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ORCIDVikram Nelvoy Rajendiran
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2020 – today
- 2024
[c6]Utsav Tiwari, Srinivas Soumitri Miriyala, Vikram Nelvoy Rajendiran:
Edge Deployable Distributed Evolutionary Optimization based Calibration method for Neural Quantization. ICASSP 2024: 6240-6244- [c5]Srinivas Soumitri Miriyala, P. K. Suhas, Utsav Tiwari, Vikram Nelvoy Rajendiran:
Mixed Precision Neural Quantization with Multi-Objective Bayesian Optimization for on-Device Deployment. ICASSP 2024: 6260-6264 - [c4]Aakansha Mishra, Srinivas Soumitri Miriyala, Vikram Nelvoy Rajendiran:
Learning Representations from Explainable and Connectionist Approaches for Visual Question Answering. ICASSP 2024: 6420-6424 - 2023
- [j1]Prasen Kumar Sharma
, Arun Abraham, Vikram Nelvoy Rajendiran:
A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks Via Learned Weights Statistics. IEEE Trans. Multim. 25: 953-965 (2023) - [c3]Prateek Keserwani, Srinivas Soumitri Miriyala, Vikram Nelvoy Rajendiran, Pradeep N. Shivamurthappa:
Receptive Field Reliant Zero-Cost Proxies for Neural Architecture Search. ICASSP 2023: 1-5 - [c2]Arun Chauhan, Utsav Tiwari, Vikram N. R:
Post Training Mixed Precision Quantization of Neural Networks using First-Order Information. ICCV (Workshops) 2023: 1335-1344 - 2021
- [i1]Prasen Kumar Sharma, Arun Abraham, Vikram Nelvoy Rajendiran:
A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks via Learned Weights Statistics. CoRR abs/2112.02834 (2021) - 2020
- [c1]Akshay Parashar, Arun Abraham, Deepak Chaudhary, Vikram Nelvoy Rajendiran:
Processor Pipelining Method for Efficient Deep Neural Network Inference on Embedded Devices. HiPC 2020: 82-90
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