Ramakrishnan Kannan

According to our database, Ramakrishnan Kannan authored at least 69 papers between 2007 and 2024.

Collaborative distances:

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

2024

Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation.

Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Sparse Symmetric Format for Tucker Decomposition.

Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru

IEEE Trans. Parallel Distributed Syst., June, 2023

Optimizing Communication in 2D Grid-Based MPI Applications at Exascale.

Hao Lu, Piyush Sao, Michael A. Matheson, Ramakrishnan Kannan, Feiyi Wang, Thomas E. Potok

Proceedings of the 30th European MPI Users' Group Meeting, 2023

Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond.

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

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

A Parallel Machine Learning Workflow for Neutron Scattering Data Analysis.

Tianle Wang, Sudip K. Seal, Ramakrishnan Kannan, Cristina Garcia-Cardona, Thomas Proffen, Shantenu Jha

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

Distributed-Memory Parallel JointNMF.

Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard W. Vuduc, Haesun Park

Proceedings of the 37th International Conference on Supercomputing, 2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations.

Ramakrishnan Kannan, Cristina Garcia-Cardona, Balasubramaniam Radhakrishnan, Sudip K. Seal

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Taking facial expression recognition outside the lab and into the wild by using challenging datasets and improved performance metrics.

Khalid Ibrahim Adem, Ramakrishnan Kannan, Kousalya Govardhanan, Rathimala Kannan

F1000Research, 2022

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

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice.

Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan, Rose Yu

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

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning.

Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park

ACM Trans. Math. Softw., 2021

ORCA: Outlier detection and Robust Clustering for Attributed graphs.

Srinivas Eswar, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park

J. Glob. Optim., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

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 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

Int. J. High Perform. Comput. Appl., 2021

COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques.

Rathimala Kannan, Ivan Zhi Wei Wang, Hway Boon Ong, Ramakrishnan Kannan, Andry Alamsyah

F1000Research, 2021

Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction.

Rathimala Kannan, Yonesh Reddiar, Ramakrishnan Kannan, Marrynal S. Eastaff, Shobana Ramesh

F1000Research, 2021

Randomized Algorithms for Scientific Computing (RASC).

Aydin Buluç, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony M. DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary L. Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna L. Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart

CoRR, 2021

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing.

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

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

Fragile Earth: Accelerating Progress towards Equitable Sustainability.

Naoki Abe, Kathleen Buckingham, Bistra Dilkina, Emre Eftelioglu, Auroop R. Ganguly, James Hodson, Ramakrishnan Kannan

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

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers.

Catherine D. Schuman, Bill Kay, Prasanna Date, Ramakrishnan Kannan, Piyush Sao, Thomas E. Potok

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Co-design of Advanced Architectures for Graph Analytics using Machine Learning.

Kuldeep R. Kurte, Neena Imam, Ramakrishnan Kannan, S. M. Shamimul Hasan, Srikanth B. Yoginath

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Design Space Exploration of Emerging Memory Technologies for Machine Learning Applications.

S. M. Shamimul Hasan, Neena Imam, Ramakrishnan Kannan, Srikanth B. Yoginath, Kuldeep R. Kurte

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters.

Piyush Sao, Hao Lu, Ramakrishnan Kannan, Vijay Thakkar, Richard W. Vuduc, Thomas E. Potok

Proceedings of the HPDC '21: The 30th International Symposium on High-Performance Parallel and Distributed Computing, 2021

Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis.

Seung-Hwan Lim, Junghoon Chae, Guojing Cong, Drahomira Herrmannova, Robert M. Patton, Ramakrishnan Kannan, Thomas E. Potok

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

Science-Guided Machine Learning for Wall-Modeled Large Eddy Simulation.

Rathakrishnan Bhaskaran, Ramakrishnan Kannan, Brian Barr, Stephan Priebe

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

Efficient Parallel Sparse Symmetric Tucker Decomposition for High-Order Tensors.

Shruti Shivakumar, Jiajia Li, Ramakrishnan Kannan, Srinivas Aluru

Proceedings of the 2021 SIAM Conference on Applied and Computational Discrete Algorithms, 2021

2020

Distributed Bayesian optimization of deep reinforcement learning algorithms.

M. Todd Young, Jacob D. Hinkle, Ramakrishnan Kannan, Arvind Ramanathan

J. Parallel Distributed Comput., 2020

Scalable knowledge graph analytics at 136 petaflop/s.

Ramakrishnan Kannan, Piyush Sao, Hao Lu, Drahomira Herrmannova, Vijay Thakkar, Robert M. Patton, Richard W. Vuduc, Thomas E. Potok

Proceedings of the International Conference for High Performance Computing, 2020

Distributed-memory parallel symmetric nonnegative matrix factorization.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Richard W. Vuduc, Haesun Park

Proceedings of the International Conference for High Performance Computing, 2020

A supernodal all-pairs shortest path algorithm.

Piyush Sao, Ramakrishnan Kannan, Prasun Gera, Richard W. Vuduc

Proceedings of the PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020

Tensorized Feature Spaces for Feature Explosion.

Ravdeep S. Pasricha, Pravallika Devineni, Evangelos E. Papalexakis, Ramakrishnan Kannan

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Parallel Hierarchical Clustering using Rank-Two Nonnegative Matrix Factorization.

Lawton Manning, Grey Ballard, Ramakrishnan Kannan, Haesun Park

Proceedings of the 27th IEEE International Conference on High Performance Computing, 2020

Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach.

Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Sudip K. Seal

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

INDEX-db: The Indian Exome Reference Database (Phase I).

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

J. Comput. Biol., 2019

PLANC: Parallel Low Rank Approximation with Non-negativity Constraints.

Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park

CoRR, 2019

Multifrontal Non-negative Matrix Factorization.

Piyush Sao, Ramakrishnan Kannan

Proceedings of the Parallel Processing and Applied Mathematics, 2019

A communication-avoiding 3D sparse triangular solver.

Piyush Sao, Ramakrishnan Kannan, Xiaoye Sherry Li, Richard W. Vuduc

Proceedings of the ACM International Conference on Supercomputing, 2019

A Scalable Graph Analytics Framework for Programming with Big Data in R (pbdR).

S. M. Shamimul Hasan, Drew Schmidt, Ramakrishnan Kannan, Neena Imam

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Learning to Predict Material Structure from Neutron Scattering Data.

Cristina Garcia-Cardona, Ramakrishnan Kannan, Travis Johnston, Thomas Proffen, Katharine Page, Sudip K. Seal

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization.

Ramakrishnan Kannan, Grey Ballard, Haesun Park

IEEE Trans. Knowl. Data Eng., 2018

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data.

Jaegul Choo, Hannah Kim, Edward Clarkson, Zhicheng Liu, Changhyun Lee, Fuxin Li, Hanseung Lee, Ramakrishnan Kannan, Charles D. Stolper, John T. Stasko, Haesun Park

ACM Trans. Knowl. Discov. Data, 2018

HyperSpace: Distributed Bayesian Hyperparameter Optimization.

M. Todd Young, Jacob D. Hinkle, Arvind Ramanathan, Ramakrishnan Kannan

Proceedings of the 30th International Symposium on Computer Architecture and High Performance Computing, 2018

Partitioning and Communication Strategies for Sparse Non-negative Matrix Factorization.

Oguz Kaya, Ramakrishnan Kannan, Grey Ballard

Proceedings of the 47th International Conference on Parallel Processing, 2018

Parallel Nonnegative CP Decomposition of Dense Tensors.

Grey Ballard, Koby Hayashi, Ramakrishnan Kannan

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

A Heterogeneity-Aware Task Scheduler for Spark.

Luna Xu, Ali Raza Butt, Seung-Hwan Lim, Ramakrishnan Kannan

Proceedings of the IEEE International Conference on Cluster Computing, 2018

TopicOnTiles: Tile-Based Spatio-Temporal Event Analytics via Exclusive Topic Modeling on Social Media.

Minsuk Choi, Dear Sungbok Shin, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Barry L. Drake, Haesun Park, Jaegul Choo

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 2018

A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases.

Md Mosharaf Hossain, Thomas M. Hines, Sheikh K. Ghafoor, Sheikh Rabiul Islam, Ramakrishnan Kannan, Sreenivas R. Sukumar

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

CBIR System Based On Prediction Errors.

C. Eswaran, Ramakrishnan Kannan, A. Mohamed Uvaze Ahamed

J. Inf. Sci. Eng., 2017

Lossy image compression based on prediction error and vector quantisation.

A. Mohamed Uvaze Ahamed, Eswaran Chikkannan, Ramakrishnan Kannan

EURASIP J. Image Video Process., 2017

Outlier Detection for Text Data : An Extended Version.

Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park

CoRR, 2017

Outlier Detection for Text Data.

Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

STExNMF: Spatio-Temporally Exclusive Topic Discovery for Anomalous Event Detection.

Dear Sungbok Shin, Minsuk Choi, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Barry L. Drake, Haesun Park, Jaegul Choo

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Scaling up data-parallel analytics platforms: Linear algebraic operation cases.

Luna Xu, Seung-Hwan Lim, Min Li, Ali Raza Butt, Ramakrishnan Kannan

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

FatMan vs. LittleBoy: Scaling Up Linear Algebraic Operations in Scale-Out Data Platforms.

Luna Xu, Seung-Hwan Lim, Ali Raza Butt, Sreenivas R. Sukumar, Ramakrishnan Kannan

Proceedings of the 1st Joint International Workshop on Parallel Data Storage and data Intensive Scalable Computing Systems, 2016

A high-performance parallel algorithm for nonnegative matrix factorization.

Ramakrishnan Kannan, Grey Ballard, Haesun Park

Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2016

Mini-apps for high performance data analysis.

Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Kernels for scalable data analysis in science: Towards an architecture-portable future.

Sreenivas R. Sukumar, Ramakrishnan Kannan, Seung-Hwan Lim, Michael A. Matheson

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Behavioral clusters in dynamic graphs.

James P. Fairbanks, Ramakrishnan Kannan, Haesun Park, David A. Bader

Parallel Comput., 2015

2014

Bounded matrix factorization for recommender system.

Ramakrishnan Kannan, Mariya Ishteva, Haesun Park

Knowl. Inf. Syst., 2014

VisIRR: Visual analytics for information retrieval and recommendation with large-scale document data.

Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Zhicheng Liu, Ramakrishnan Kannan, Charles D. Stolper, John T. Stasko, Barry L. Drake, Haesun Park

Proceedings of the 9th IEEE Conference on Visual Analytics Science and Technology, 2014

A Dynamic Data Driven Application System for Vehicle Tracking.

Richard Fujimoto, Angshuman Guin, Michael Hunter, Haesun Park, Gaurav Kanitkar, Ramakrishnan Kannan, Michael Milholen, Sabra Neal, Philip Pecher

Proceedings of the International Conference on Computational Science, 2014

2012

Bounded Matrix Low Rank Approximation.

Ramakrishnan Kannan, Mariya Ishteva, Haesun Park

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011

Fast Rule Mining Over Multi-Dimensional Windows.

Mahashweta Das, Deepak Padmanabhan, Prasad Deshpande, Ramakrishnan Kannan

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce.

Amol Ghoting, Prabhanjan Kambadur, Edwin P. D. Pednault, Ramakrishnan Kannan

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2009

Nash Bargaining Based Ad Networks for Sponsored Search Auctions.

Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari

Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing, 2009

CRM Analytics Framework.

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

Proceedings of the 15th International Conference on Management of Data, 2009

2008

A Nash bargaining approach to retention enhancing bid optimization in sponsored search auctions with discrete bids.

Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Yadati Narahari

Proceedings of the 2008 IEEE International Conference on Automation Science and Engineering, 2008

2007

Lossless Compression Schemes for ECG Signals Using Neural Network Predictors.

Ramakrishnan Kannan, C. Eswaran

EURASIP J. Adv. Signal Process., 2007

Incentive Compatible Mechanisms for Group Ticket Allocation in Software Maintenance Services.

Karthik Subbian, Ramakrishnan Kannan, Raghav Kumar Gautam, Y. Narahari

Proceedings of the 14th Asia-Pacific Software Engineering Conference (APSEC 2007), 2007