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Search/Learning for optimization
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bibtex list
- Marcela Zuluaga, Andreas Krause and Markus Püschel
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem
Journal of Machine Learning Research, Vol. 17, No. 104, pp. 1-32, 2016
- Marcela Zuluaga, Andreas Krause, Guillaume Sergent and Markus Püschel
Active Learning for Multi-Objective Optimization
Proc. International Conference on Machine Learning (ICML), pp. 462-470, 2013
- Marcela Zuluaga, Andreas Krause and Markus Püschel
Multi-Objective Optimization for High-Level Synthesis
Proc. Workshop on High-Level Synthesis for High Performance Computing (HLS4HPC), 2013
- Marcela Zuluaga, Andreas Krause, Peter A. Milder and Markus Püschel
"Smart" Design Space Sampling to Predict Pareto-Optimal Solutions
Proc. Languages, Compilers, Tools and Theory for Embedded Systems (LCTES), pp. 119-128 , 2012
- Frédéric de Mesmay, Yevgen Voronenko and Markus Püschel
Offline Library Adaptation Using Automatically Generated Heuristics
Proc. IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 1-10, 2010
- Frédéric de Mesmay
On the Computer Generation of Adaptive Numerical Libraries
PhD. thesis, Electrical and Computer Engineering, Carnegie Mellon University, 2010
- Frédéric de Mesmay, Arpad Rimmel, Yevgen Voronenko and Markus Püschel
Bandit-Based Optimization on Graphs with Application to Library Performance Tuning
Proc. International Conference on Machine Learning (ICML), pp. 729-736, 2009
- Bryan Singer and Manuela Veloso
Automating the Modeling and Optimization of the Performance of Signal Transforms
IEEE Transactions on Signal Processing, Vol. 50, No. 8, pp. 2003-2014, 2002
- Bryan Singer and Manuela Veloso
Learning to Construct Fast Signal Processing Implementations
Journal of Machine Learning Research, special issue on ``the Eighteenth International Conference on Machine Learning (ICML 2001)'', Vol. 3, pp. 887-919, 2002
- Bryan Singer
Automating the Modeling and Optimization of the Performance of Signal Processing Algorithms
PhD. thesis, Computer Science, Carnegie Mellon University, 2001
- Bryan Singer and Manuela Veloso
Learning to Generate Fast Signal Processing Implementations
Proc. International Conference on Machine Learning (ICML), pp. 529-536, 2001
- Bryan Singer and Manuela Veloso
Stochastic Search for Signal Processing Algorithm Optimization
Proc. Supercomputing (SC), pp. 22, 2001
- Pinit Kumhom, Jeremy Johnson and Prawat Nagvajara
Design, optimization, and implementation of a universal FFT processor
Proc. IEEE ASIC/SOC Conference, IEEE, pp. 182-186, 2000
- Bryan Singer and Manuela Veloso
Learning to Predict Performance from Formula Modeling and Training Data
Proc. International Conference on Machine Learning (ICML), pp. 887-894, 2000
