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Publication search results
found 85 matches
- 2024
- Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar:
Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. AAAI 2024: 15066-15074 - Yongseok Soh, Ramakrishnan Kannan, Piyush Sao, Jee W. Choi:
Accelerated Constrained Sparse Tensor Factorization on Massively Parallel Architectures. ICPP 2024: 107-116 - Emre Eftelioglu, Bistra Dilkina, Naoki Abe, Ramakrishnan Kannan, Yuzhou Chen, Yulia R. Gel, Kathleen Buckingham, Auroop R. Ganguly, James Hodson, Jiafu Mao:
Fragile Earth: Generative and Foundational Models for Sustainable Development. KDD 2024: 6710-6711 - Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar:
Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. CoRR abs/2402.11760 (2024) - Zhi-Feng Wei, Pablo Moriano, Ramakrishnan Kannan:
Robustness of graph embedding methods for community detection. CoRR abs/2405.00636 (2024) - 2023
- Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru:
Sparse Symmetric Format for Tucker Decomposition. IEEE Trans. Parallel Distributed Syst. 34(6): 1743-1756 (2023) - Ramakrishnan Kannan, Cristina Garcia-Cardona, Balasubramaniam Radhakrishnan, Sudip K. Seal:
A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations. IEEE Big Data 2023: 1744-1753 - Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park:
Distributed-Memory Parallel JointNMF. ICS 2023: 301-312 - Tianle Wang, Sudip K. Seal, Ramakrishnan Kannan, Cristina Garcia-Cardona, Thomas Proffen, Shantenu Jha:
A Parallel Machine Learning Workflow for Neutron Scattering Data Analysis. IPDPS Workshops 2023: 795-798 - Naoki Abe, Kathleen Buckingham, Yuzhou Chen, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, Yulia R. Gel, James Hodson, Ramakrishnan Kannan, Huikyo Lee, Jiafu Mao, Rose Yu:
Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond. KDD 2023: 5845-5846 - Hao Lu, Piyush Sao, Michael A. Matheson, Ramakrishnan Kannan, Feiyi Wang, Thomas E. Potok:
Optimizing Communication in 2D Grid-Based MPI Applications at Exascale. EuroMPI 2023: 9:1-9:11 - 2022
- Rathimala Kannan, Khor Woon Shing, Kannan Ramakrishnan, Hway Boon Ong, Andry Alamsyah:
Machine Learning Models for Predicting Financially Vigilant Low-Income Households. IEEE Access 10: 70418-70427 (2022) - Rathimala Kannan, Haq'ul Aqif Abdul Halim, Kannan Ramakrishnan, Shahrinaz Ismail, Dedy Rahman Wijaya:
Machine learning approach for predicting production delays: a quarry company case study. J. Big Data 9(1): 94 (2022) - Ananth Hari Ramakrishnan, Muthaiah Rajappa, Kannan Krithivasan, Panagiotis E. Chatzistergos, Nachiappan Chockalingam, Madhusudhana Rao Nalluri:
A concept for movement-based computerized segmentation of connective tissue in ultrasound imaging. Multim. Tools Appl. 81(26): 38053-38066 (2022) - Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu:
MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning. IEEE Big Data 2022: 1936-1941 - Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu:
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice. KDD 2022: 4866-4867 - 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:
Exaflops Biomedical Knowledge Graph Analytics. SC 2022: 6:1-6:11 - Khalid Ibrahim Adem, Ramakrishnan Kannan, Kousalya Govardhanan, Rathimala Kannan:
Taking facial expression recognition outside the lab and into the wild by using challenging datasets and improved performance metrics. F1000Research 11: 349 (2022) - 2021
- Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - Srinivas Eswar, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park:
ORCA: Outlier detection and Robust Clustering for Attributed graphs. J. Glob. Optim. 81(4): 967-989 (2021) - Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park:
PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints. ACM Trans. Math. Softw. 47(3): 20:1-20:37 (2021) - Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru:
Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors. ACDA 2021: 193-204 - Rathakrishnan Bhaskaran, Ramakrishnan Kannan, Brian Barr, Stephan Priebe:
Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation. IEEE BigData 2021: 1809-1816 - Seung-Hwan Lim, Junghoon Chae, Guojing Cong, Drahomira Herrmannova, Robert M. Patton, Ramakrishnan Kannan, Thomas E. Potok:
Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis. IEEE BigData 2021: 4381-4386 - Piyush Sao, Hao Lu, Ramakrishnan Kannan, Vijay Thakkar, Richard W. Vuduc, Thomas E. Potok:
Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters. HPDC 2021: 121-131 - S. M. Shamimul Hasan, Neena Imam, Ramakrishnan Kannan, Srikanth B. Yoginath, Kuldeep R. Kurte:
Design Space Exploration of Emerging Memory Technologies for Machine Learning Applications. IPDPS Workshops 2021: 439-448 - Kuldeep R. Kurte, Neena Imam, Ramakrishnan Kannan, S. M. Shamimul Hasan, Srikanth B. Yoginath:
Co-design of Advanced Architectures for Graph Analytics using Machine Learning. IPDPS Workshops 2021: 298-307 - Catherine D. Schuman, Bill Kay, Prasanna Date, Ramakrishnan Kannan, Piyush Sao, Thomas E. Potok:
Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers. IPDPS Workshops 2021: 308-311 - Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan:
Fragile Earth: Accelerating Progress towards Equitable Sustainability. KDD 2021: 4102-4103 - Nathalie Rauschmayr, Vikas Kumar, Rahul Huilgol, Andrea Olgiati, Satadal Bhattacharjee, Nihal Harish, Vandana Kannan, Amol Lele, Anirudh Acharya, Jared Nielsen, Lakshmi Ramakrishnan, Ishan Bhatt, Kohen Chia, Neelesh Dodda, Zhihan Li, Jiacheng Gu, Miyoung Choi, Balajee Nagarajan, Jeffrey Geevarghese, Denis Davydenko, Sifei Li, Lu Huang, Edward Kim, Tyler Hill, Krishnaram Kenthapadi:
Amazon SageMaker Debugger: A System for Real-Time Insights into Machine Learning Model Training. MLSys 2021
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