Yingxue Zhang

According to our database, Yingxue Zhang authored at least 66 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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

Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang

ACM Trans. Inf. Syst., January, 2024

Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization.

Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang

Trans. Mach. Learn. Res., 2024

DyG2Vec: Efficient Representation Learning for Dynamic Graphs.

Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates

Trans. Mach. Learn. Res., 2024

The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation.

Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chételat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan

CoRR, 2024

Enhancing CTR Prediction in Recommendation Domain with Search Query Representation.

Yuening Wang, Chen Ma, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates

CoRR, 2024

Sparse Decomposition of Graph Neural Networks.

Yaochen Hu, Mai Zeng, Ge Zhang, Pavel Rumiantsev, Liheng Ma, Yingxue Zhang, Mark Coates

CoRR, 2024

ET-Plan-Bench: Embodied Task-level Planning Benchmark Towards Spatial-Temporal Cognition with Foundation Models.

Lingfeng Zhang, Yuening Wang, Hongjian Gu, Atia Hamidizadeh, Zhanguang Zhang, Yuecheng Liu, Yutong Wang, David Gamaliel Arcos Bravo, Junyi Dong, Shunbo Zhou, Tongtong Cao, Yuzheng Zhuang, Yingxue Zhang, Jianye Hao

CoRR, 2024

HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation.

Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates

CoRR, 2024

Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data.

Jiaming Zhou, Abbas Ghaddar, Ge Zhang, Liheng Ma, Yaochen Hu, Soumyasundar Pal, Mark Coates, Bin Wang, Yingxue Zhang, Jianye Hao

CoRR, 2024

MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization.

Faezeh Faez, Raika Karimi, Yingxue Zhang, Xing Li, Lei Chen, Mingxuan Yuan, Mahdi Biparva

CoRR, 2024

Personalized Negative Reservoir for Incremental Learning in Recommender Systems.

Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates

CoRR, 2024

GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection.

Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network.

Yunbo Hou, Haoran Ye, Yingxue Zhang, Siyuan Xu, Guojie Song

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

CKGConv: General Graph Convolution with Continuous Kernels.

Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Generalizable and Relation Sensitive Netlist Representation for Analog Circuit Design.

Surya Penmetsa, Fahad Rahman Amik, Zhanguang Zhang, Yingying Fu, Yingxue Zhang, Wulong Liu, Jianye Hao

Proceedings of the Great Lakes Symposium on VLSI 2024, 2024

Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation.

Yuening Wang, Man Chen, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Multi-resolution Time-Series Transformer for Long-term Forecasting.

Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

EWEK-QA : Enhanced Web and Efficient Knowledge Graph Retrieval for Citation-based Question Answering Systems.

Mohammad Dehghan, Mohammad Ali Alomrani, Sunyam Bagga, David Alfonso-Hermelo, Khalil Bibi, Abbas Ghaddar, Yingxue Zhang, Xiaoguang Li, Jianye Hao, Qun Liu, Jimmy Lin, Boxing Chen, Prasanna Parthasarathi, Mahdi Biparva, Mehdi Rezagholizadeh

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Preference and Concurrence Aware Bayesian Graph Neural Networks for Recommender Systems.

Hongjian Gu, Yaochen Hu, Yingxue Zhang

CoRR, 2023

Towards Automated Negative Sampling in Implicit Recommendation.

Fuyuan Lyu, Yaochen Hu, Xing Tang, Yingxue Zhang, Ruiming Tang, Xue Liu

CoRR, 2023

Dynamically Expandable Graph Convolution for Streaming Recommendation.

Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma

Proceedings of the ACM Web Conference 2023, 2023

Compressed Interaction Graph based Framework for Multi-behavior Recommendation.

Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang

Proceedings of the ACM Web Conference 2023, 2023

Hierarchical Projection Enhanced Multi-behavior Recommendation.

Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

A Survey on User Behavior Modeling in Recommender Systems.

Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Bidirectional Learning for Offline Model-based Biological Sequence Design.

Can Chen, Yingxue Zhang, Xue Liu, Mark Coates

Proceedings of the International Conference on Machine Learning, 2023

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

Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Dual-Process Graph Neural Network for Diversified Recommendation.

Yuanyi Ren, Hang Ni, Yingxue Zhang, Xi Wang, Guojie Song, Dong Li, Jianye Hao

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System.

Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Spectral Augmentations for Graph Contrastive Learning.

Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems.

Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network.

Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Node copying: A random graph model for effective graph sampling.

Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates

Signal Process., 2022

DyG2Vec: Representation Learning for Dynamic Graphs with Self-Supervision.

Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates

CoRR, 2022

Polarized Graph Neural Networks.

Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation.

Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

EFLEC: Efficient Feature-LEakage Correction in GNN based Recommendation Systems.

Ishaan Kumar, Yaochen Hu, Yingxue Zhang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Versatile Multi-stage Graph Neural Network for Circuit Representation.

Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bidirectional Learning for Offline Infinite-width Model-based Optimization.

Can Chen, Yingxue Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding.

Mohammad Amini, Zhanguang Zhang, Surya Penmetsa, Yingxue Zhang, Jianye Hao, Wulong Liu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation.

Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Invariant Factor Graph Neural Networks.

Zheng Fang, Ziyun Zhang, Guojie Song, Yingxue Zhang, Dong Li, Jianye Hao, Xi Wang

Proceedings of the IEEE International Conference on Data Mining, 2022

Dual Path Graph Convolutional Networks.

Yunhe Li, Yaochen Hu, Yingxue Zhang

Proceedings of the IEEE International Conference on Acoustics, 2022

Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation.

Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction.

Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation.

Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King

CoRR, 2021

Content Filtering Enriched GNN Framework for News Recommendation.

Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He

CoRR, 2021

Modeling Scale-free Graphs for Knowledge-aware Recommendation.

Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jian Hao, Irwin King

CoRR, 2021

TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion.

Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Dual Graph enhanced Embedding Neural Network for CTR Prediction.

Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting.

Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates

Proceedings of the 38th International Conference on Machine Learning, 2021

Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction.

Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems.

Yuening Wang, Yingxue Zhang, Mark Coates

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Graph Representation Learning via Adversarial Variational Bayes.

Yunhe Li, Yaochen Hu, Yingxue Zhang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender Systems.

Kian Ahrabian, Yishi Xu, Yingxue Zhang, Jiapeng Wu, Yuening Wang, Mark Coates

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Detection and Defense of Topological Adversarial Attacks on Graphs.

Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Knowledge-Enhanced Top-K Recommendation in Poincaré Ball.

Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Non Parametric Graph Learning for Bayesian Graph Neural Networks.

Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Neighbor Interaction Aware Graph Convolution Networks for Recommendation.

Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, Mark Coates

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks.

Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation.

Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation.

Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates

Proceedings of the 37th International Conference on Machine Learning, 2020

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems.

Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Memory Augmented Graph Neural Networks for Sequential Recommendation.

Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Multi-graph Convolution Collaborative Filtering.

Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification.

Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence.

Chen Ma, Yingxue Zhang, Qinglong Wang, Xue Liu

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018