Weilin Cong - RankMe

26 papers A* 7A 3Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation. WWW Xiao Lin, Zhicheng Tang, Weilin Cong, Mengyue Hang, Kai Wang, Yajuan Wang, Zhichen Zeng, Ting-Wei Li, Hyunsik Yoo, Zhining Liu, Xuying Ning, Ruizhong Qiu, Wen-Yen Chen, Shuo Chang, Rong Jin, Huayu Li, Hanghang Tong
2025	A	`conf`	Billion-Scale Graph Deep Learning Framework for Ads Recommendation. CIKM Si Zhang, Weilin Cong, Dongqi Fu, Andrey Malevich, Hao Wu, Baichuan Yuan, Xin Zhou, Kaveh Hassani, Zhigang Hua, Austin Derrow-Pinion, Yan Xie, Xuewei Wang, Yinglong Xia, Ning Yao, Vena Li, Sem Park, Bo Long
2025	A*	`conf`	Learning Graph Quantized Tokenizers. ICLR Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long
2024	J	`jnl`	Learning Graph Quantized Tokenizers for Transformers. CoRR Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long
2024	J	`jnl`	On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method. CoRR Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi
2023	—	`conf`	BeMap: Balanced Message Passing for Fair Graph Neural Network. LoG Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong
2023	J	`jnl`	BeMap: Balanced Message Passing for Fair Graph Neural Network. CoRR Xiao Lin, Jian Kang, Weilin Cong, Hanghang Tong
2023	A*	`conf`	Do We Really Need Complicated Model Architectures For Temporal Networks? ICLR Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
2023	J	`jnl`	Do We Really Need Complicated Model Architectures For Temporal Networks? CoRR Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
2023	A	`conf`	DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi
2023	A	`conf`	Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. AISTATS Weilin Cong, Mehrdad Mahdavi
2023	J	`jnl`	Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. CoRR Weilin Cong, Mehrdad Mahdavi
2023	J	`jnl`	Understanding the Structural Components Behind the Psychological Effects of Autonomous Sensory Meridian Response (ASMR) With Machine Learning and Experimental Methods. J. Media Psychol. Theor. Methods Appl. Ryan Tan, Heather Shoenberger, Weilin Cong, Mehrdad Mahdavi
2022	A*	`conf`	Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. ICLR Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
2022	J	`jnl`	Predicting Protein-Ligand Docking Structure with Graph Neural Network. J. Chem. Inf. Model. Huaipan Jiang, Jian Wang, Weilin Cong, Yihe Huang, Morteza Ramezani, Anup Sarma, Nikolay V. Dokholyan, Mehrdad Mahdavi, Mahmut T. Kandemir
2021	J	`jnl`	Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen
2021	J	`jnl`	Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. CoRR Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
2021	A*	`conf`	On Provable Benefits of Depth in Training Graph Convolutional Networks. NeurIPS Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
2021	J	`jnl`	On Provable Benefits of Depth in Training Graph Convolutional Networks. CoRR Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
2021	J	`jnl`	On the Importance of Sampling in Learning Graph Convolutional Networks. CoRR Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
2020	—	`conf`	Encrypted rich-data steganography using generative adversarial networks. WiseML@WiSec Dule Shu, Weilin Cong, Jiaming Chai, Conrad S. Tucker
2020	A*	`conf`	GCN meets GPU: Decoupling "When to Sample" from "How to Sample". NeurIPS Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Anand Sivasubramaniam, Mahmut T. Kandemir
2020	A*	`conf`	Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. KDD Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi
2020	J	`jnl`	Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. CoRR Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi
2019	—	`conf`	Balance of memory footprint and runtime for high-density routing in large-scale FPGAs. ASICON Wei Liu, Weilin Cong, Chengyu Hu, Peng Lu, Jinmei Lai
2017	J	`jnl`	Improved Face Detection and Alignment using Cascade Deep Convolutional Network. CoRR Weilin Cong, Sanyuan Zhao, Hui Tian, Jianbing Shen