -- represents an important artificial intelligence task, entailing a range of applications (e. g., cyber threat hunting).
no code implementations • 30 Apr 2023 • Jiali Wang, Yijie Mao, Ting Wang, Yuanming Shi
We rigorously develop an energy consumption model for the local training at devices through the use of QNNs and communication models over Cloud-RAN.
no code implementations • 26 Apr 2023 • Chunxi Guo, Zhiliang Tian, Jintao Tang, Pancheng Wang, Zhihua Wen, Kang Yang, Ting Wang
Text-to-SQL is a task that converts a natural language question into a structured query language (SQL) to retrieve information from a database.
no code implementations • 21 Mar 2023 • Brady Lund, Ting Wang, Nishith Reddy Mannuru, Bing Nie, Somipam Shimray, Ziang Wang
Potential ethical issues that could arise with the emergence of large language models like GPT-3, the underlying technology behind ChatGPT, and its usage by academics and researchers, are discussed and situated within the context of broader advancements in artificial intelligence, machine learning, and natural language processing for research and scholarly publishing.
1 code implementation • 28 Feb 2023 • Chong Fu, Xuhong Zhang, Shouling Ji, Ting Wang, Peng Lin, Yanghe Feng, Jianwei Yin
Thus, in this paper, we propose FreeEagle, the first data-free backdoor detection method that can effectively detect complex backdoor attacks on deep neural networks, without relying on the access to any clean samples or samples with the trigger.
no code implementations • 21 Feb 2023 • Yuan Sun, Qiurong Song, Xinning Gui, Fenglong Ma, Ting Wang
Automated machine learning (AutoML) is envisioned to make ML techniques accessible to ordinary users.
no code implementations • 11 Jan 2023 • Ting Wang, Zongkai Wu, Feiyu Yao, Donglin Wang
First, we propose an Environment Representation Graph (ERG) through object detection to express the environment in semantic level.
no code implementations • 1 Dec 2022 • Pengyu Qiu, Xuhong Zhang, Shouling Ji, Chong Fu, Xing Yang, Ting Wang
Our work shows that hashing is a promising solution to counter data reconstruction attacks.
no code implementations • 1 Dec 2022 • Pengyu Qiu, Xuhong Zhang, Shouling Ji, Changjiang Li, Yuwen Pu, Xing Yang, Ting Wang
Vertical federated learning (VFL) is an emerging paradigm that enables collaborators to build machine learning models together in a distributed fashion.
1 code implementation • 14 Nov 2022 • Jie Wang, Yuzhou Peng, Xiaodong Yang, Ting Wang, YanMing Zhang
The SportsMOT dataset aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer.
no code implementations • 21 Oct 2022 • Ren Pang, Changjiang Li, Zhaohan Xi, Shouling Ji, Ting Wang
This paper asks the intriguing question: is it possible to exploit neural architecture search (NAS) as a new attack vector to launch previously improbable attacks?
3 code implementations • ICCV 2023 • Changjiang Li, Ren Pang, Zhaohan Xi, Tianyu Du, Shouling Ji, Yuan YAO, Ting Wang
As a new paradigm in machine learning, self-supervised learning (SSL) is capable of learning high-quality representations of complex data without relying on labels.
2 code implementations • USENIX Security 22 2022 • Chong Fu, Xuhong Zhang, Shouling Ji, Jinyin Chen, Jingzheng Wu, Shanqing Guo, Jun Zhou, Alex X. Liu, Ting Wang
However, we discover that the bottom model structure and the gradient update mechanism of VFL can be exploited by a malicious participant to gain the power to infer the privately owned labels.
no code implementations • 27 Sep 2022 • Zhaohan Xi, Ren Pang, Changjiang Li, Tianyu Du, Shouling Ji, Fenglong Ma, Ting Wang
(ii) It supports complex logical queries with varying relation and view constraints (e. g., with complex topology and/or from multiple views); (iii) It scales up to KGs of large sizes (e. g., millions of facts) and fine-granular views (e. g., dozens of views); (iv) It generalizes to query structures and KG views that are unobserved during training.
1 code implementation • COLING 2022 • Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, Ting Wang
Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers.
no code implementations • 5 Sep 2022 • Yuyou Gan, Yuhao Mao, Xuhong Zhang, Shouling Ji, Yuwen Pu, Meng Han, Jianwei Yin, Ting Wang
Experiment results show that the MeTFA-smoothed explanation can significantly increase the robust faithfulness.
no code implementations • 13 Aug 2022 • Tong Wang, Yuan YAO, Feng Xu, Miao Xu, Shengwei An, Ting Wang
Existing defenses are mainly built upon the observation that the backdoor trigger is usually of small size or affects the activation of only a few neurons.
1 code implementation • 24 May 2022 • Zhiwei Ling, Zhihao Yue, Jun Xia, Ming Hu, Ting Wang, Mingsong Chen
Along with the popularity of Artificial Intelligence (AI) and Internet-of-Things (IoT), Federated Learning (FL) has attracted steadily increasing attentions as a promising distributed machine learning paradigm, which enables the training of a central model on for numerous decentralized devices without exposing their privacy.
no code implementations • 23 May 2022 • Zhi Zeng, Ting Wang
In this method, a hierarchical unsupervised neural network is constructed to estimate the marginal distribution function and the Copula function by solving differential equations.
no code implementations • 13 May 2022 • Yisheng Song, Ting Wang, Subrota K Mondal, Jyoti Prakash Sahoo
Few-shot learning (FSL) has emerged as an effective learning method and shows great potential.
1 code implementation • 9 May 2022 • Zhihao Yue, Jun Xia, Zhiwei Ling, Ming Hu, Ting Wang, Xian Wei, Mingsong Chen
Due to the popularity of Artificial Intelligence (AI) techniques, we are witnessing an increasing number of backdoor injection attacks that are designed to maliciously threaten Deep Neural Networks (DNNs) causing misclassification.
1 code implementation • 21 Apr 2022 • Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen
Due to the prosperity of Artificial Intelligence (AI) techniques, more and more backdoors are designed by adversaries to attack Deep Neural Networks (DNNs). Although the state-of-the-art method Neural Attention Distillation (NAD) can effectively erase backdoor triggers from DNNs, it still suffers from non-negligible Attack Success Rate (ASR) together with lowered classification ACCuracy (ACC), since NAD focuses on backdoor defense using attention features (i. e., attention maps) of the same order.
no code implementations • 7 Apr 2022 • Yuhao Mao, Chong Fu, Saizhuo Wang, Shouling Ji, Xuhong Zhang, Zhenguang Liu, Jun Zhou, Alex X. Liu, Raheem Beyah, Ting Wang
To bridge this critical gap, we conduct the first large-scale systematic empirical study of transfer attacks against major cloud-based MLaaS platforms, taking the components of a real transfer attack into account.
1 code implementation • 29 Mar 2022 • Peng Yang, Yuning Jiang, Ting Wang, Yong Zhou, Yuanming Shi, Colin N. Jones
To address this issue, in this paper, we instead propose a novel over-the-air second-order federated optimization algorithm to simultaneously reduce the communication rounds and enable low-latency global model aggregation.
no code implementations • 17 Mar 2022 • Fuzhou Gong, Ting Wang
In this paper, we propose and study a novel continuous-time model, based on the well-known constant elasticity of variance (CEV) model, to describe the asset price process.
no code implementations • 28 Feb 2022 • Bo Li, Ting Wang, Peng Yang, Mingsong Chen, Shui Yu, Mounir Hamdi
To support the needs of ever-growing cloud-based services, the number of servers and network devices in data centers is increasing exponentially, which in turn results in high complexities and difficulties in network optimization.
no code implementations • 22 Feb 2022 • Changjiang Li, Li Wang, Shouling Ji, Xuhong Zhang, Zhaohan Xi, Shanqing Guo, Ting Wang
Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendors.
no code implementations • 29 Jan 2022 • Tian Liu, Jiahao Ding, Ting Wang, Miao Pan, Mingsong Chen
However, since our grouping method is based on the similarity of extracted feature maps from IoT devices, it may incur additional risks of privacy exposure.
no code implementations • 24 Dec 2021 • Haibo Jin, Ruoxi Chen, Jinyin Chen, Yao Cheng, Chong Fu, Ting Wang, Yue Yu, Zhaoyan Ming
Existing DNN testing methods are mainly designed to find incorrect corner case behaviors in adversarial settings but fail to discover the backdoors crafted by strong trojan attacks.
no code implementations • 11 Dec 2021 • Muchao Ye, Junyu Luo, Guanjie Zheng, Cao Xiao, Ting Wang, Fenglong Ma
Deep neural networks (DNNs) have been broadly adopted in health risk prediction to provide healthcare diagnoses and treatments.
no code implementations • 24 Nov 2021 • Shiqi Liu, Lu Wang, Jie Lian, Ting Chen, Cong Liu, Xuchen Zhan, Jintao Lu, Jie Liu, Ting Wang, Dong Geng, Hongwei Duan, Yuze Tian
Relative radiometric normalization(RRN) of different satellite images of the same terrain is necessary for change detection, object classification/segmentation, and map-making tasks.
1 code implementation • 22 Nov 2021 • Tong Wang, Yuan YAO, Feng Xu, Shengwei An, Hanghang Tong, Ting Wang
We also evaluate FTROJAN against state-of-the-art defenses as well as several adaptive defenses that are designed on the frequency domain.
1 code implementation • 30 Oct 2021 • Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, Ting Wang
However, a pre-trained model with backdoor can be a severe threat to the applications.
1 code implementation • 12 Oct 2021 • Ren Pang, Zhaohan Xi, Shouling Ji, Xiapu Luo, Ting Wang
Neural Architecture Search (NAS) represents an emerging machine learning (ML) paradigm that automatically searches for models tailored to given tasks, which greatly simplifies the development of ML systems and propels the trend of ML democratization.
no code implementations • 25 Jan 2021 • Min Fu, Yong Zhou, Yuanming Shi, Ting Wang, Wei Chen
Over-the-air computation (AirComp) provides a promising way to support ultrafast aggregation of distributed data.
Optimize the trajectory of UAV which plays a BS in communication system
no code implementations • 22 Jan 2021 • Xinyang Zhang, Ren Pang, Shouling Ji, Fenglong Ma, Ting Wang
Providing explanations for deep neural networks (DNNs) is essential for their use in domains wherein the interpretability of decisions is a critical prerequisite.
no code implementations • 1 Jan 2021 • Xinyang Zhang, Zheng Zhang, Ting Wang
One intriguing property of deep neural networks (DNNs) is their vulnerability to adversarial perturbations.
1 code implementation • 16 Dec 2020 • Ren Pang, Zheng Zhang, Xiangshan Gao, Zhaohan Xi, Shouling Ji, Peng Cheng, Xiapu Luo, Ting Wang
To bridge this gap, we design and implement TROJANZOO, the first open-source platform for evaluating neural backdoor attacks/defenses in a unified, holistic, and practical manner.
no code implementations • 10 Dec 2020 • Ting Wang, Zongkai Wu, Donglin Wang
In the training phase, we first locate the generalization problem to the visual perception module, and then compare two meta-learning algorithms for better generalization in seen and unseen environments.
1 code implementation • 5 Oct 2020 • Yuwei Li, Shouling Ji, Yuan Chen, Sizhuang Liang, Wei-Han Lee, Yueyao Chen, Chenyang Lyu, Chunming Wu, Raheem Beyah, Peng Cheng, Kangjie Lu, Ting Wang
We hope that our findings can shed light on reliable fuzzing evaluation, so that we can discover promising fuzzing primitives to effectively facilitate fuzzer designs in the future.
Cryptography and Security
1 code implementation • 1 Aug 2020 • Xinyang Zhang, Zheng Zhang, Shouling Ji, Ting Wang
Recent years have witnessed the emergence of a new paradigm of building natural language processing (NLP) systems: general-purpose, pre-trained language models (LMs) are composed with simple downstream models and fine-tuned for a variety of NLP tasks.
2 code implementations • 21 Jun 2020 • Zhaohan Xi, Ren Pang, Shouling Ji, Ting Wang
One intriguing property of deep neural networks (DNNs) is their inherent vulnerability to backdoor attacks -- a trojan model responds to trigger-embedded inputs in a highly predictable manner while functioning normally otherwise.
1 code implementation • 16 Jun 2020 • Ren Pang, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang
Deep neural networks (DNNs) are inherently susceptible to adversarial attacks even under black-box settings, in which the adversary only has query access to the target models.
1 code implementation • 24 Mar 2020 • Ting Wang, Yingjin Ma, Lian Zhao, Jinrong Jiang
In this work, we present an efficient procedure for constructing CI expansions from MPS using the Charm++ parallel programming framework, upon which automatic load balancing and object migration facilities can be employed.
Computational Physics Strongly Correlated Electrons
no code implementations • 24 Mar 2020 • Junfeng Guo, Ting Wang, Cong Liu
Being able to detect and mitigate poisoning attacks, typically categorized into backdoor and adversarial poisoning (AP), is critical in enabling safe adoption of DNNs in many application domains.
1 code implementation • 5 Nov 2019 • Ren Pang, Hua Shen, Xinyang Zhang, Shouling Ji, Yevgeniy Vorobeychik, Xiapu Luo, Alex Liu, Ting Wang
Specifically, (i) we develop a new attack model that jointly optimizes adversarial inputs and poisoned models; (ii) with both analytical and empirical evidence, we reveal that there exist intriguing "mutual reinforcement" effects between the two attack vectors -- leveraging one vector significantly amplifies the effectiveness of the other; (iii) we demonstrate that such effects enable a large design spectrum for the adversary to enhance the existing attacks that exploit both vectors (e. g., backdoor attacks), such as maximizing the attack evasiveness with respect to various detection methods; (iv) finally, we discuss potential countermeasures against such optimized attacks and their technical challenges, pointing to several promising research directions.
no code implementations • ICLR 2019 • Xinyang Zhang, Yifan Huang, Chanh Nguyen, Shouling Ji, Ting Wang
On the possibility side, we show that it is still feasible to construct adversarial training methods to significantly improve the resilience of networks against adversarial inputs over empirical datasets.
no code implementations • 23 Jan 2019 • Tianyu Du, Shouling Ji, Jinfeng Li, Qinchen Gu, Ting Wang, Raheem Beyah
Despite their immense popularity, deep learning-based acoustic systems are inherently vulnerable to adversarial attacks, wherein maliciously crafted audios trigger target systems to misbehave.
Cryptography and Security
1 code implementation • 13 Dec 2018 • Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, Ting Wang
Deep Learning-based Text Understanding (DLTU) is the backbone technique behind various applications, including question answering, machine translation, and text classification.
no code implementations • 3 Dec 2018 • Xinyang Zhang, Ningfei Wang, Hua Shen, Shouling Ji, Xiapu Luo, Ting Wang
The improved interpretability is believed to offer a sense of security by involving human in the decision-making process.
no code implementations • 2 Dec 2018 • Yujie Ji, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang
By empirically studying four deep learning systems (including both individual and ensemble systems) used in skin cancer screening, speech recognition, face verification, and autonomous steering, we show that such attacks are (i) effective - the host systems misbehave on the targeted inputs as desired by the adversary with high probability, (ii) evasive - the malicious models function indistinguishably from their benign counterparts on non-targeted inputs, (iii) elastic - the malicious models remain effective regardless of various system design choices and tuning strategies, and (iv) easy - the adversary needs little prior knowledge about the data used for system tuning or inference.
Cryptography and Security
no code implementations • 1 Aug 2018 • Yujie Ji, Xinyang Zhang, Ting Wang
Deep neural networks (DNNs) are inherently vulnerable to adversarial inputs: such maliciously crafted samples trigger DNNs to misbehave, leading to detrimental consequences for DNN-powered systems.
2 code implementations • 5 Jan 2018 • Xinyang Zhang, Shouling Ji, Ting Wang
Privacy-preserving releasing of complex data (e. g., image, text, audio) represents a long-standing challenge for the data mining research community.
no code implementations • 2 Dec 2017 • Chanh Nguyen, Georgi Georgiev, Yujie Ji, Ting Wang
We believe that this work opens a new direction for designing adversarial input detection methods.
no code implementations • 25 Aug 2017 • Xinyang Zhang, Yujie Ji, Ting Wang
Many of today's machine learning (ML) systems are not built from scratch, but are compositions of an array of {\em modular learning components} (MLCs).
no code implementations • 24 Apr 2017 • Shu Zhang, Hui Yu, Ting Wang, Junyu Dong, Honghai Liu
With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks.
no code implementations • 6 Apr 2017 • Zhe Sun, Ting Wang, Ke Deng, Xiao-Feng Wang, Robert Lafyatis, Ying Ding, Ming Hu, Wei Chen
More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods.
no code implementations • 11 Oct 2016 • Yifan Hou, Pan Zhou, Ting Wang, Li Yu, Yuchong Hu, Dapeng Wu
In this respect, the key challenge is how to realize personalized course recommendation as well as to reduce the computing and storage costs for the tremendous course data.
no code implementations • 22 Aug 2014 • Peilei Liu, Ting Wang
Firstly, we briefly introduce this model in this paper, and then we explain the neural mechanism of language and reasoning with it.
no code implementations • 18 Jul 2014 • Peilei Liu, Ting Wang
Finally, we compare motor system with sensory system.
no code implementations • 25 Jun 2014 • Peilei Liu, Ting Wang
The coding mechanism of sensory memory on the neuron scale is one of the most important questions in neuroscience.
no code implementations • 23 Jun 2014 • Peilei Liu, Ting Wang
This is complementary to existing theories and has provided better explanations for sound localization.
no code implementations • 8 Jun 2014 • Peilei Liu, Ting Wang
Protein-protein interaction extraction is the key precondition of the construction of protein knowledge network, and it is very important for the research in the biomedicine.