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researcher

A. Choudhury

4 papers hereh-index 10657 citations35 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.DC2
  • cs.LG1
  • cs.SE1
same name
  • A. Choudhury — 23 papers, h 17
  • A. Choudhury — 8 papers, h 12
  • A. Choudhury — 7 papers, h 21
  • A. Choudhury — 6 papers, h 2
  • A. Choudhury — 4 papers, h 4
  • A. Choudhury — 2 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedEfficient Inferencing of Compressed Deep Neural Networks

2 citations · 2 across the 3 of their papers we have counts for

collaborators

4 papers

cs.SE2026

Revisiting the Role of Natural Language Code Comments in Code Translation

Monika Gupta, Ajay Meena, Anamitra Roy Choudhury +2

The advent of large language models (LLMs) has ushered in a new era in automated code translation across programming languages. Since most code-specific LLMs are pretrained on well…

cs.DC2021

Rightsizing Clusters for Time-Limited Tasks

Venkatesan T. Chakaravarthy, Padmanabha V. Seshadri, Pooja Aggarwal +4

In conventional public clouds, designing a suitable initial cluster for a given application workload is important in reducing the computational foot-print during run-time. In edge…

cs.LG2020

PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination

Saurabh Goyal, Anamitra R. Choudhury, Saurabh M. Raje +3

We develop a novel method, called PoWER-BERT, for improving the inference time of the popular BERT model, while maintaining the accuracy. It works by: a) exploiting redundancy pert…

cs.DC2017★ 2 cited

Efficient Inferencing of Compressed Deep Neural Networks

Dharma Teja Vooturi, Saurabh Goyal, Anamitra R. Choudhury +2

Large number of weights in deep neural networks makes the models difficult to be deployed in low memory environments such as, mobile phones, IOT edge devices as well as "inferencin…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.