Thierry Moreau

Orcid: 0000-0002-5257-4044

According to our database1, Thierry Moreau authored at least 28 papers between 1996 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Exploiting Errors for Efficiency: A Survey from Circuits to Applications.
ACM Comput. Surv., 2021

Automatic generation of high-performance quantized machine learning kernels.
Proceedings of the CGO '20: 18th ACM/IEEE International Symposium on Code Generation and Optimization, 2020

A Hardware-Software Blueprint for Flexible Deep Learning Specialization.
IEEE Micro, 2019

Relay: A High-Level IR for Deep Learning.
CoRR, 2019

Cross-Stack Co-Design for Efficient and Adaptable Hardware Acceleration.
PhD thesis, 2018

Energy-Efficient Neural Network Acceleration in the Presence of Bit-Level Memory Errors.
IEEE Trans. Circuits Syst. I Regul. Pap., 2018

A Taxonomy of General Purpose Approximate Computing Techniques.
IEEE Embed. Syst. Lett., 2018

Automating Generation of Low Precision Deep Learning Operators.
CoRR, 2018

Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms.
CoRR, 2018

VTA: An Open Hardware-Software Stack for Deep Learning.
CoRR, 2018

TVM: End-to-End Optimization Stack for Deep Learning.
CoRR, 2018

Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments.
CoRR, 2018

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning.
Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

Learning to Optimize Tensor Programs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

MATIC: Learning around errors for efficient low-voltage neural network accelerators.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

Leveraging the VTA-TVM Hardware-Software Stack for FPGA Acceleration of 8-bit ResNet-18 Inference.
Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research.
Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

Exploring computation-communication tradeoffs in camera systems.
Proceedings of the 2017 IEEE International Symposium on Workload Characterization, 2017

Exploiting quality-energy tradeoffs with arbitrary quantization: special session paper.
Proceedings of the Twelfth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis Companion, 2017

Approximate Computing: Making Mobile Systems More Efficient.
IEEE Pervasive Comput., 2015

SNNAP: Approximate computing on programmable SoCs via neural acceleration.
Proceedings of the 21st IEEE International Symposium on High Performance Computer Architecture, 2015

Towards a Better Approximation of Full Domain Hash - or - The Reef and Shoal Integrity Arrangement
CoRR, 2013

A model-based statistic for detecting molecular markers associated with complex survival patterns in early-stage cancer.
J. Clin. Bioinform., 2012

Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes.
BMC Bioinform., 2010

PEKE, Probabilistic Encryption Key Exchange, 10 Years Later, Including the PEKEv1.25 Specifications.
IACR Cryptol. ePrint Arch., 2005

A simple procedure for estimating the false discovery rate.
Bioinform., 2005

The emergence of a legal framework for electronic transactions.
Comput. Secur., 1999

A probabilistic flaw in PGP design?
Comput. Secur., 1996