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2020 – today
- 2024
[i4]Xin Huang, Weipeng Zhuo, Minh Phu Vuong, Shiju Li, Jongryool Kim, Bradley Rees, Chul-Ho Lee:
CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks. CoRR abs/2404.02300 (2024)- 2023
- [c9]Seunghwa Kang, Chuck Hastings, Joe Eaton, Brad Rees:
cuGraph C++ primitives: vertex/edge-centric building blocks for parallel graph computing. IPDPS Workshops 2023: 226-229 - [c8]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-Linkage Agglomerative Clustering on the GPU. ECML/PKDD (1) 2023: 711-726 - [i3]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-linkage Agglomerative Clustering on the GPU. CoRR abs/2306.16354 (2023) - 2022
- [c7]Seunghwa Kang, Joseph Nke, Brad Rees:
Analyzing Multi-trillion Edge Graphs on Large GPU Clusters: A Case Study with PageRank. HPEC 2022: 1-7 - [c6]Xin Huang, Jongryool Kim, Bradley Rees, Chul-Ho Lee:
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass. IISWC 2022: 160-170 - [c5]Brad Rees, Xiaoyun Wang, Joe Eaton, Onur Yilmaz, Rick Ratzel, Dominique LaSalle:
Accelerated GNN Training with DGL and RAPIDS cuGraph in a Fraud Detection Workflow. KDD 2022: 4820-4821 - [c4]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, Tim Oates:
GPU Semiring Primitives for Sparse Neighborhood Methods. MLSys 2022 - [p1]Alexandre Fender, Brad Rees, Joe Eaton:
RAPIDS cuGraph. Massive Graph Analytics 2022: 483-493 - [i2]Xin Huang, Jongryool Kim, Bradley Rees, Chul-Ho Lee:
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass. CoRR abs/2211.03021 (2022) - 2021
- [j1]Florian Browne
, Brad Rees, George T.-C. Chiu, Neera Jain:
Iterative Learning Control With Time-Delay Compensation: An Application to Twin-Roll Strip Casting. IEEE Trans. Control. Syst. Technol. 29(1): 140-149 (2021) - [i1]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, John Zedlewski, Tim Oates:
Semiring Primitives for Sparse Neighborhood Methods on the GPU. CoRR abs/2104.06357 (2021) - 2020
- [c3]Seunghwa Kang, Alexandre Fender, Joe Eaton, Brad Rees:
Computing PageRank Scores of Web Crawl Data Using DGX A100 Clusters. HPEC 2020: 1-4 - [c2]Bartley Richardson, Bradley Rees, Tom Drabas, Even Oldridge, David A. Bader, Rachel Allen:
Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS. KDD 2020: 3503-3504
2010 – 2019
- 2013
- [c1]Ted E. Senator, Henry G. Goldberg, Alex Memory, William T. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon, David A. Bader, Edmond Chow, Irfan A. Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Green, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine, Jay Yoon Lee, Danai Koutra, Christos Faloutsos, Daniel D. Corkill, Lisa Friedland, Amanda Gentzel, David D. Jensen:
Detecting insider threats in a real corporate database of computer usage activity. KDD 2013: 1393-1401
Coauthor Index
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