activity
20222025
most citedA Hardware-Aware Framework for Accelerating Neural Architecture Search Across Modalities

4 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Seeing the Signs: A Survey of Edge-Deployable OCR Models for Billboard Visibility Analysis

Maciej Szankin, Vidhyananth Venkatasamy, Lihang Ying

Outdoor advertisements remain a critical medium for modern marketing, yet accurately verifying billboard text visibility under real-world conditions is still challenging. Tradition…

cs.AI2024

LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models

Anthony Sarah, Sharath Nittur Sridhar, Maciej Szankin +1

The abilities of modern large language models (LLMs) in solving natural language processing, complex reasoning, sentiment analysis and other tasks have been extraordinary which has…

cs.LG2023

SimQ-NAS: Simultaneous Quantization Policy and Neural Architecture Search

Sharath Nittur Sridhar, Maciej Szankin, Fang Chen +2

Recent one-shot Neural Architecture Search algorithms rely on training a hardware-agnostic super-network tailored to a specific task and then extracting efficient sub-networks for…

cs.LG20224 cited

A Hardware-Aware Framework for Accelerating Neural Architecture Search Across Modalities

Daniel Cummings, Anthony Sarah, Sharath Nittur Sridhar +3

Recent advances in Neural Architecture Search (NAS) such as one-shot NAS offer the ability to extract specialized hardware-aware sub-network configurations from a task-specific sup…

cs.AI20221 cited

A Hardware-Aware System for Accelerating Deep Neural Network Optimization

Anthony Sarah, Daniel Cummings, Sharath Nittur Sridhar +4

Recent advances in Neural Architecture Search (NAS) which extract specialized hardware-aware configurations (a.k.a. "sub-networks") from a hardware-agnostic "super-network" have be…

cs.NE2022

Accelerating Neural Architecture Exploration Across Modalities Using Genetic Algorithms

Daniel Cummings, Sharath Nittur Sridhar, Anthony Sarah +1

Neural architecture search (NAS), the study of automating the discovery of optimal deep neural network architectures for tasks in domains such as computer vision and natural langua…