Ramakrishnan Kannan

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 63

Top Topics

Machine Learning

Money Laundering

Matrix Factorization

Top Venues

IPDPS Workshops

Publications

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)
Zhi-Feng Wei, Pablo Moriano, Ramakrishnan Kannan
Robustness of graph embedding methods for community detection. CoRR (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. CoRR (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)
Yongseok Soh, Ramakrishnan Kannan, Piyush Sao, Jee W. Choi
Accelerated Constrained Sparse Tensor Factorization on Massively Parallel Architectures. ICPP (2024)
Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru
Sparse Symmetric Format for Tucker Decomposition. IEEE Trans. Parallel Distributed Syst. 34 (6) (2023)
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)
Ramakrishnan Kannan, Cristina Garcia-Cardona, Balasubramaniam Radhakrishnan, Sudip K. Seal
A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations. BigData (2023)
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)
Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park
Distributed-Memory Parallel JointNMF. ICS (2023)
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)
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)
Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu
MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning. Big Data (2022)
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 (2022)
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)
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)
Rathimala Kannan, Ivan Zhi Wei Wang, Hway Boon Ong, Ramakrishnan Kannan, Andry Alamsyah
COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques. F1000Research 10 (2021)
Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC (2021)
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)
Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan
Fragile Earth: Accelerating Progress towards Equitable Sustainability. KDD (2021)
Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru
Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors. ACDA (2021)
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)
Francis J. Alexander, James 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 Ramakrishniah, 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) (2021)
Aydin Buluç, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna L. Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart
Randomized Algorithms for Scientific Computing (RASC). CoRR (2021)
Srinivas Eswar, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park
ORCA: Outlier detection and Robust Clustering for Attributed graphs. J. Glob. Optim. 81 (4) (2021)
Rathakrishnan Bhaskaran, Ramakrishnan Kannan, Brian Barr, Stephan Priebe
Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation. IEEE BigData (2021)
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)
Rathimala Kannan, Yonesh Reddiar, Ramakrishnan Kannan, Marrynal S. Eastaff, Shobana Ramesh
Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction. F1000Research 10 (2021)
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)
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) (2021)
Ravdeep S. Pasricha, Pravallika Devineni, Evangelos E. Papalexakis, Ramakrishnan Kannan
Tensorized Feature Spaces for Feature Explosion. ICPR (2020)
Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park
Distributed-memory parallel symmetric nonnegative matrix factorization. SC (2020)
Piyush Sao, Ramakrishnan Kannan, Prasun Gera, Richard W. Vuduc
A supernodal all-pairs shortest path algorithm. PPoPP (2020)
Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Sudip K. Seal
Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach. IEEE BigData (2020)
Ramakrishnan Kannan, Piyush Sao, Hao Lu, Drahomira Herrmannova, Vijay Thakkar, Robert M. Patton, Richard W. Vuduc, Thomas E. Potok
Scalable knowledge graph analytics at 136 petaflop/s. SC (2020)
M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan
Distributed Bayesian optimization of deep reinforcement learning algorithms. J. Parallel Distributed Comput. 139 (2020)
Lawton Manning, Grey Ballard, Ramakrishnan Kannan, Haesun Park
Parallel Hierarchical Clustering using Rank-Two Nonnegative Matrix Factorization. HiPC (2020)
Piyush Sao, Ramakrishnan Kannan
Multifrontal Non-negative Matrix Factorization. PPAM (1) (2019)
S. M. Shamimul Hasan, Drew Schmidt, Ramakrishnan Kannan, Neena Imam
A Scalable Graph Analytics Framework for Programming with Big Data in R (pbdR). IEEE BigData (2019)
Husayn Ahmed P., Vidhya V., Ravi Prabhakar More, Biju Viswanath, Sanjeev Jain, Mahendra S. Rao, Odity Mukherjee, Naren P. Rao, Janardhanan C. Narayanaswamy, Palanimuthu T. Sivakumar, Arun Kandaswamy, Muralidharan Kesavan, Urvakhsh-Meherwan Mehta, Ganesan Venkatasubramanian, John P. John, Meera Purushottam, Ramakrishnan Kannan, Bhupesh Mehta, Thennarasu Kandavel, B. Binukumar, Jitender Saini, Deepak Jayarajan, A. Shyamsundar, Sydney Moirangthem, Kumar G. Vijay, Jagadisha Thirthalli, Prabha S. Chandra, Bangalore N. Gangadhar, Pratima Murthy, Mitradas M. Panicker, Upinder S. Bhalla, Sumantra Chattarji, Vivek Benegal, Mathew Varghese, Janardhan Y. C. Reddy, Padinjat Raghu
INDEX-db: The Indian Exome Reference Database (Phase I). J. Comput. Biol. 26 (3) (2019)
Piyush Sao, Ramakrishnan Kannan, Xiaoye Sherry Li, Richard W. Vuduc
A communication-avoiding 3D sparse triangular solver. ICS (2019)
Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Katharine Page, Sudip K. Seal
Learning to Predict Material Structure from Neutron Scattering Data. IEEE BigData (2019)
Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints. CoRR (2019)
Luna Xu, Ali Raza Butt, Seung-Hwan Lim, Ramakrishnan Kannan
A Heterogeneity-Aware Task Scheduler for Spark. CLUSTER (2018)
Md Mosharaf Hossain, Thomas M. Hines, Sheikh K. Ghafoor, Sheikh Rabiul Islam, Ramakrishnan Kannan, Sreenivas R. Sukumar
A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases. IEEE BigData (2018)
Ramakrishnan Kannan, Grey Ballard, Haesun Park
MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization. IEEE Trans. Knowl. Data Eng. 30 (3) (2018)
Grey Ballard, Koby Hayashi, Ramakrishnan Kannan
Parallel Nonnegative CP Decomposition of Dense Tensors. CoRR (2018)
Jaegul Choo, Hannah Kim, Edward Clarkson, Zhicheng Liu, Changhyun Lee, Fuxin Li, Hanseung Lee, Ramakrishnan Kannan, Charles D. Stolper, John T. Stasko, Haesun Park
VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data. ACM Trans. Knowl. Discov. Data 12 (1) (2018)
Grey Ballard, Koby Hayashi, Ramakrishnan Kannan
Parallel Nonnegative CP Decomposition of Dense Tensors. HiPC (2018)
M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan
HyperSpace: Distributed Bayesian Hyperparameter Optimization. SBAC-PAD (2018)
Oguz Kaya, Ramakrishnan Kannan, Grey Ballard
Partitioning and Communication Strategies for Sparse Non-negative Matrix Factorization. ICPP (2018)
Minsuk Choi, Dear Sungbok Shin, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Barry L. Drake, Haesun Park, Jaegul Choo
TopicOnTiles: Tile-Based Spatio-Temporal Event Analytics via Exclusive Topic Modeling on Social Media. CHI (2018)
C. Eswaran, Ramakrishnan Kannan, A. Mohamed Uvaze Ahamed
CBIR System Based On Prediction Errors. J. Inf. Sci. Eng. 33 (2) (2017)
Luna Xu, Seung-Hwan Lim, Min Li, Ali Raza Butt, Ramakrishnan Kannan
Scaling up data-parallel analytics platforms: Linear algebraic operation cases. IEEE BigData (2017)
Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park
Outlier Detection for Text Data. SDM (2017)
A. Mohamed Uvaze Ahamed, Eswaran Chikkannan, Ramakrishnan Kannan
Lossy image compression based on prediction error and vector quantisation. EURASIP J. Image Video Process. 2017 (2017)
Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park
Outlier Detection for Text Data : An Extended Version. CoRR (2017)
Dear Sungbok Shin, Minsuk Choi, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Barry L. Drake, Haesun Park, Jaegul Choo
STExNMF: Spatio-Temporally Exclusive Topic Discovery for Anomalous Event Detection. ICDM (2017)
Ramakrishnan Kannan, Grey Ballard, Haesun Park
MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization. CoRR (2016)
Luna Xu, Seung-Hwan Lim, Ali Raza Butt, Sreenivas R. Sukumar, Ramakrishnan Kannan
FatMan vs. LittleBoy: Scaling Up Linear Algebraic Operations in Scale-Out Data Platforms. PDSW-DISCS@SC (2016)
Ramakrishnan Kannan, Grey Ballard, Haesun Park
A high-performance parallel algorithm for nonnegative matrix factorization. PPOPP (2016)
Sreenivas R. Sukumar, Ramakrishnan Kannan, Seung-Hwan Lim, Michael A. Matheson
Kernels for scalable data analysis in science: Towards an architecture-portable future. IEEE BigData (2016)
Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim
Mini-apps for high performance data analysis. IEEE BigData (2016)
Ramakrishnan Kannan, Grey Ballard, Haesun Park
A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization. CoRR (2015)
James P. Fairbanks, Ramakrishnan Kannan, Haesun Park, David A. Bader
Behavioral clusters in dynamic graphs. Parallel Comput. 47 (2015)
Richard Fujimoto, Angshuman Guin, Michael Hunter, Haesun Park, Gaurav Kanitkar, Ramakrishnan Kannan, Michael Milholen, Sabra Neal, Philip Pecher
A Dynamic Data Driven Application System for Vehicle Tracking. ICCS (2014)
Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Zhicheng Liu, Ramakrishnan Kannan, Charles D. Stolper, John T. Stasko, Barry L. Drake, Haesun Park
VisIRR: Visual analytics for information retrieval and recommendation with large-scale document data. IEEE VAST (2014)
Ramakrishnan Kannan, Mariya Ishteva, Haesun Park
Bounded matrix factorization for recommender system. Knowl. Inf. Syst. 39 (3) (2014)
Ramakrishnan Kannan, Mariya Ishteva, Haesun Park
Bounded Matrix Low Rank Approximation. ICDM (2012)
Amol Ghoting, Prabhanjan Kambadur, Edwin P. D. Pednault, Ramakrishnan Kannan
NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce. KDD (2011)
Mahashweta Das, Deepak Padmanabhan, Prasad Deshpande, Ramakrishnan Kannan
Fast Rule Mining Over Multi-Dimensional Windows. SDM (2011)
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari
Nash Bargaining Based Ad Networks for Sponsored Search Auctions. CEC (2009)
Joseph P. Bigus, Upendra Chitnis, Prasad M. Deshpande, Ramakrishnan Kannan, Mukesh K. Mohania, Sumit Negi, Deepak Padmanabhan, Edwin P. D. Pednault, Soujanya Soni, Bipen K. Telkar, Brian F. White
CRM Analytics Framework. COMAD (2009)
Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Yadati Narahari
A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids. CASE (2008)
Ramakrishnan Kannan, C. Eswaran
Lossless Compression Schemes for ECG Signals Using Neural Network Predictors. EURASIP J. Adv. Signal Process. 2007 (2007)
Karthik Subbian, Ramakrishnan Kannan, Raghav Kumar Gautam, Y. Narahari
Incentive Compatible Mechanisms for Group Ticket Allocation in Software Maintenance Services. APSEC (2007)