no code implementations • 26 Feb 2024 • Isabelle Mohr, Markus Krimmel, Saba Sturua, Mohammad Kalim Akram, Andreas Koukounas, Michael Günther, Georgios Mastrapas, Vinit Ravishankar, Joan Fontanals Martínez, Feng Wang, Qi Liu, Ziniu Yu, Jie Fu, Saahil Ognawala, Susana Guzman, Bo wang, Maximilian Werk, Nan Wang, Han Xiao
We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language.
1 code implementation • 27 Jan 2024 • Zenghui Lin, Xintong Liu, Nan Wang, Ruichen Li, Qingao Liu, Jingying Ma, LiWei Wang, Yan Wang, Shenda Hong
This kind of continuous monitoring, in contrast to the short-term one, collects an extended period of fetal heart data.
1 code implementation • 19 Jan 2024 • Tianyi Zhao, Maoxun Yuan, Feng Jiang, Nan Wang, Xingxing Wei
Specifically, following this perspective, we design a Redundant Spectrum Removal module to coarsely remove interfering information within each modality and a Dynamic Feature Selection module to finely select the desired features for feature fusion.
no code implementations • 7 Jan 2024 • Pengfei Ding, Yan Wang, Guanfeng Liu, Nan Wang, Xiaofang Zhou
To address this challenging problem, we propose a novel Causal OOD Heterogeneous graph Few-shot learning model, namely COHF.
no code implementations • 11 Dec 2023 • Fan Xu, Nan Wang, Hao Wu, Xuezhi Wen, Xibin Zhao, Hai Wan
This detector includes a hybrid filtering module and a local environmental constraint module, the two modules are utilized to solve heterophily and label utilization problem respectively.
no code implementations • 17 Nov 2023 • Fan Xu, Nan Wang, Xuezhi Wen, Meiqi Gao, Chaoqun Guo, Xibin Zhao
Graph anomaly detection plays a crucial role in identifying exceptional instances in graph data that deviate significantly from the majority.
1 code implementation • 30 Oct 2023 • Michael Günther, Jackmin Ong, Isabelle Mohr, Alaeddine Abdessalem, Tanguy Abel, Mohammad Kalim Akram, Susana Guzman, Georgios Mastrapas, Saba Sturua, Bo wang, Maximilian Werk, Nan Wang, Han Xiao
Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information.
1 code implementation • 23 Oct 2023 • Jinyu Li, Xiaokun Pan, Gan Huang, Ziyang Zhang, Nan Wang, Hujun Bao, Guofeng Zhang
In this work, we design a novel visual-inertial odometry (VIO) system called RD-VIO to handle both of these two problems.
no code implementations • 8 Sep 2023 • Weijian Xie, Guanyi Chu, Quanhao Qian, Yihao Yu, Hai Li, Danpeng Chen, Shangjin Zhai, Nan Wang, Hujun Bao, Guofeng Zhang
In this paper, we propose a novel method that integrates a light-weight depth completion network into a sparse SLAM system using a multi-basis depth representation, so that dense mapping can be performed online even on a mobile phone.
1 code implementation • 6 Jun 2023 • Fobo Shi, Peijun Qing, Dong Yang, Nan Wang, Youbo Lei, Haonan Lu, Xiaodong Lin, Duantengchuan Li
To address this issue in prompt engineering, we propose a new and effective approach called Prompt Space.
no code implementations • 3 Jun 2023 • Fan Xu, Nan Wang, Xibin Zhao
To address such problem, we propose an anomaly detection method GALDetector which is combined of global and local information based on observed normal samples.
no code implementations • 2 May 2023 • Jinlong Hu, Yangmin Huang, Nan Wang, Shoubin Dong
In this paper, we focused on pre-training methods with Transformer networks to leverage existing unlabeled data for brain functional network classification.
no code implementations • 6 Apr 2023 • Nan Wang, Xuezhi Wen, Dalin Zhang, Xibin Zhao, Jiahui Ma, Mengxia Luo, Sen Nie, Shi Wu, Jiqiang Liu
APT detection is difficult to detect due to the long-term latency, covert and slow multistage attack patterns of Advanced Persistent Threat (APT).
no code implementations • 15 Mar 2023 • Sicheng Zhou, Nan Wang, LiWei Wang, Ju Sun, Anne Blaes, Hongfang Liu, Rui Zhang
We developed three types of NLP models (i. e., conditional random field, bi-directional long short-term memory and CancerBERT) to extract cancer phenotypes from clinical texts.
no code implementations • 17 Feb 2023 • Gang Hu, Yinglei Teng, Nan Wang, F. Richard Yu
Federated Learning (FL) is a novel distributed machine learning approach to leverage data from Internet of Things (IoT) devices while maintaining data privacy.
no code implementations • 14 Oct 2022 • Nan Wang, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu, Hamed Firooz, Hongning Wang, Shaoliang Nie
However, the bias inherent in user written text, often used for PTG model training, can inadvertently associate different levels of linguistic quality with users' protected attributes.
no code implementations • 4 Jul 2022 • Danpeng Chen, Shuai Wang, Weijian Xie, Shangjin Zhai, Nan Wang, Hujun Bao, Guofeng Zhang
Even if the plane parameters are involved in the optimization, we effectively simplify the back-end map by using planar structures.
1 code implementation • 2 Jun 2022 • Nan Wang, Shaohui Lin, Xiaoxiao Li, Ke Li, Yunhang Shen, Yue Gao, Lizhuang Ma
U-Nets have achieved tremendous success in medical image segmentation.
1 code implementation • 29 Mar 2022 • Zhixue Wang, Yu Zhang, Lin Luo, Nan Wang
This paper proposed a novel anomaly detection (AD) approach of High-speed Train images based on convolutional neural networks and the Vision Transformer.
1 code implementation • 17 Mar 2022 • Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li
To improve fMRI representation learning and classification under a label-efficient setting, we propose a novel and theory-driven self-supervised learning (SSL) framework on GCNs, namely Graph CCA for Temporal self-supervised learning on fMRI analysis GATE.
no code implementations • 24 Jan 2022 • Nan Wang, Hongning Wang, Maryam Karimzadehgan, Branislav Kveton, Craig Boutilier
This problem has been studied extensively in the setting of known objective functions.
no code implementations • 19 Dec 2021 • Liang Peng, Nan Wang, Nicha Dvornek, Xiaofeng Zhu, Xiaoxiao Li
Then we train a global GCN node classifier across institutions using a federated graph learning platform.
no code implementations • 17 Dec 2021 • Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork
Multiclass classification (MCC) is a fundamental machine learning problem of classifying each instance into one of a predefined set of classes.
no code implementations • 1 Nov 2021 • Aobo Yang, Nan Wang, Renqin Cai, Hongbo Deng, Hongning Wang
As recommendation is essentially a comparative (or ranking) process, a good explanation should illustrate to users why an item is believed to be better than another, i. e., comparative explanations about the recommended items.
no code implementations • 26 Oct 2021 • Nan Wang, Lu Lin, Jundong Li, Hongning Wang
In this paper, we propose a principled new way for unbiased graph embedding by learning node embeddings from an underlying bias-free graph, which is not influenced by sensitive node attributes.
no code implementations • 29 Sep 2021 • Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork
We further demonstrate that the most popular MCC architecture in deep learning can be mathematically formulated as a LTR pipeline equivalently, with a specific set of choices in terms of ranking model architecture and loss function.
1 code implementation • COLING 2022 • Nan Wang, Jiwei Li, Yuxian Meng, Xiaofei Sun, Han Qiu, Ziyao Wang, Guoyin Wang, Jun He
We formalize predicate disambiguation as multiple-choice machine reading comprehension, where the descriptions of candidate senses of a given predicate are used as options to select the correct sense.
Ranked #1 on Semantic Role Labeling on CoNLL 2005
no code implementations • 25 Aug 2021 • Sicheng Zhou, LiWei Wang, Nan Wang, Hongfang Liu, Rui Zhang
This data used in the study included 21, 291 breast cancer patients diagnosed from 2010 to 2020, patients' clinical notes and pathology reports were collected from the University of Minnesota Clinical Data Repository (UMN).
1 code implementation • 15 Mar 2021 • Meiyu Huang, Yao Xu, Lixin Qian, Weili Shi, Yaqin Zhang, Wei Bao, Nan Wang, Xuejiao Liu, Xueshuang Xiang
We obtain the SAR patches from SAR satellite GaoFen-3 images and the optical patches from Google Earth images.
no code implementations • 7 Mar 2021 • Nan Wang, Branislav Kveton, Maryam Karimzadehgan
We propose a bandit algorithm that explores purely by randomizing its past observations.
no code implementations • 24 Jan 2021 • Aobo Yang, Nan Wang, Hongbo Deng, Hongning Wang
At training time, the two learning tasks are joined by a latent sentiment vector, which is encoded by the recommendation module and used to make word choices for explanation generation.
1 code implementation • COLING 2020 • Yan Song, Yuanhe Tian, Nan Wang, Fei Xia
For the particular dataset used in this study, we show that high-quality summaries can be generated by extracting two types of utterances, namely, problem statements and treatment recommendations.
no code implementations • 10 Nov 2020 • Xiatian Zhang, Xunshi He, Nan Wang, Rong Chen
For high-dimensional data, there are huge communication costs for distributed GBDT because the communication volume of GBDT is related to the number of features.
no code implementations • 9 Jul 2020 • Nan Wang, Chengwei Chen, Yuan Xie, Lizhuang Ma
The brain structure in the collected data is complicated, thence, doctors are required to spend plentiful energy when diagnosing brain abnormalities.
Semi-supervised Anomaly Detection Supervised Anomaly Detection
no code implementations • WS 2020 • Nan Wang, Yan Song, Fei Xia
Medical conversation is a central part of medical care.
no code implementations • 9 Jun 2020 • Nan Wang, Hongning Wang
In this work, we propose a directional multi-aspect ranking criterion to enable a holistic ranking of items with respect to multiple aspects.
no code implementations • 18 May 2020 • Nan Wang, Zhen Qin, Xuanhui Wang, Hongning Wang
Recent advances in unbiased learning to rank (LTR) count on Inverse Propensity Scoring (IPS) to eliminate bias in implicit feedback.
no code implementations • 22 Apr 2020 • Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet Orgun, Longbing Cao, Nan Wang, Francesco Ricci, Philip S. Yu
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS).
no code implementations • 22 Feb 2020 • Tingting Zhang, Yushi Lan, Aiguo Song, Kun Liu, Nan Wang
The network information system is a military information network system with evolution characteristics.
1 code implementation • 21 Dec 2019 • Nan Wang, Yabin Zhou, Fenglei Han, Haitao Zhu, Jingzheng Yao
However, wavelength-dependent light attenuation and back-scattering result in color distortion and haze effect, which degrade the visibility of images.
no code implementations • 18 Sep 2019 • Nan Wang, Hongning Wang
The framework naturally leads to a probabilistic multi-aspect ranking criterion, which generalizes the single-aspect ranking to a multivariate fashion.
no code implementations • 3 Jun 2019 • Yiyi Tao, Yiling Jia, Nan Wang, Hongning Wang
In this work, we integrate regression trees to guide the learning of latent factor models for recommendation, and use the learnt tree structure to explain the resulting latent factors.
1 code implementation • 19 Sep 2018 • Nan Wang, Michail Matthaiou, Dimitrios S. Nikolopoulos, Blesson Varghese
When compared to executing applications on the Edge servers without dynamic vertical scaling, static priorities and dynamic priorities reduce SLO violation rates of requests by up to 4% and 12% for the online game, respectively, and in both cases 6% for the face detection workload.
Distributed, Parallel, and Cluster Computing Systems and Control
no code implementations • WS 2018 • Nan Wang, Yan Song, Fei Xia
This paper describes the COSTA scheme for coding structures and actions in conversation.
1 code implementation • 10 Jun 2018 • Nan Wang, Hongning Wang, Yiling Jia, Yue Yin
Explaining automatically generated recommendations allows users to make more informed and accurate decisions about which results to utilize, and therefore improves their satisfaction.
no code implementations • SEMEVAL 2018 • Nan Wang, Jin Wang, Xue-jie Zhang
This paper describes our approach to SemEval-2018 Task 2, which aims to predict the most likely associated emoji, given a tweet in English or Spanish.
no code implementations • IJCNLP 2017 • Nan Wang, Jin Wang, Xue-jie Zhang
This paper describes our submission to IJCNLP 2017 shared task 4, for predicting the tags of unseen customer feedback sentences, such as comments, complaints, bugs, requests, and meaningless and undetermined statements.
no code implementations • 29 Nov 2017 • Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Chao Wang, Nan Wang
Generative Adversarial Networks are proved to be efficient on various kinds of image generation tasks.
1 code implementation • 29 Nov 2017 • Ziqiang Zheng, Wang Chao, Zhibin Yu, Nan Wang, Haiyong Zheng, Bing Zheng
We present an approach for learning to translate faces in the wild from the source photo domain to the target caricature domain with different styles, which can also be used for other high-level image-to-image translation tasks.
no code implementations • 7 Sep 2016 • Blesson Varghese, Nan Wang, Sakil Barbhuiya, Peter Kilpatrick, Dimitrios S. Nikolopoulos
Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables.
Distributed, Parallel, and Cluster Computing
no code implementations • 11 Jul 2015 • Nan Wang
Better optimization algorithms that minimize the training loss can possibly give very poor generalization performance.
1 code implementation • 23 Jan 2014 • Nan Wang, Jan Melchior, Laurenz Wiskott
We present a theoretical analysis of Gaussian-binary restricted Boltzmann machines (GRBMs) from the perspective of density models.
no code implementations • 20 Dec 2013 • Nan Wang, Dirk Jancke, Laurenz Wiskott
Our work demonstrates the centered GDBM is a meaningful model approach for basic receptive field properties and the emergence of spontaneous activity patterns in early cortical visual areas.