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bibtex list 

de Mesmay, Frédéric 

  1. 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
  2. Frédéric de Mesmay
    On the Computer Generation of Adaptive Numerical Libraries
    PhD. thesis, Electrical and Computer Engineering, Carnegie Mellon University, 2010
  3. 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

Johnson, Jeremy 

  1. 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

Krause, Andreas 

  1. 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
  2. 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
  3. 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
  4. 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

Kumhom, Pinit 

  1. 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

Milder, Peter A. 

  1. 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

Nagvajara, Prawat 

  1. 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

Püschel, Markus 

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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

Rimmel, Arpad 

  1. 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

Sergent, Guillaume 

  1. 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

Singer, Bryan 

  1. 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
  2. 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
  3. Bryan Singer
    Automating the Modeling and Optimization of the Performance of Signal Processing Algorithms
    PhD. thesis, Computer Science, Carnegie Mellon University, 2001
  4. Bryan Singer and Manuela Veloso
    Learning to Generate Fast Signal Processing Implementations
    Proc. International Conference on Machine Learning (ICML), pp. 529-536, 2001
  5. Bryan Singer and Manuela Veloso
    Stochastic Search for Signal Processing Algorithm Optimization
    Proc. Supercomputing (SC), pp. 22, 2001
  6. 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

Veloso, Manuela 

  1. 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
  2. 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
  3. Bryan Singer and Manuela Veloso
    Learning to Generate Fast Signal Processing Implementations
    Proc. International Conference on Machine Learning (ICML), pp. 529-536, 2001
  4. Bryan Singer and Manuela Veloso
    Stochastic Search for Signal Processing Algorithm Optimization
    Proc. Supercomputing (SC), pp. 22, 2001
  5. 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

Voronenko, Yevgen 

  1. 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
  2. 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

Zuluaga, Marcela 

  1. 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
  2. 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
  3. 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
  4. 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
Publication interface designed and implemented by Patra Pantupat, Aliaksei Sandryhaila, and Markus Püschel
Electrical and Computer Engineering, Carnegie Mellon University, 2007