| DNR: A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs S Kundu, M Nazemi, PA Beerel, M Pedram Proceedings of the 26th Asia and South Pacific Design Automation Conference …, 2021 | 88 | 2021 |
| FFT-Based Deep Learning Deployment in Embedded Systems S Lin, N Liu, M Nazemi, H Li, C Ding, Y Wang, M Pedram IEEE Design, Automation, and Test in Europe Conference & Exhibition (DATE), 2017 | 71 | 2017 |
| Pre-defined Sparsity for Low-Complexity Convolutional Neural Networks S Kundu, M Nazemi, M Pedram, KM Chugg, P Beerel IEEE Transactions on Computers, 2020 | 58 | 2020 |
| Energy-Efficient, Low-Latency Realization of Neural Networks Through Boolean Logic Minimization M Nazemi, G Pasandi, M Pedram IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2019 | 49 | 2019 |
| SynergicLearning: Neural Network-Based Feature Extraction for Highly-Accurate Hyperdimensional Learning M Nazemi, A Esmaili, A Fayyazi, M Pedram 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2020 | 34 | 2020 |
| NullaNet: Training Deep Neural Networks for Reduced-Memory-Access Inference M Nazemi, G Pasandi, M Pedram arXiv preprint arXiv:1807.08716, 2018 | 30 | 2018 |
| ThermTap: An online power analyzer and thermal simulator for Android devices MJ Dousti, M Ghasemi-Gol, M Nazemi, M Pedram IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED …, 2015 | 22 | 2015 |
| NullaNet Tiny: Ultra-low-latency DNN inference through fixed-function combinational logic M Nazemi, A Fayyazi, A Esmaili, A Khare, SN Shahsavani, M Pedram arXiv preprint arXiv:2104.05421, 2021 | 17 | 2021 |
| Energy-aware scheduling of task graphs with imprecise computations and end-to-end deadlines A Esmaili, M Nazemi, M Pedram ACM Transactions on Design Automation of Electronic Systems (TODAES) 25 (1 …, 2019 | 17 | 2019 |
| Therminator 2: A Fast Thermal Simulator for Portable Devices MJ Dousti, Q Xie, M Nazemi, M Pedram IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021 | 13 | 2021 |
| Modeling processor idle times in MPSoC platforms to enable integrated DPM, DVFS, and task scheduling subject to a hard deadline A Esmaili, M Nazemi, M Pedram IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2019 | 13 | 2019 |
| A Hardware-Friendly Algorithm for Scalable Training and Deployment of Dimensionality Reduction Models on FPGA M Nazemi, AE Eshratifar, M Pedram IEEE International Symposium on Quality Electronic Design (ISQED), 2018 | 13 | 2018 |
| Deploying Customized Data Representation and Approximate Computing in Machine Learning Applications M Nazemi, M Pedram IEEE/ACM International Symposium on Low Power Electronic Design (ISLPED), 2018 | 12 | 2018 |
| High-Performance FPGA Implementation of Equivariant Adaptive Separation via Independence Algorithm for Independent Component Analysis M Nazemi, S Nazarian, M Pedram IEEE International Conference on Application-specific Systems, Architectures …, 2017 | 9 | 2017 |
| Sensitivity-aware mixed-precision quantization and width optimization of deep neural networks through cluster-based tree-structured Parzen estimation S Azizi, M Nazemi, A Fayyazi, M Pedram arXiv preprint arXiv:2308.06422, 2023 | 6 | 2023 |
| Espresso-gpu: blazingly fast two-level logic minimization H Kanakia, M Nazemi, A Fayyazi, M Pedram 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2021 | 6 | 2021 |
| Low-precision mixed-computation models for inference on edge S Azizi, M Nazemi, M Kamal, M Pedram IEEE Transactions on Very Large Scale Integration (VLSI) Systems 32 (8 …, 2024 | 4 | 2024 |
| A fast training-free compression framework for vision transformers JH Heo, A Fayyazi, M Nazemi, M Pedram arXiv preprint arXiv:2303.02331 2 (3), 2023 | 4 | 2023 |
| Memory-Efficient Vision Transformers: An Activation-Aware Mixed-Rank Compression Strategy S Azizi, M Nazemi, M Pedram European Conference on Computer Vision, 55-66, 2024 | 3 | 2024 |
| Neuroblend: Towards low-power yet accurate neural network-based inference engine blending binary and fixed-point convolutions A Fayyazi, M Nazemi, A Fayyazi, M Pedram Proceedings of the Great Lakes Symposium on VLSI 2024, 730-735, 2024 | 2 | 2024 |
