Guojing Cong
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
41
Venues
14
Active years
2004–2024
Best venue rank
A*
Where they publish
Papers
41 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICDM | Cross-tissue, Cross-platform Prediction and Validation of Toxicogenomics Profiles with Deep Learning and Clustering. | Trang Do, Richard Kim, Scott Auerbach, Warren M. Casey, Andrew A. Rooney, Guojing Cong |
| 2024 | ICMLA | Predicting Drug Effects from High-Dimensional, Asymmetric Drug Datasets by Using Graph Neural Networks: A Comprehensive Analysis of Multitarget Drug Effect Prediction. | Avishek Bose, Guojing Cong |
| 2023 | ICDM | Clustering High-dimensional Toxicogenomics Data with Rare Signals. | Guojing Cong, Scott Auerbach |
| 2023 | ICMLA | Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. | Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman |
| 2022 | ICDM | Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery. | Guojing Cong, Talia Ben-Naim, Victor Fung, Anshul Gupta, Rodrigo Neumann, Mathias Steiner |
| 2022 | ICDM | Augmenting Graph Convolution with Distance Preserving Embedding for Improved Learning. | Guojing Cong, Seung-Hwan Lim, Steven Young |
| 2022 | SC | Exaflops Biomedical Knowledge Graph Analytics. | Ramakrishnan Kannan, Piyush Sao, Hao Lu, Jakub Kurzak, Gundolf Schenk, Yongmei Shi, Seung-Hwan Lim, Sharat Israni, Vijay Thakkar, Guojing Cong, Robert M. Patton, Sergio E. Baranzini, Richard W. Vuduc, Thomas E. Potok |
| 2022 | SC | Neuromorphic Computing for Scientific Applications. | Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman |
| 2021 | ICMLA | Elastic distributed training with fast convergence and efficient resource utilization. | Guojing Cong |
| 2020 | CCGRID | Partial data permutation for training deep neural networks. | Guojing Cong, Li Zhang, Chih-Chieh Yang |
| 2020 | ICASSP | Fast Training of Deep Neural Networks for Speech Recognition. | Guojing Cong, Brian Kingsbury, Chih-Chieh Yang, Tianyi Liu |
| 2020 | SC | Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum. | Guojing Cong, Tianyi Liu |
| 2019 | HiPC | Accelerating Data Loading in Deep Neural Network Training. | Chih-Chieh Yang, Guojing Cong |
| 2019 | WACV | Video Action Recognition With an Additional End-to-End Trained Temporal Stream. | Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Chih-Chieh Yang, Barry Chen |
| 2019 | SC | Preparation and optimization of a diverse workload for a large-scale heterogeneous system. | Ian Karlin, Yoonho Park, Bronis R. de Supinski, Peng Wang, Bert Still, David Beckingsale, Robert Blake, Tong Chen, Guojing Cong, Carlos H. A. Costa, Johann Dahm, Giacomo Domeniconi, Thomas Epperly, Aaron Fisher, Sara Kokkila Schumacher, Steven H. Langer, Hai Le, Eun Kyung Lee, Naoya Maruyama, Xinyu Que, David F. Richards, Bjrn Sjgreen, Jonathan Wong, Carol S. Woodward, Ulrike Meier Yang, Xiaohua Zhang, Bob Anderson, David Appelhans, Levi Barnes, Peter D. Barnes Jr., Sorin Bastea, David Bhme, Jamie A. Bramwell, James M. Brase, Jos R. Brunheroto, Barry Chen, Charway R. Cooper, Tony Degroot, Robert D. Falgout, Todd Gamblin, David J. Gardner, James N. Glosli, John A. Gunnels, Max P. Katz, Tzanio V. Kolev, I-Feng W. Kuo, Matthew P. LeGendre, Ruipeng Li, Pei-Hung Lin, Shelby Lockhart, Kathleen McCandless, Claudia Misale, Jaime H. Moreno, Rob Neely, Jarom Nelson, Rao Nimmakayala, Kathryn M. O'Brien, Kevin O'Brien, Ramesh Pankajakshan, Roger Pearce, Slaven Peles, Phil Regier, Steven C. Rennich, Martin Schulz, Howard Scott, James C. Sexton, Kathleen Shoga, Shiv Sundram, Guillaume Thomas-Collignon, Brian Van Essen, Alexey Voronin, Bob Walkup, Lu Wang, Chris Ward, Hui-Fang Wen, Daniel A. White, Christopher Young, Cyril Zeller, Edward Zywicz |
| 2018 | IJCAI | On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization. | Fan Zhou, Guojing Cong |
| 2018 | SBAC-PAD | Accelerating Deep Neural Network Training for Action Recognition on a Cluster of GPUs. | Guojing Cong, Giacomo Domeniconi, Joshua Shapiro, Fan Zhou, Barry Chen |
| 2017 | ICMLA | A Hierarchical, Bulk-Synchronous Stochastic Gradient Descent Algorithm for Deep-Learning Applications on GPU Clusters. | Guojing Cong, Onkar Bhardwaj |
| 2017 | ICPP | An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications. | Guojing Cong, Onkar Bhardwaj, Minwei Feng |
| 2017 | SC | Accelerating deep neural network learning for speech recognition on a cluster of GPUs. | Guojing Cong, Brian Kingsbury, Soumyadip Gosh, George Saon, Fan Zhou |
| 2016 | HPCC | Composable Locality Optimizations for Accelerating Parallel Forest Computations. | Guojing Cong, Ilie Gabriel Tanase |
| 2016 | SC | Practical Efficiency of Asynchronous Stochastic Gradient Descent. | Onkar Bhardwaj, Guojing Cong |
| 2015 | EuroPar | Accelerating Minimum Spanning Forest Computations on Multicore Platforms. | Guojing Cong, Ilie Gabriel Tanase, Yinglong Xia |
| 2015 | SC | Parallelism-centric optimization and performance study of a finance aggregation engine on modern NUMA systems. | Guojing Cong, Sophia Wen, James Sedgwick, Louis Ly |
| 2015 | SBAC-PAD | Memory Centric Computation (Mc2) for Large-Scale Graph Processing. | Kattamuri Ekanadham, Guojing Cong |
| 2014 | EuroPar | Fast Parallel Connected Components Algorithms on GPUs. | Guojing Cong, Paul Muzio |
| 2014 | HPCC | A Synchronous Parallel Max-Flow Algorithm for Real-World Networks. | Guojing Cong |
| 2013 | SC | Maximizing the performance of irregular applications on multithreaded, NUMA systems. | Guojing Cong, Hui-Fang Wen |
| 2012 | HPCC | Tool-assisted Optimization of Shared-memory Accesses in UPC Applications. | Guojing Cong, Hui-Fang Wen, Hiroki Murata, Yasushi Negishi |
| 2012 | ISSTA | A static analysis tool using a three-step approach for data races in HPC programs. | Yasushi Negishi, Hiroki Murata, Guojing Cong, Hui-Fang Wen, I-Hsin Chung |
| 2012 | SC | Application data prefetching on the IBM blue gene/Q supercomputer. | I-Hsin Chung, Changhoan Kim, Hui-Fang Wen, Guojing Cong |
| 2010 | EuroPar | Guided Performance Analysis Combining Profile and Trace Tools. | Judit Gimnez, Jess Labarta, F. Xavier Pegenaute, Hui-Fang Wen, David J. Klepacki, I-Hsin Chung, Guojing Cong, Felix Voigtlnder, Bernd Mohr |
| 2010 | SC | Fast PGAS Implementation of Distributed Graph Algorithms. | Guojing Cong, George Almsi, Vijay A. Saraswat |
| 2009 | EuroPar | A Holistic Approach towards Automated Performance Analysis and Tuning. | Guojing Cong, I-Hsin Chung, Hui-Fang Wen, David J. Klepacki, Hiroki Murata, Yasushi Negishi, Takao Moriyama |
| 2008 | HPCC | Workload Performance Characterization of DARPA HPCS Benchmarks. | Seetharami R. Seelam, I-Hsin Chung, Guojing Cong, Hui-Fang Wen, David J. Klepacki |
| 2008 | ICPP | Solving Large, Irregular Graph Problems Using Adaptive Work-Stealing. | Guojing Cong, Sreedhar B. Kodali, Sriram Krishnamoorthy, Doug Lea, Vijay A. Saraswat, Tong Wen |
| 2007 | ISPA | Techniques for Designing Efficient Parallel Graph Algorithms for SMPs and Multicore Processors. | Guojing Cong, David A. Bader |
| 2006 | HiPC | A Study on the Locality Behavior of Minimum Spanning Tree Algorithms. | Guojing Cong, Simone Sbaraglia |
| 2005 | ICPP | On the Architectural Requirements for Efficient Execution of Graph Algorithms. | David A. Bader, Guojing Cong, John Feo |
| 2004 | HiPC | Lock-Free Parallel Algorithms: An Experimental Study. | Guojing Cong, David A. Bader |
| 2004 | ICPP | The Euler Tour Technique and Parallel Rooted Spanning Tree. | Guojing Cong, David A. Bader |