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Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations


May 10, 2021
Jaehoon Koo, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul Hovland, Mary Hall


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Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version)


Apr 27, 2021
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul Hovland, Valerie Taylor, Mary Hall

* Submitted to CCPE journal. arXiv admin note: substantial text overlap with arXiv:2010.08040 

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Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics


Feb 24, 2021
Jongeun Kim, Sven Leyffer, Prasanna Balaprakash


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Learning-Based Distributed Random Access for Multi-Cell IoT Networks with NOMA


Jan 02, 2021
Sami Khairy, Prasanna Balaprakash, Lin X. Cai, H. Vincent Poor

* Submitted to the JSAC Series on Machine Learning for Communications and Networks 

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AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data


Oct 30, 2020
Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu


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Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization


Oct 15, 2020
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul Hovland, Valerie Taylor, Mary Hall

* to be published in the 11th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS20) 

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Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks


Aug 28, 2020
Tanwi Mallick, Mariam Kiran, Bashir Mohammed, Prasanna Balaprakash

* 10 Pages, 11 Figures 

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Graph Neural Network Architecture Search for Molecular Property Prediction


Aug 27, 2020
Shengli Jiang, Prasanna Balaprakash


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Meta Continual Learning via Dynamic Programming


Aug 05, 2020
R. Krishnan, Prasanna Balaprakash


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Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning


Jul 16, 2020
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash


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A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes


May 07, 2020
Sami Khairy, Prasanna Balaprakash, Lin X. Cai

* Submitted as a brief paper to the IEEE TNNLS 

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Towards On-Chip Bayesian Neuromorphic Learning


May 05, 2020
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia


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Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting


Apr 20, 2020
Tanwi Mallick, Prasanna Balaprakash, Eric Rask, Jane Macfarlane


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Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV based Random Access IoT Networks with NOMA


Feb 05, 2020
Sami Khairy, Prasanna Balaprakash, Lin X. Cai, Yu Cheng

* Submitted to IEEE JSAC Special Issue on Massive Access for 5G and Beyond 

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Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems


Nov 25, 2019
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash

* To appear in the proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), New York, USA, February 2020 

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Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems


Nov 11, 2019
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash


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Value-Added Chemical Discovery Using Reinforcement Learning


Nov 10, 2019
Peihong Jiang, Hieu Doan, Sandeep Madireddy, Rajeev Surendran Assary, Prasanna Balaprakash


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Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images


Nov 10, 2019
Sandeep Madireddy, Nan Li, Nesar Ramachandra, Prasanna Balaprakash, Salman Habib


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Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models


Nov 01, 2019
Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash


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Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting


Oct 01, 2019
Tanwi Mallick, Prasanna Balaprakash, Eric Rask, Jane Macfarlane


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MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles


Sep 22, 2019
Shashi M. Aithal, Prasanna Balaprakash

* In M. Weiland, G. Juckeland, C. Trinitis, and P. Sadayappan, editors, High Performance Computing, pages 186--205, Cham, 2019. Springer International Publishing 

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Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research


Sep 01, 2019
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens

* SC '19: IEEE/ACM International Conference on High Performance Computing, Networking, Storage and Analysis, November 17--22, 2019, Denver, CO 

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Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning


Jun 04, 2019
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash


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Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout


Apr 29, 2019
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia

* 4 pages, 4 figures. Submitted to International Conference on Neuromorphic Systems (ICONS) 2019 

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