Bita Darvish Rouhani

Orcid: 0000-0002-8412-4320

According to our database1, Bita Darvish Rouhani authored at least 45 papers between 2014 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Intellectual Property Protection of Deep-Learning Systems via Hardware/Software Co-Design.
IEEE Des. Test, 2024

2023
Microscaling Data Formats for Deep Learning.
CoRR, 2023

Shared Microexponents: A Little Shifting Goes a Long Way.
CoRR, 2023


2021
CuRTAIL: ChaRacterizing and Thwarting AdversarIal Deep Learning.
IEEE Trans. Dependable Secur. Comput., 2021

SWANN: Small-World Architecture for Fast Convergence of Neural Networks.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2021

Hardware/Algorithm Codesign for Adversarially Robust Deep Learning.
IEEE Des. Test, 2021

2020
Towards A Domain-Customized Automated Machine Learning Framework For Networks and Systems.
CoRR, 2020

Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SpecMark: A Spectral Watermarking Framework for IP Protection of Speech Recognition Systems.
Proceedings of the Interspeech 2020, 2020

2019
Safe Machine Learning and Defeating Adversarial Attacks.
IEEE Secur. Priv., 2019

Deep Learning on Private Data.
IEEE Secur. Priv., 2019

SWNet: Small-World Neural Networks and Rapid Convergence.
CoRR, 2019

BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks.
CoRR, 2019

DeepMarks: A Secure Fingerprinting Framework for Digital Rights Management of Deep Learning Models.
Proceedings of the 2019 on International Conference on Multimedia Retrieval, 2019

DeepAttest: an end-to-end attestation framework for deep neural networks.
Proceedings of the 46th International Symposium on Computer Architecture, 2019

SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing.
Proceedings of the International Conference on Computer-Aided Design, 2019

DeepSigns: An End-to-End Watermarking Framework for Ownership Protection of Deep Neural Networks.
Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

2018
Succinct and Assured Machine Learning: Training and Execution.
PhD thesis, 2018

ReDCrypt: Real-Time Privacy-Preserving Deep Learning Inference in Clouds Using FPGAs.
ACM Trans. Reconfigurable Technol. Syst., 2018

Serving DNNs in Real Time at Datacenter Scale with Project Brainwave.
IEEE Micro, 2018

DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models.
IACR Cryptol. ePrint Arch., 2018

DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks.
IACR Cryptol. ePrint Arch., 2018

Performance Comparison of Contemporary DNN Watermarking Techniques.
CoRR, 2018

AgileNet: Lightweight Dictionary-based Few-shot Learning.
CoRR, 2018

DeepFense: online accelerated defense against adversarial deep learning.
Proceedings of the International Conference on Computer-Aided Design, 2018

Assured deep learning: practical defense against adversarial attacks.
Proceedings of the International Conference on Computer-Aided Design, 2018

CausaLearn: Automated Framework for Scalable Streaming-based Causal Bayesian Learning using FPGAs.
Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

MAXelerator: FPGA accelerator for privacy preserving multiply-accumulate (MAC) on cloud servers.
Proceedings of the 55th Annual Design Automation Conference, 2018

2017
RISE: An Automated Framework for Real-Time Intelligent Video Surveillance on FPGA.
ACM Trans. Embed. Comput. Syst., 2017

DeepSecure: Scalable Provably-Secure Deep Learning.
IACR Cryptol. ePrint Arch., 2017

CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning.
CoRR, 2017

TinyDL: Just-in-time deep learning solution for constrained embedded systems.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

ExtDict: Extensible Dictionaries for Data- and Platform-Aware Large-Scale Learning.
Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

Deep3: Leveraging Three Levels of Parallelism for Efficient Deep Learning.
Proceedings of the 54th Annual Design Automation Conference, 2017

2016
Automated Real-Time Analysis of Streaming Big and Dense Data on Reconfigurable Platforms.
ACM Trans. Reconfigurable Technol. Syst., 2016

Chime: Checkpointing Long Computations on Interm ittently Energized IoT Devices.
IEEE Trans. Multi Scale Comput. Syst., 2016

DeLight: Adding Energy Dimension To Deep Neural Networks.
Proceedings of the 2016 International Symposium on Low Power Electronics and Design, 2016

Perform-ML: performance optimized machine learning by platform and content aware customization.
Proceedings of the 53rd Annual Design Automation Conference, 2016

Going deeper than deep learning for massive data analytics under physical constraints.
Proceedings of the Eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, 2016

2015
An Effectiveness Model for Enterprise Architecture Methodologies.
Int. J. Enterp. Inf. Syst., 2015

Agent-Oriented Based Enterprise Architecture Implementation Methodology.
Proceedings of the New Contributions in Information Systems and Technologies, 2015

Flexible Transformations For Learning Big Data.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

SSketch: An Automated Framework for Streaming Sketch-Based Analysis of Big Data on FPGA.
Proceedings of the 23rd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2015

2014
Current Issues on Enterprise Architecture Implementation Methodology.
Proceedings of the New Perspectives in Information Systems and Technologies, 2014


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