Search Results for author: Nan Wang

Found 56 papers, 16 papers with code

Removal and Selection: Improving RGB-Infrared Object Detection via Coarse-to-Fine Fusion

1 code implementation19 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.

feature selection Object +3

Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum

no code implementations11 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.

Binary Classification Fraud Detection

Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection

no code implementations17 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.

Contrastive Learning Graph Anomaly Detection

RD-VIO: Robust Visual-Inertial Odometry for Mobile Augmented Reality in Dynamic Environments

1 code implementation23 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.

Depth Completion with Multiple Balanced Bases and Confidence for Dense Monocular SLAM

no code implementations8 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.

Depth Completion

Exploring Global and Local Information for Anomaly Detection with Normal Samples

no code implementations3 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.

Anomaly Detection Fraud Detection +1

BrainNPT: Pre-training of Transformer networks for brain network classification

no code implementations2 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.


TBDetector:Transformer-Based Detector for Advanced Persistent Threats with Provenance Graph

no code implementations6 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).


A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records

no code implementations15 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.

Clustered Data Sharing for Non-IID Federated Learning over Wireless Networks

no code implementations17 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.

Clustering Federated Learning +1

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation

no code implementations14 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.

counterfactual Counterfactual Inference +4

VIP-SLAM: An Efficient Tightly-Coupled RGB-D Visual Inertial Planar SLAM

no code implementations4 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.

AnoDFDNet: A Deep Feature Difference Network for Anomaly Detection

1 code implementation29 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.

Anomaly Detection object-detection +1

GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis

1 code implementation17 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.

Classification Representation Learning +1

IMO$^3$: Interactive Multi-Objective Off-Policy Optimization

no code implementations24 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.

Rank4Class: A Ranking Formulation for Multiclass Classification

no code implementations17 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.

Classification Image Classification +4

Comparative Explanations of Recommendations

no code implementations1 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.

Explainable Recommendation Recommendation Systems +1

Unbiased Graph Embedding with Biased Graph Observations

no code implementations26 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.

Fairness Graph Embedding

Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank

no code implementations29 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.

Image Classification Information Retrieval +4

An MRC Framework for Semantic Role Labeling

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.

Computational Efficiency Machine Reading Comprehension +3

CancerBERT: a BERT model for Extracting Breast Cancer Phenotypes from Electronic Health Records

no code implementations25 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).


The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion

1 code implementation15 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.

SAR Ship Detection

CORe: Capitalizing On Rewards in Bandit Exploration

no code implementations7 Mar 2021 Nan Wang, Branislav Kveton, Maryam Karimzadehgan

We propose a bandit algorithm that explores purely by randomizing its past observations.

Explanation as a Defense of Recommendation

no code implementations24 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.

Explanation Generation

Summarizing Medical Conversations via Identifying Important Utterances

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.

Distributed Learning with Low Communication Cost via Gradient Boosting Untrained Neural Network

no code implementations10 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.

Federated Learning

Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network

no code implementations9 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

Directional Multivariate Ranking

no code implementations9 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.

Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction

no code implementations18 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.


Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method

no code implementations22 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.

UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing

1 code implementation21 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.

Generative Adversarial Network

BPMR: Bayesian Probabilistic Multivariate Ranking

no code implementations18 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.

Recommendation Systems

The FacT: Taming Latent Factor Models for Explainability with Factorization Trees

no code implementations3 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.


DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments

1 code implementation19 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

Explainable Recommendation via Multi-Task Learning in Opinionated Text Data

1 code implementation10 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.

Explainable Recommendation Multi-Task Learning

YNU-HPCC at SemEval-2018 Task 2: Multi-ensemble Bi-GRU Model with Attention Mechanism for Multilingual Emoji Prediction

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.

Sentiment Analysis Task 2

YNU-HPCC at IJCNLP-2017 Task 4: Attention-based Bi-directional GRU Model for Customer Feedback Analysis Task of English

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.

General Classification Question Answering +4

Unpaired Photo-to-Caricature Translation on Faces in the Wild

1 code implementation29 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.

Caricature Photo-To-Caricature Translation +2

Challenges and Opportunities in Edge Computing

no code implementations7 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

A new boosting algorithm based on dual averaging scheme

no code implementations11 Jul 2015 Nan Wang

Better optimization algorithms that minimize the training loss can possibly give very poor generalization performance.

BIG-bench Machine Learning

Gaussian-binary Restricted Boltzmann Machines on Modeling Natural Image Statistics

1 code implementation23 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.

blind source separation

Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines

no code implementations20 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.

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