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Dorian Florescu
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2020 – today
- 2024
- [c12]Dorian Florescu, Matthew England:
Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems. ICMS 2024: 186-195 - [i9]Dorian Florescu, Matthew England:
Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems. CoRR abs/2404.17508 (2024) - 2023
- [j6]Gal Shtendel
, Dorian Florescu
, Ayush Bhandari
:
Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling. IEEE Trans. Signal Process. 71: 4134-4145 (2023) - [i8]Gal Shtendel, Dorian Florescu, Ayush Bhandari:
Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling. CoRR abs/2307.04917 (2023) - 2022
- [j5]Dorian Florescu
, Felix Krahmer
, Ayush Bhandari
:
The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments. IEEE Trans. Signal Process. 70: 616-630 (2022) - [j4]Dorian Florescu
, Ayush Bhandari
:
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation. IEEE Trans. Signal Process. 70: 4912-4924 (2022) - [c11]Dorian Florescu, Ayush Bhandari:
Unlimited Sampling with Local Averages. ICASSP 2022: 5742-5746 - [c10]Dorian Florescu, Ayush Bhandari:
Modulo Event-Driven Sampling: System Identification and Hardware Experiments. ICASSP 2022: 5747-5751 - [c9]Dorian Florescu, Ayush Bhandari:
Unlimited Sampling via Generalized Thresholding. ISIT 2022: 1606-1611 - [i7]Dorian Florescu, Ayush Bhandari:
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation. CoRR abs/2208.10234 (2022) - [i6]Dorian Florescu, Ayush Bhandari:
Multi-Dimensional Unlimited Sampling and Robust Reconstruction. CoRR abs/2209.06426 (2022) - 2021
- [c8]Dorian Florescu, Felix Krahmer, Ayush Bhandari:
Unlimited Sampling with Hysteresis. ACSCC 2021: 831-835 - [c7]Dorian Florescu, Felix Krahmer, Ayush Bhandari:
Event-Driven Modulo Sampling. ICASSP 2021: 5435-5439 - [i5]Dorian Florescu, Felix Krahmer, Ayush Bhandari:
The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments. CoRR abs/2111.12675 (2021) - 2020
- [c6]Dorian Florescu, Matthew England:
A Machine Learning Based Software Pipeline to Pick the Variable Ordering for Algorithms with Polynomial Inputs. ICMS 2020: 302-311 - [i4]Dorian Florescu, Matthew England:
A machine learning based software pipeline to pick the variable ordering for algorithms with polynomial inputs. CoRR abs/2005.11251 (2020)
2010 – 2019
- 2019
- [j3]Dorian Florescu, Daniel Coca
:
Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines. Neural Comput. 31(9): 1825-1852 (2019) - [c5]Dorian Florescu, Matthew England:
Improved Cross-Validation for Classifiers that Make Algorithmic Choices to Minimise Runtime Without Compromising Output Correctness. MACIS 2019: 341-356 - [c4]Matthew England, Dorian Florescu:
Machine Learning to Improve Cylindrical Algebraic Decomposition in Maple. MC 2019: 330-333 - [c3]Matthew England
, Dorian Florescu:
Comparing Machine Learning Models to Choose the Variable Ordering for Cylindrical Algebraic Decomposition. CICM 2019: 93-108 - [c2]Dorian Florescu, Matthew England:
Algorithmically Generating New Algebraic Features of Polynomial Systems for Machine Learning. SC-square@SIAM AG 2019 - [i3]Matthew England, Dorian Florescu:
Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition. CoRR abs/1904.11061 (2019) - [i2]Dorian Florescu, Matthew England:
Algorithmically generating new algebraic features of polynomial systems for machine learning. CoRR abs/1906.01455 (2019) - [i1]Dorian Florescu, Matthew England:
Improved cross-validation for classifiers that make algorithmic choices to minimise runtime without compromising output correctness. CoRR abs/1911.12672 (2019) - 2018
- [j2]Dorian Florescu, Daniel Coca
:
Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data. Neural Comput. 30(3) (2018) - 2015
- [j1]Dorian Florescu, Daniel Coca
:
A Novel Reconstruction Framework for Time-Encoded Signals with Integrate-and-Fire Neurons. Neural Comput. 27(9): 1872-1898 (2015) - [c1]Dorian Florescu, Daniel Coca:
Implementation of linear filters in the spike domain. ECC 2015: 2298-2302
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last updated on 2024-07-29 21:31 CEST by the dblp team
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