no code implementations • 28 May 2024 • Mingjia Yin, Hao Wang, Wei Guo, Yong liu, Suojuan Zhang, Sirui Zhao, Defu Lian, Enhong Chen
The sequential recommender (SR) system is a crucial component of modern recommender systems, as it aims to capture the evolving preferences of users.
no code implementations • 27 May 2024 • Jiawei Shao, Jingwen Tong, Qiong Wu, Wei Guo, Zijian Li, Zehong Lin, Jun Zhang
To empower LLMs with knowledge and expertise in the wireless domain, this paper proposes WirelessLLM, a comprehensive framework for adapting and enhancing LLMs to address the unique challenges and requirements of wireless communication networks.
no code implementations • 21 May 2024 • Mingjia Yin, Hao Wang, Wei Guo, Yong liu, Zhi Li, Sirui Zhao, Defu Lian, Enhong Chen
Cross-domain sequential recommendation (CDSR) aims to uncover and transfer users' sequential preferences across multiple recommendation domains.
1 code implementation • 27 Mar 2024 • Shuai Xiang, Pieter M. Blok, James Burridge, Haozhou Wang, Wei Guo
The diverse and high-quality content generated by recent generative models demonstrates the great potential of using synthetic data to train downstream models.
no code implementations • 26 Mar 2024 • Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong liu, Defu Lian, Enhong Chen
In recommendation systems, users frequently engage in multiple types of behaviors, such as clicking, adding to a cart, and purchasing.
no code implementations • 3 Mar 2024 • Wei Guo, Fuzhen Zhuang, Xiao Zhang, Yiqi Tong, Jin Dong
However, since FL enables a continuous share of knowledge among participants with each communication round while not allowing local data to be accessed by other participants, FTL faces many unique challenges that are not present in TL.
1 code implementation • 25 Jan 2024 • Wei Guo, Yuqi Zhang, De Ma, Qian Zheng
Recent advancement in computer vision has significantly lowered the barriers to artistic creation.
1 code implementation • 2 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.
1 code implementation • 6 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.
1 code implementation • 9 Sep 2023 • Yongjie Wang, Hangwei Qian, Yongjie Liu, Wei Guo, Chunyan Miao
Existing methods fail to exploit flexibility and address the concerns of non-robustness simultaneously.
1 code implementation • 30 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.
no code implementations • 19 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.
1 code implementation • 3 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.
no code implementations • 11 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.
no code implementations • 22 May 2023 • Kun Li, Fan Zhang, Wei Guo
Adversarial attacks are to deceive the deep learning model by generating adversarial samples.
2 code implementations • 18 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.
1 code implementation • 4 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''.
no code implementations • 24 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.
no code implementations • 22 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.
1 code implementation • 11 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.
no code implementations • 11 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.
no code implementations • 3 Nov 2022 • Pouria Razzaghi, Amin Tabrizian, Wei Guo, Shulu Chen, Abenezer Taye, Ellis Thompson, Alexis Bregeon, Ali Baheri, Peng Wei
Then we survey the landscape of existing RL-based applications in aviation.
1 code implementation • 26 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.
2 code implementations • 18 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.
no code implementations • 3 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.
no code implementations • 2 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.
no code implementations • 9 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.
1 code implementation • 26 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.
no code implementations • 2 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.
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.
no code implementations • 30 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).
no code implementations • 16 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.
2 code implementations • Proceedings of the 30th ACM International Conference on Information & Knowledge Management 2021 • Bo Chen, Yichao Wang, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He
The state-of-the-art deep CTR models with parallel structure (e. g., DCN) learn explicit and implicit feature interactions through independent parallel networks.
no code implementations • 1 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.
no code implementations • 25 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.
no code implementations • 17 May 2021 • Etienne David, Mario Serouart, Daniel Smith, Simon Madec, Kaaviya Velumani, Shouyang Liu, Xu Wang, Francisco Pinto Espinosa, Shahameh Shafiee, Izzat S. A. Tahir, Hisashi Tsujimoto, Shuhei Nasuda, Bangyou Zheng, Norbert Kichgessner, Helge Aasen, Andreas Hund, Pouria Sadhegi-Tehran, Koichi Nagasawa, Goro Ishikawa, Sébastien Dandrifosse, Alexis Carlier, Benoit Mercatoris, Ken Kuroki, Haozhou Wang, Masanori Ishii, Minhajul A. Badhon, Curtis Pozniak, David Shaner LeBauer, Morten Lilimo, Jesse Poland, Scott Chapman, Benoit de Solan, Frédéric Baret, Ian Stavness, Wei Guo
We now release a new version of the Global Wheat Head Detection (GWHD) dataset in 2021, which is bigger, more diverse, and less noisy than the 2020 version.
no code implementations • 13 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.
no code implementations • 5 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.
no code implementations • 1 May 2021 • Wei Guo, Benedetta Tondi, Mauro Barni
We introduce a new attack against face verification systems based on Deep Neural Networks (DNN).
no code implementations • 21 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.
1 code implementation • 17 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.
no code implementations • 9 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.
6 code implementations • 14 Dec 2020 • Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton A. Earnshaw, Imran S. Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the wild.
no code implementations • 12 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.
4 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).
no code implementations • 23 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
no code implementations • 25 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).
1 code implementation • 25 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.
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.
no code implementations • 18 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.
1 code implementation • 6 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.
1 code implementation • 18 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.
no code implementations • 15 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.
no code implementations • 4 Oct 2019 • Akshay L Chandra, Sai Vikas Desai, Vineeth N. Balasubramanian, Seishi Ninomiya, Wei Guo
We show promising results on two publicly available cereal crop datasets - Sorghum and Wheat.
no code implementations • 7 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.
1 code implementation • 3 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.
no code implementations • 19 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.
no code implementations • 3 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.
no code implementations • 6 Aug 2018 • Bin Chen, Wei Guo, Bin Li, Rober K. F. Teng, Mingjun Dai, Jianping Luo, Hui Wang
An automatic classification method has been studied to effectively detect and recognize Electrocardiogram (ECG).
no code implementations • 14 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).
no code implementations • 11 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.
no code implementations • 12 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.