Da Zheng

According to our database, Da Zheng authored at least 61 papers between 2010 and 2024.

Collaborative distances:

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

2024

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting.

Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis

IEEE Trans. Neural Networks Learn. Syst., February, 2024

NetInfoF Framework: Measuring and Exploiting Network Usable Information.

Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos

CoRR, 2024

2023

Tango: rethinking quantization for graph neural network training on GPUs.

Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu

CoRR, 2023

OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization.

Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu

CoRR, 2023

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks.

Kun Wu, Mert Hidayetoglu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-Mei W. Hwu

CoRR, 2023

PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction.

Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun

Proceedings of the ACM Web Conference 2023, 2023

DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training.

Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna

Proceedings of the International Conference for High Performance Computing, 2023

TANGO: re-thinking quantization for graph neural network training on GPUs.

Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu

Proceedings of the International Conference for High Performance Computing, 2023

DSP: Efficient GNN Training with Multiple GPUs.

Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis

Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2023

Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs.

Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang, Da Zheng, Soji Adeshina, Jun Ma, Han Zhao, Christos Faloutsos, George Karypis

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes.

Jian Zhang, Da Zheng, Xiang Song, Theodore Vasiloudis, Israt Nisa, Jim Lu

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

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications.

Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi

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

19th International Workshop on Mining and Learning with Graphs (MLG).

Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu

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

Optimizing Irregular Dense Operators of Heterogeneous GNN Models on GPU.

Israt Nisa, Minjie Wang, Da Zheng, Qiang Fu, Ümit V. Çatalyürek, George Karypis

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

2022

TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs.

Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis

Proc. VLDB Endow., 2022

From Local to Global: Spectral-Inspired Graph Neural Networks.

Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman

CoRR, 2022

Efficient and effective training of language and graph neural network models.

Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis

CoRR, 2022

TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs.

Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis

CoRR, 2022

Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs.

Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis

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

Nimble GNN Embedding with Tensor-Train Decomposition.

Chunxing Yin, Da Zheng, Israt Nisa, Christos Faloutsos, George Karypis, Richard W. Vuduc

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

2021

Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs.

Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis

CoRR, 2021

TraverseNet: Unifying Space and Time in Message Passing.

Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis

CoRR, 2021

Scalable Graph Neural Networks with Deep Graph Library.

Da Zheng, Minjie Wang, Quan Gan, Xiang Song, Zheng Zhang, George Karypis

Proceedings of the WSDM '21, 2021

Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks.

Balasubramaniam Srinivasan, Da Zheng, George Karypis

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Dr. Top-k: delegate-centric Top-k on GPUs.

Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu

Proceedings of the International Conference for High Performance Computing, 2021

Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs.

Jialin Dong, Da Zheng, Lin F. Yang, George Karypis

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

Schema-Aware Deep Graph Convolutional Networks for Heterogeneous Graphs.

Saurav Manchanda, Da Zheng, George Karypis

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Assessment of the accuracy of several methods for measuring the spatial attitude of geological bodies using an android smartphone.

Jue Wang, Nengpan Ju, Chaoyang He, Junchao Cai, Da Zheng

Comput. Geosci., 2020

PanRep: Universal node embeddings for heterogeneous graphs.

Vassilis N. Ioannidis, Da Zheng, George Karypis

CoRR, 2020

Few-shot link prediction via graph neural networks for Covid-19 drug-repurposing.

Vassilis N. Ioannidis, Da Zheng, George Karypis

CoRR, 2020

Collective Multi-type Entity Alignment Between Knowledge Graphs.

Qi Zhu, Hao Wei, Bunyamin Sisman, Da Zheng, Christos Faloutsos, Xin Luna Dong, Jiawei Han

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Learning Graph Neural Networks with Deep Graph Library.

Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis

Proceedings of the Companion of The 2020 Web Conference 2020, 2020

DGL-KE: Training Knowledge Graph Embeddings at Scale.

Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis

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

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs.

Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis

Proceedings of the 10th IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms, 2020

FeatGraph: a flexible and efficient backend for graph neural network systems.

Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang

Proceedings of the International Conference for High Performance Computing, 2020

Scalable Graph Neural Networks with Deep Graph Library.

Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis

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

2019

Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs.

Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang

CoRR, 2019

Graphyti: A Semi-External Memory Graph Library for FlashGraph.

Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns

CoRR, 2019

clusterNOR: A NUMA-Optimized Clustering Framework.

Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns

CoRR, 2019

2018

Challenges Towards Deploying Data Intensive Scientific Applications on Extreme Heterogeneity Supercomputers.

Hang Liu, Yufei Ding, Da Zheng, Seung Woo Son, Da Yan

CoRR, 2018

FlashR: parallelize and scale R for machine learning using SSDs.

Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns

Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2018

2017

Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs.

Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns

IEEE Trans. Parallel Distributed Syst., 2017

knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library.

Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal C. Burns

Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing, 2017

2016

FlashMatrix: Parallel, Scalable Data Analysis with Generalized Matrix Operations using Commodity SSDs.

Da Zheng, Disa Mhembere, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns

CoRR, 2016

Semi-External Memory Sparse Matrix Multiplication on Billion-node Graphs in a Multicore Architecture.

Da Zheng, Disa Mhembere, Vince Lyzinski, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns

CoRR, 2016

An SSD-based eigensolver for spectral analysis on billion-node graphs.

Da Zheng, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay

CoRR, 2016

NUMA-optimized In-memory and Semi-external-memory Parameterized Clustering.

Disa Mhembere, Da Zheng, Joshua T. Vogelstein, Carey E. Priebe, Randal C. Burns

CoRR, 2016

Directed automatic speech transcription error correction using bidirectional LSTM.

Da Zheng, Zhehuai Chen, Yue Wu, Kai Yu

Proceedings of the 10th International Symposium on Chinese Spoken Language Processing, 2016

2015

Optimize Unsynchronized Garbage Collection in an SSD Array.

Da Zheng, Randal C. Burns, Alexander S. Szalay

CoRR, 2015

FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs.

Da Zheng, Disa Mhembere, Randal C. Burns, Joshua T. Vogelstein, Carey E. Priebe, Alexander S. Szalay

Proceedings of the 13th USENIX Conference on File and Storage Technologies, 2015

2014

Hadoop in Low-Power Processors.

Da Zheng, Alexander S. Szalay, Andreas Terzis

CoRR, 2014

FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs.

Da Zheng, Disa Mhembere, Randal C. Burns, Alexander S. Szalay

CoRR, 2014

Active Community Detection in Massive Graphs.

Heng Wang, Da Zheng, Randal C. Burns, Carey E. Priebe

CoRR, 2014

Semantic parser enhancement for dialogue domain extension with little data.

Su Zhu, Lu Chen, Kai Sun, Da Zheng, Kai Yu

Proceedings of the 2014 IEEE Spoken Language Technology Workshop, 2014

2013

Toward millions of file system IOPS on low-cost, commodity hardware.

Da Zheng, Randal C. Burns, Alexander S. Szalay

Proceedings of the International Conference for High Performance Computing, 2013

Parallel Set Determination and K-Means Clustering for Data Mining on Telecommunication Networks.

Da-Qi Ren, Da Zheng, Guowei Huang, Shujie Zhang, Zane Wei

Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

2012

Automatic Parallelization of Array-oriented Programs for a Multi-core Machine.

Wai-Mee Ching, Da Zheng

Int. J. Parallel Program., 2012

A Parallel Page Cache: IOPS and Caching for Multicore Systems.

Da Zheng, Randal C. Burns, Alexander S. Szalay

Proceedings of the 4th USENIX Workshop on Hot Topics in Storage and File Systems, 2012

2011

Extending classic telecommunication addressing schemes for Home Gateway based user content and services discovery.

Da Zheng, Anne-Marie Bosneag, Sidath Handurukande, David Cleary

Proceedings of the 2011 IEEE Consumer Communications and Networking Conference, 2011

2010

Stability Analysis of Time Delayed System with Coefficient Uncertainty and Time Delay Uncertainty.

Da Zheng, Zhengyun Ren, Jian-An Fang

Eur. J. Control, 2010

Signal reconstruction and frequency estimation of a biased and noisy sinusoidal signal.

Da Zheng, Lei Jiang, Zhengyun Ren, Jian-An Fang, Xiumei Wu

Proceedings of the 8th IEEE International Conference on Control and Automation, 2010