Dorian Florescu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 27

Top Topics

Computer Algebra

Variable Ordering

Conflict Directed

Top Venues

IEEE Trans. Signal Process.

Publications

Dorian Florescu, Matthew England
Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems. CoRR (2024)
Dorian Florescu, Matthew England
Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems. ICMS (2024)
Gal Shtendel, Dorian Florescu, Ayush Bhandari
Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling. CoRR (2023)
Gal Shtendel, Dorian Florescu, Ayush Bhandari
Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling. IEEE Trans. Signal Process. 71 (2023)
Dorian Florescu, Ayush Bhandari
Unlimited Sampling with Local Averages. ICASSP (2022)
Dorian Florescu, Ayush Bhandari
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation. IEEE Trans. Signal Process. 70 (2022)
Dorian Florescu, Felix Krahmer, Ayush Bhandari
The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments. IEEE Trans. Signal Process. 70 (2022)
Dorian Florescu, Ayush Bhandari
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation. CoRR (2022)
Dorian Florescu, Ayush Bhandari
Modulo Event-Driven Sampling: System Identification and Hardware Experiments. ICASSP (2022)
Dorian Florescu, Ayush Bhandari
Multi-Dimensional Unlimited Sampling and Robust Reconstruction. CoRR (2022)
Dorian Florescu, Ayush Bhandari
Unlimited Sampling via Generalized Thresholding. ISIT (2022)
Dorian Florescu, Felix Krahmer, Ayush Bhandari
Unlimited Sampling with Hysteresis. ACSCC (2021)
Dorian Florescu, Felix Krahmer, Ayush Bhandari
Event-Driven Modulo Sampling. ICASSP (2021)
Dorian Florescu, Felix Krahmer, Ayush Bhandari
The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments. CoRR (2021)
Dorian Florescu, Matthew England
A Machine Learning Based Software Pipeline to Pick the Variable Ordering for Algorithms with Polynomial Inputs. ICMS (2020)
Dorian Florescu, Matthew England
A machine learning based software pipeline to pick the variable ordering for algorithms with polynomial inputs. CoRR (2020)
Matthew England, Dorian Florescu
Machine Learning to Improve Cylindrical Algebraic Decomposition in Maple. MC (2019)
Dorian Florescu, Matthew England
Improved Cross-Validation for Classifiers that Make Algorithmic Choices to Minimise Runtime Without Compromising Output Correctness. MACIS (2019)
Dorian Florescu, Matthew England
Algorithmically Generating New Algebraic Features of Polynomial Systems for Machine Learning. SC-square@SIAM AG (2019)
Matthew England, Dorian Florescu
Comparing Machine Learning Models to Choose the Variable Ordering for Cylindrical Algebraic Decomposition. CICM (2019)
Dorian Florescu, Daniel Coca
Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines. Neural Comput. 31 (9) (2019)
Dorian Florescu, Matthew England
Improved cross-validation for classifiers that make algorithmic choices to minimise runtime without compromising output correctness. CoRR (2019)
Dorian Florescu, Matthew England
Algorithmically generating new algebraic features of polynomial systems for machine learning. CoRR (2019)
Matthew England, Dorian Florescu
Comparing machine learning models to choose the variable ordering for cylindrical algebraic decomposition. CoRR (2019)
Dorian Florescu, Daniel Coca
Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data. Neural Comput. 30 (3) (2018)
Dorian Florescu, Daniel Coca
A Novel Reconstruction Framework for Time-Encoded Signals with Integrate-and-Fire Neurons. Neural Comput. 27 (9) (2015)
Dorian Florescu, Daniel Coca
Implementation of linear filters in the spike domain. ECC (2015)