- David Grochol, Lukás Sekanina:
Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing. CEC 2020: 1-8 - Jakub Husa, Lukás Sekanina:
Evolving Cryptographic Boolean Functions with Minimal Multiplicative Complexity. CEC 2020: 1-8 - Bharath Srinivas Prabakaran, Vojtech Mrazek
, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique:
ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems. DAC 2020: 1-6 - Filip Vaverka, Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina:
TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU. DATE 2020: 294-297 - Alberto Bosio, Stefano Di Carlo, Patrick Girard, Ernesto Sánchez, Alessandro Savino, Lukás Sekanina, Marcello Traiola, Zdenek Vasícek, Arnaud Virazel:
Design, Verification, Test and In-Field Implications of Approximate Computing Systems. ETS 2020: 1-10 - Filip Vaverka, Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina:
TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU. CoRR abs/2002.09481 (2020) - Milan Ceska, Jirí Matyás, Vojtech Mrazek, Lukás Sekanina, Zdenek Vasícek, Tomás Vojnar:
Adaptive Verifiability-Driven Strategy for Evolutionary Approximation of Arithmetic Circuits. CoRR abs/2003.02491 (2020) - Vojtech Mrazek, Lukás Sekanina, Zdenek Vasícek:
Using Libraries of Approximate Circuits in Design of Hardware Accelerators of Deep Neural Networks. CoRR abs/2004.10483 (2020) - Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique:
ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems. CoRR abs/2004.10502 (2020) - 2019
- Michaela Drahosova, Lukás Sekanina, Michal Wiglasz:
Adaptive Fitness Predictors in Coevolutionary Cartesian Genetic Programming. Evol. Comput. 27(3): 497-523 (2019) - Vojtech Mrazek, Lukás Sekanina, Roland Dobai, Marek Sýs, Petr Svenda:
Efficient On-Chip Randomness Testing Utilizing Machine Learning Techniques. IEEE Trans. Very Large Scale Integr. Syst. 27(12): 2734-2744 (2019) - Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique:
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components. DAC 2019: 123 - Petr Rek, Lukás Sekanina:
TypeCNN: CNN Development Framework With Flexible Data Types. DATE 2019: 292-295 - Zdenek Vasícek, Vojtech Mrazek, Lukás Sekanina:
Automated Circuit Approximation Method Driven by Data Distribution. DATE 2019: 96-101 - Ondrej Koncal, Lukás Sekanina:
Cartesian Genetic Programming as an Optimizer of Programs Evolved with Geometric Semantic Genetic Programming. EuroGP 2019: 98-113 - Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Muhammad Abdullah Hanif, Muhammad Shafique:
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining. ICCAD 2019: 1-8 - Zoran Stamenkovic, Alberto Bosio, György Cserey, Ondrej Novák, Witold A. Pleskacz, Lukás Sekanina, Andreas Steininger, Goran Stojanovic, Viera Stopjaková:
International Symposium on Design and Diagnostics of Electronic Circuits and Systems. ITC 2019: 1-4 - Filip Badan, Lukás Sekanina:
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution. TPNC 2019: 109-121 - Lukás Sekanina, Zdenek Vasícek, Vojtech Mrazek:
Automated Search-Based Functional Approximation for Digital Circuits. Approximate Circuits 2019: 175-203 - Lukás Sekanina, Ting Hu, Nuno Lourenço, Hendrik Richter, Pablo García-Sánchez:
Genetic Programming - 22nd European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24-26, 2019, Proceedings. Lecture Notes in Computer Science 11451, Springer 2019, ISBN 978-3-030-16669-4 [contents] - Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique:
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components. CoRR abs/1902.10807 (2019) - Zdenek Vasícek, Vojtech Mrazek, Lukás Sekanina:
Automated Circuit Approximation Method Driven by Data Distribution. CoRR abs/1903.04188 (2019) - Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Muhammad Abdullah Hanif, Muhammad Shafique:
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining. CoRR abs/1907.07229 (2019) - Filip Badan, Lukás Sekanina:
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution. CoRR abs/1910.06854 (2019) - 2018
- Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Honglan Jiang, Jie Han:
Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error. IEEE Trans. Very Large Scale Integr. Syst. 26(11): 2572-2576 (2018) - David Grochol, Lukás Sekanina:
Fast Reconfigurable Hash Functions for Network Flow Hashing in FPGAs. AHS 2018: 257-263 - Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina:
Design of Quality-Configurable Approximate Multipliers Suitable for Dynamic Environment. AHS 2018: 264-271 - Milan Ceska, Jirí Matyás, Vojtech Mrazek, Lukás Sekanina, Zdenek Vasícek, Tomás Vojnar:
ADAC: Automated Design of Approximate Circuits. CAV (1) 2018: 612-620 - David Grochol, Lukás Sekanina:
Multi-objective Evolution of Ultra-Fast General-Purpose Hash Functions. EuroGP 2018: 187-202 - Vojtech Mrazek, Marek Sýs, Zdenek Vasícek, Lukás Sekanina, Vashek Matyas:
Evolving boolean functions for fast and efficient randomness testing. GECCO 2018: 1302-1309
