Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Sarah, Anthony"'
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 prompted their extensive adoption. Unfortunately, these abilities com
Externí odkaz:
http://arxiv.org/abs/2405.18377
With the recent growth in demand for large-scale deep neural networks, compute in-memory (CiM) has come up as a prominent solution to alleviate bandwidth and on-chip interconnect bottlenecks that constrain Von-Neuman architectures. However, the const
Externí odkaz:
http://arxiv.org/abs/2402.11780
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 different hardware platforms. Popular approaches separate the training
Externí odkaz:
http://arxiv.org/abs/2312.13301
One-Shot Neural Architecture Search (NAS) algorithms often rely on training a hardware agnostic super-network for a domain specific task. Optimal sub-networks are then extracted from the trained super-network for different hardware platforms. However
Externí odkaz:
http://arxiv.org/abs/2308.15609
Publikováno v:
Pilot and Feasibility Studies, Vol 10, Iss 1, Pp 1-8 (2024)
Abstract Background The new P-STEP® (Personalised Space Technology Exercise Platform) app is designed to bring together tailored exercise guidance and up-to-date air quality information. The app allows individuals to plan outdoor exercise walking ro
Externí odkaz:
https://doaj.org/article/03d6ab4692f24774be2100a8dc6799a7
Autor:
Cummings, Daniel, Sarah, Anthony, Sridhar, Sharath Nittur, Szankin, Maciej, Munoz, Juan Pablo, Sundaresan, Sairam
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 super-network. While considerable effort has been employed towards improv
Externí odkaz:
http://arxiv.org/abs/2205.10358
Autor:
Lamdouar, Hala, Sundaresan, Sairam, Jungbluth, Anna, Saikia, Sudeshna Boro, Camarata, Amanda Joy, Miles, Nathan, Scoczynski, Marcella, Stone, Mavis, Sarah, Anthony, Muñoz-Jaramillo, Andrés, Narock, Ayris, Szabo, Adam
The solar wind consists of charged particles ejected from the Sun into interplanetary space and towards Earth. Understanding the magnetic field of the solar wind is crucial for predicting future space weather and planetary atmospheric loss. Compared
Externí odkaz:
http://arxiv.org/abs/2203.01184
Autor:
Sarah, Anthony, Cummings, Daniel, Sridhar, Sharath Nittur, Sundaresan, Sairam, Szankin, Maciej, Webb, Tristan, Munoz, J. Pablo
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 become increasingly popular. While considerable effort has been employed
Externí odkaz:
http://arxiv.org/abs/2202.12954
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 language processing, has seen rapid growth in the machine learning research
Externí odkaz:
http://arxiv.org/abs/2202.12934
Models based on BERT have been extremely successful in solving a variety of natural language processing (NLP) tasks. Unfortunately, many of these large models require a great deal of computational resources and/or time for pre-training and fine-tunin
Externí odkaz:
http://arxiv.org/abs/2202.12411