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ORCIDHamed Fatemi Langroudi
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- affiliation: Rochester Institute of Technology, Neuromorphic AI Lab, NY, USA
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2020 – today
- 2022
[c9]Hamed Fatemi Langroudi, Vedant Karia, Tej Pandit, Becky Mashaido, Dhireesha Kudithipudi:
ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML. CoNGA 2022: 50-65- 2021
- [c8]Hamed Fatemi Langroudi, Vedant Karia, Zachariah Carmichael, Abdullah M. Zyarah, Tej Pandit, John L. Gustafson, Dhireesha Kudithipudi:
ALPS: Adaptive Quantization of Deep Neural Networks With GeneraLized PositS. CVPR Workshops 2021: 3100-3109 - [i7]Hamed Fatemi Langroudi, Vedant Karia, Tej Pandit, Dhireesha Kudithipudi:
TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT. CoRR abs/2104.02233 (2021) - 2020
- [c7]Hamed Fatemi Langroudi, Vedant Karia, John L. Gustafson, Dhireesha Kudithipudi:
Adaptive Posit: Parameter aware numerical format for deep learning inference on the edge. CVPR Workshops 2020: 3123-3131
2010 – 2019
- 2019
- [c6]Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Deep Positron: A Deep Neural Network Using the Posit Number System. DATE 2019: 1421-1426 - [c5]Hamed Fatemi Langroudi, Cory E. Merkel, Humza Syed, Dhireesha Kudithipudi:
Exploiting Randomness in Deep Learning Algorithms. IJCNN 2019: 1-8 - [i6]Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks. CoRR abs/1903.10584 (2019) - [i5]Hamed Fatemi Langroudi, Zachariah Carmichael, Dhireesha Kudithipudi:
Deep Learning Training on the Edge with Low-Precision Posits. CoRR abs/1907.13216 (2019) - [i4]Hamed Fatemi Langroudi, Zachariah Carmichael, David Pastuch, Dhireesha Kudithipudi:
Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge. CoRR abs/1908.02386 (2019) - 2018
- [c4]Seyed Hamed Fatemi Langroudi, Tej Pandit, Dhireesha Kudithipudi:
Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit. EMC2@ASPLOS 2018: 19-23 - [i3]Seyed Hamed Fatemi Langroudi, Tej Pandit, Dhireesha Kudithipudi:
Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit. CoRR abs/1805.08624 (2018) - [i2]Zachariah Carmichael, Seyed Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi:
Deep Positron: A Deep Neural Network Using the Posit Number System. CoRR abs/1812.01762 (2018) - 2017
- [c3]Dillon Graham, Seyed Hamed Fatemi Langroudi, Christopher Kanan, Dhireesha Kudithipudi:
Convolutional Drift Networks for Video Classification. ICRC 2017: 1-8 - [i1]Dillon Graham, Seyed Hamed Fatemi Langroudi, Christopher Kanan, Dhireesha Kudithipudi:
Convolutional Drift Networks for Video Classification. CoRR abs/1711.01201 (2017) - 2015
- [j1]Ghassem Jaberipur, Seyed Hamed Fatemi Langroudi:
(4+2 log n)ΔG Parallel Prefix Modulo-(2n-3) Adder via Double Representation of Residues in [0, 2]. IEEE Trans. Circuits Syst. II Express Briefs 62-II(6): 583-587 (2015) - [c2]Seyed Hamed Fatemi Langroudi, Ghassem Jaberipur:
Modulo-(2n - 2q - 1) Parallel Prefix Addition via Excess-Modulo Encoding of Residues. ARITH 2015: 121-128 - 2014
- [c1]Seyed Hamed Fatemi Langroudi, Ghassem Jaberipur:
Double {0, 1, 2} representation modulo-(2n - 3) adders. IWSSIP 2014: 119-122
Coauthor Index
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