Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Mehrotra, Abhinav"'
Autor:
Hunter, Rosco, Dudziak, Łukasz, Abdelfattah, Mohamed S., Mehrotra, Abhinav, Bhattacharya, Sourav, Wen, Hongkai
Text-to-image diffusion models have demonstrated unprecedented capabilities for flexible and realistic image synthesis. Nevertheless, these models rely on a time-consuming sampling procedure, which has motivated attempts to reduce their latency. When
Externí odkaz:
http://arxiv.org/abs/2401.01008
Autor:
Gao, Yan, Fernandez-Marques, Javier, Parcollet, Titouan, Mehrotra, Abhinav, Lane, Nicholas D.
The ubiquity of microphone-enabled devices has lead to large amounts of unlabelled audio data being produced at the edge. The integration of self-supervised learning (SSL) and federated learning (FL) into one coherent system can potentially offer dat
Externí odkaz:
http://arxiv.org/abs/2204.02804
Autor:
Almeida, Mario, Laskaridis, Stefanos, Mehrotra, Abhinav, Dudziak, Lukasz, Leontiadis, Ilias, Lane, Nicholas D.
With smartphones' omnipresence in people's pockets, Machine Learning (ML) on mobile is gaining traction as devices become more powerful. With applications ranging from visual filters to voice assistants, intelligence on mobile comes in many forms and
Externí odkaz:
http://arxiv.org/abs/2109.13963
Consider a home or office where multiple devices are running voice assistants (e.g., TVs, lights, ovens, refrigerators, etc.). A human user turns to a particular device and gives a voice command, such as ``Alexa, can you ...''. This paper focuses on
Externí odkaz:
http://arxiv.org/abs/2109.13094
Neural Architecture Search (NAS) is quickly becoming the standard methodology to design neural network models. However, NAS is typically compute-intensive because multiple models need to be evaluated before choosing the best one. To reduce the comput
Externí odkaz:
http://arxiv.org/abs/2101.08134
Autor:
Vipperla, Ravichander, Park, Sangjun, Choo, Kihyun, Ishtiaq, Samin, Min, Kyoungbo, Bhattacharya, Sourav, Mehrotra, Abhinav, Ramos, Alberto Gil C. P., Lane, Nicholas D.
LPCNet is an efficient vocoder that combines linear prediction and deep neural network modules to keep the computational complexity low. In this work, we present two techniques to further reduce it's complexity, aiming for a low-cost LPCNet vocoder-b
Externí odkaz:
http://arxiv.org/abs/2008.04574
Autor:
Mehrotra, Abhinav, Dudziak, Łukasz, Yeo, Jinsu, Lee, Young-yoon, Vipperla, Ravichander, Abdelfattah, Mohamed S., Bhattacharya, Sourav, Ishtiaq, Samin, Ramos, Alberto Gil C. P., Lee, SangJeong, Kim, Daehyun, Lane, Nicholas D.
Publikováno v:
INTERSPEECH 2020
Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research have shown that AutoML-based Low Rank Factorization (LRF) technique, when
Externí odkaz:
http://arxiv.org/abs/2008.02897
Understanding and learning the characteristics of network paths has been of particular interest for decades and has led to several successful applications. Such analysis becomes challenging for urban networks as their size and complexity are signific
Externí odkaz:
http://arxiv.org/abs/1912.07662
Autor:
Mehrotra, Abhinav
Mobile notifications provide a unique mechanism for real-time information delivery systems to users in order to increase its effectiveness. However, real-time notification delivery to users via mobile phones does not always translate into users' awar
Externí odkaz:
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.715589