Search Results for author: Wei Guo

Found 56 papers, 22 papers with code

Learning to Manipulate Artistic Images

1 code implementation25 Jan 2024 Wei Guo, Yuqi Zhang, De Ma, Qian Zheng

Recent advancement in computer vision has significantly lowered the barriers to artistic creation.

Computational Efficiency Feature Compression +2

JMA: a General Algorithm to Craft Nearly Optimal Targeted Adversarial Example

1 code implementation2 Jan 2024 Benedetta Tondi, Wei Guo, Mauro Barni

Most of the approaches proposed so far to craft targeted adversarial examples against Deep Learning classifiers are highly suboptimal and typically rely on increasing the likelihood of the target class, thus implicitly focusing on one-hot encoding settings.

Multi-Label Classification

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

1 code implementation6 Nov 2023 Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong liu, Ruiming Tang, Defu Lian, Enhong Chen

To this end, we propose a graph-driven framework, named Adaptive and Personalized Graph Learning for Sequential Recommendation (APGL4SR), that incorporates adaptive and personalized global collaborative information into sequential recommendation systems.

Graph Learning Multi-Task Learning +1

Adaptive Multi-Modalities Fusion in Sequential Recommendation Systems

1 code implementation30 Aug 2023 Hengchang Hu, Wei Guo, Yong liu, Min-Yen Kan

We propose a graph-based approach (named MMSR) to fuse modality features in an adaptive order, enabling each modality to prioritize either its inherent sequential nature or its interplay with other modalities.

Sequential Recommendation

Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction

no code implementations19 Aug 2023 Hengyu Zhang, Chang Meng, Wei Guo, Huifeng Guo, Jieming Zhu, Guangpeng Zhao, Ruiming Tang, Xiu Li

Click-Through Rate (CTR) prediction, crucial in applications like recommender systems and online advertising, involves ranking items based on the likelihood of user clicks.

Click-Through Rate Prediction Recommendation Systems

MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction

1 code implementation3 Aug 2023 Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang

The large capacity of neural models helps digest such massive amounts of data under the supervised learning paradigm, yet they fail to utilize the substantial data to its full potential, since the 1-bit click signal is not sufficient to guide the model to learn capable representations of features and instances.

Binary Classification Click-Through Rate Prediction +1

ATWM: Defense against adversarial malware based on adversarial training

no code implementations11 Jul 2023 Kun Li, Fan Zhang, Wei Guo

In order to defend against malware attacks, researchers have proposed many Windows malware detection models based on deep learning.

Adversarial Defense Malware Detection

FGAM:Fast Adversarial Malware Generation Method Based on Gradient Sign

no code implementations22 May 2023 Kun Li, Fan Zhang, Wei Guo

Adversarial attacks are to deceive the deep learning model by generating adversarial samples.

Malware Detection

CodeKGC: Code Language Model for Generative Knowledge Graph Construction

2 code implementations18 Apr 2023 Zhen Bi, Jing Chen, Yinuo Jiang, Feiyu Xiong, Wei Guo, Huajun Chen, Ningyu Zhang

However, large generative language model trained on structured data such as code has demonstrated impressive capability in understanding natural language for structural prediction and reasoning tasks.

Code Completion graph construction +1

Compressed Interaction Graph based Framework for Multi-behavior Recommendation

1 code implementation4 Mar 2023 Wei Guo, Chang Meng, Enming Yuan, ZhiCheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang

However, it is challenging to explore multi-behavior data due to the unbalanced data distribution and sparse target behavior, which lead to the inadequate modeling of high-order relations when treating multi-behavior data ''as features'' and gradient conflict in multitask learning when treating multi-behavior data ''as labels''.

Multi-Task Learning

A holistically 3D-printed flexible millimeter-wave Doppler radar: Towards fully printed high-frequency multilayer flexible hybrid electronics systems

no code implementations24 Feb 2023 Hong Tang, Yingjie Zhang, Bowen Zheng, Sensong An, Mohammad Haerinia, Yunxi Dong, Yi Huang, Wei Guo, Hualiang Zhang

Flexible hybrid electronics (FHE) is an emerging technology enabled through the integration of advanced semiconductor devices and 3D printing technology.

A Survey on User Behavior Modeling in Recommender Systems

no code implementations22 Feb 2023 ZhiCheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang

Besides, we elaborate on the industrial practices of UBM methods with the hope of providing insights into the application value of existing UBM solutions.

Recommendation Systems

Universal Detection of Backdoor Attacks via Density-based Clustering and Centroids Analysis

1 code implementation11 Jan 2023 Wei Guo, Benedetta Tondi, Mauro Barni

Experiments carried out on several classification tasks and network architectures, considering different types of backdoor attacks (with either clean or corrupted labels), and triggering signals, including both global and local triggering signals, as well as sample-specific and source-specific triggers, reveal that the proposed method is very effective to defend against backdoor attacks in all the cases, always outperforming the state of the art techniques.

Backdoor Attack Clustering

Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation

no code implementations11 Nov 2022 Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates

To offer accurate and diverse recommendation services, recent methods use auxiliary information to foster the learning process of user and item representations.

Decision Making Recommendation Systems +2

Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks

1 code implementation26 Oct 2022 Hengyu Zhang, Enming Yuan, Wei Guo, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang

Sequential recommendation (SR) plays an important role in personalized recommender systems because it captures dynamic and diverse preferences from users' real-time increasing behaviors.

Disentanglement Information Retrieval +1

IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System

2 code implementations18 Oct 2022 Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, JinXing Liu, Zhenhua Dong, Ruiming Tang

FE-Block module performs fine-grained and early feature interactions to capture the interactive signals between user and item towers explicitly and CIR module leverages a contrastive interaction regularization to further enhance the interactions implicitly.

Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation

no code implementations3 Aug 2022 Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang

More specifically, we propose a novel Coarse-to-fine Knowledge-enhanced Multi-interest Learning (CKML) framework to learn shared and behavior-specific interests for different behaviors.

A temporal chrominance trigger for clean-label backdoor attack against anti-spoof rebroadcast detection

no code implementations2 Jun 2022 Wei Guo, Benedetta Tondi, Mauro Barni

We propose a stealthy clean-label video backdoor attack against Deep Learning (DL)-based models aiming at detecting a particular class of spoofing attacks, namely video rebroadcast attacks.

Backdoor Attack

Improved-Flow Warp Module for Remote Sensing Semantic Segmentation

no code implementations9 May 2022 Yinjie Zhang, Yi Liu, Wei Guo

Second, the offsets help with the low-resolution deep feature up-sampling process to improve the feature accordance, which boosts the accuracy of semantic segmentation.

Segmentation Semantic Segmentation

Cross Pairwise Ranking for Unbiased Item Recommendation

1 code implementation26 Apr 2022 Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang

In this work, we develop a new learning paradigm named Cross Pairwise Ranking (CPR) that achieves unbiased recommendation without knowing the exposure mechanism.

Recommendation Systems

Rotated Object Detection via Scale-invariant Mahalanobis Distance in Aerial Images

no code implementations2 Apr 2022 Siyang Wen, Wei Guo, Yi Liu, Ruijie Wu

The eight-parameter (coordinates of box vectors) methods in rotated object detection usually use ln-norm losses (L1 loss, L2 loss, and smooth L1 loss) as loss functions.

Object object-detection +1

Extending the WILDS Benchmark for Unsupervised Adaptation

1 code implementation ICLR 2022 Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang

Unlabeled data can be a powerful point of leverage for mitigating these distribution shifts, as it is frequently much more available than labeled data and can often be obtained from distributions beyond the source distribution as well.

MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction

no code implementations30 Nov 2021 Wei Guo, Can Zhang, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang

With the help of two novel CNN-based multi-interest extractors, self-supervision signals are discovered with full considerations of different interest representations (point-wise and union-wise), interest dependencies (short-range and long-range), and interest correlations (inter-item and intra-item).

Click-Through Rate Prediction Contrastive Learning +3

An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences

no code implementations16 Nov 2021 Wei Guo, Benedetta Tondi, Mauro Barni

The classification guiding the analysis is based on the amount of control that the attacker has on the training process, and the capability of the defender to verify the integrity of the data used for training, and to monitor the operations of the DNN at training and test time.

Backdoor Attack Test

Dual Graph enhanced Embedding Neural Network for CTR Prediction

no code implementations1 Jun 2021 Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He

To solve these problems, we propose a novel module named Dual Graph enhanced Embedding, which is compatible with various CTR prediction models to alleviate these two problems.

Click-Through Rate Prediction Recommendation Systems

Estimates of maize plant density from UAV RGB images using Faster-RCNN detection model: impact of the spatial resolution

no code implementations25 May 2021 Kaaviya Velumani, Raul Lopez-Lozano, Simon Madec, Wei Guo, Joss Gillet, Alexis Comar, Frederic Baret

Results show that Faster-RCNN achieved very good plant detection and counting (rRMSE=0. 08) performances when native HR images are used both for training and validation.

Generative Adversarial Network Management +1

Global Wheat Challenge 2020: Analysis of the competition design and winning models

no code implementations13 May 2021 Etienne David, Franklin Ogidi, Wei Guo, Frederic Baret, Ian Stavness

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems.

Data Augmentation Head Detection +1

Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance

no code implementations5 May 2021 Wei Guo, Marc Brittain, Peng Wei

We demonstrate the effectiveness of the two sub-modules in an open-source air traffic simulator with challenging environment settings.

Data Augmentation reinforcement-learning +1

Deep Learning for Click-Through Rate Estimation

no code implementations21 Apr 2021 Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He

In this survey, we provide a comprehensive review of deep learning models for CTR estimation tasks.

Recommendation Systems

ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table

1 code implementation17 Apr 2021 Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu

Different from the models with dense training data, the training data for CTR models is usually high-dimensional and sparse.

FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data

no code implementations9 Jan 2021 Shuyuan Yan, Bolin Ding, Wei Guo, Jingren Zhou, Zhewei Wei, Xiaowei Jiang, Sheng Xu

Our scalable real-time forecasting system FlashP (Flash Prediction) is built based on this idea, with two major challenges to be resolved in this paper: first, we need to figure out how approximate aggregations affect the fitting of forecasting models, and forecasting results; and second, accordingly, what sampling algorithms we should use to obtain these approximate aggregations and how large the samples are.

Time Series Time Series Analysis

Multi-Scale Cascading Network with Compact Feature Learning for RGB-Infrared Person Re-Identification

no code implementations12 Dec 2020 Can Zhang, Hong Liu, Wei Guo, Mang Ye

RGB-Infrared person re-identification (RGB-IR Re-ID) aims to match persons from heterogeneous images captured by visible and thermal cameras, which is of great significance in the surveillance system under poor light conditions.

Person Re-Identification

ICNet: Intra-saliency Correlation Network for Co-Saliency Detection

3 code implementations NeurIPS 2020 Wen-Da Jin, Jun Xu, Ming-Ming Cheng, Yi Zhang, Wei Guo

Intra-saliency and inter-saliency cues have been extensively studied for co-saliency detection (Co-SOD).

Saliency Detection

Charge density wave and weak Kondo effect in a Dirac semimetal CeSbTe

no code implementations23 Nov 2020 Peng Li, Baijiang Lv, Yuan Fang, Wei Guo, Zhongzheng Wu, Yi Wu, Cheng-Maw Cheng, Dawei Shen, Yuefeng Nie, Luca Petaccia, Chao Cao, Zhu-An Xu, Yang Liu

Using angle-resolved photoemission spectroscopy (ARPES) and low-energy electron diffraction (LEED), together with density-functional theory (DFT) calculation, we report the formation of charge density wave (CDW) and its interplay with the Kondo effect and topological states in CeSbTe.

Strongly Correlated Electrons Materials Science

Commonsense knowledge adversarial dataset that challenges ELECTRA

no code implementations25 Oct 2020 Gongqi Lin, Yuan Miao, Xiaoyong Yang, Wenwu Ou, Lizhen Cui, Wei Guo, Chunyan Miao

To investigate machine comprehension models' ability in handling the commonsense knowledge, we created a Question and Answer Dataset with common knowledge of Synonyms (QADS).

Reading Comprehension Word Sense Disambiguation

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems

1 code implementation25 Aug 2020 Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates

We develop a Graph Structure Aware Incremental Learning framework, GraphSAIL, to address the commonly experienced catastrophic forgetting problem that occurs when training a model in an incremental fashion.

Incremental Learning Recommendation Systems

A Framework for Recommending Accurate and Diverse ItemsUsing Bayesian Graph Convolutional Neural Networks

1 code implementation Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2020 Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates

Because of the multitude of relationships existing in recommender systems, Graph Neural Networks (GNNs) based approaches have been proposed to better characterize the various relationships between a user and items while modeling a user's preferences.

Recommendation Systems

Computer Vision with Deep Learning for Plant Phenotyping in Agriculture: A Survey

no code implementations18 Jun 2020 Akshay L Chandra, Sai Vikas Desai, Wei Guo, Vineeth N. Balasubramanian

In light of growing challenges in agriculture with ever growing food demand across the world, efficient crop management techniques are necessary to increase crop yield.

Management Plant Phenotyping

Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases

1 code implementation6 Jun 2020 Wei Guo, Aylin Caliskan

Furthermore, we develop two methods, Intersectional Bias Detection (IBD) and Emergent Intersectional Bias Detection (EIBD), to automatically identify the intersectional biases and emergent intersectional biases from static word embeddings in addition to measuring them in contextualized word embeddings.

Bias Detection Sentence +1

Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter

1 code implementation18 Apr 2020 Autumn Toney, Akshat Pandey, Wei Guo, David Broniatowski, Aylin Caliskan

This paper considers the problem of automatically characterizing overall attitudes and biases that may be associated with emerging information operations via artificial intelligence.

Semantic-Aware Label Placement for Augmented Reality in Street View

no code implementations15 Dec 2019 Jianqing Jia, Semir Elezovikj, Heng Fan, Shuojin Yang, Jing Liu, Wei Guo, Chiu C. Tan, Haibin Ling

Our solution encodes the constraints for placing labels in an optimization problem to obtain the final label layout, and the labels will be placed in appropriate positions to reduce the chances of overlaying important real-world objects in street view AR scenarios.

An Adaptive Supervision Framework for Active Learning in Object Detection

no code implementations7 Aug 2019 Sai Vikas Desai, Akshay L Chandra, Wei Guo, Seishi Ninomiya, Vineeth N. Balasubramanian

Our extensive experiments show that the proposed framework can be used to train good generalizable models with much lesser annotation costs than the state of the art active learning approaches for object detection.

Active Learning object-detection +1

Deep Learning-Based Semantic Segmentation of Microscale Objects

1 code implementation3 Jul 2019 Ekta U. Samani, Wei Guo, Ashis G. Banerjee

Accurate estimation of the positions and shapes of microscale objects is crucial for automated imaging-guided manipulation using a non-contact technique such as optical tweezers.

Segmentation Semantic Segmentation

Automatic estimation of heading date of paddy rice using deep learning

no code implementations19 Jun 2019 Sai Vikas Desai, Vineeth N. Balasubramanian, Tokihiro Fukatsu, Seishi Ninomiya, Wei Guo

Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location.

Image Classification Time Series +1

Towards Personalized Management of Type B Aortic Dissection Using STENT: a STandard cta database with annotation of the ENtire aorta and True-false lumen

no code implementations3 Jan 2019 Jianning Li, Long Cao, Yangyang Ge, Bowen Meng, Cheng Wang, Wei Guo

The database contains 274 CT angiography (CTA) scans from 274 unique TBAD patients and is split into a training set(254 cases including 210 preoperative and 44 postoperative scans ) and a test set(20 cases). Based on STENT, we develop a series of methods including automated TBAD segmentation and automated measurement of TBAD parameters that facilitate personalized and precise management of the disease.

Decision Making Management +1

Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by Imitating Physicians

no code implementations14 Dec 2017 Ning Li, Haopeng Liu, Bin Qiu, Wei Guo, Shijun Zhao, Kungang Li, Jie He

This paper proposes a novel and efficient method to build a Computer-Aided Diagnoses (CAD) system for lung nodule detection based on Computed Tomography (CT).

Computed Tomography (CT) Lung Nodule Detection +2

A Note on Community Trees in Networks

no code implementations11 Oct 2017 Ruqian Chen, Yen-Chi Chen, Wei Guo, Ashis G. Banerjee

We introduce the concept of community trees that summarizes topological structures within a network.

Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification

no code implementations12 Jan 2017 Wei Guo, Krithika Manohar, Steven L. Brunton, Ashis G. Banerjee

Topological data analysis (TDA) has emerged as one of the most promising techniques to reconstruct the unknown shapes of high-dimensional spaces from observed data samples.

General Classification Texture Classification +1

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