[PDF][PDF] A review of speech-centric trustworthy machine learning: Privacy, safety, and fairness
Speech-centric machine learning systems have revolutionized a number of leading
industries ranging from transportation and healthcare to education and defense …
industries ranging from transportation and healthcare to education and defense …
Gpt-fl: Generative pre-trained model-assisted federated learning
In this work, we propose GPT-FL, a generative pre-trained model-assisted federated
learning (FL) framework. At its core, GPT-FL leverages generative pre-trained models to …
learning (FL) framework. At its core, GPT-FL leverages generative pre-trained models to …
Timelyfl: Heterogeneity-aware asynchronous federated learning with adaptive partial training
Abstract In cross-device Federated Learning (FL) environments, scaling synchronous FL
methods is challenging as stragglers hinder the training process. Moreover, the availability …
methods is challenging as stragglers hinder the training process. Moreover, the availability …
Fedmultimodal: A benchmark for multimodal federated learning
Over the past few years, Federated Learning (FL) has become an emerging machine
learning technique to tackle data privacy challenges through collaborative training. In the …
learning technique to tackle data privacy challenges through collaborative training. In the …
Peft-ser: On the use of parameter efficient transfer learning approaches for speech emotion recognition using pre-trained speech models
T Feng, S Narayanan - 2023 11th International Conference on …, 2023 - ieeexplore.ieee.org
Many recent studies have focused on fine-tuning pretrained models for speech emotion
recognition (SER), resulting in promising performance compared to traditional methods that …
recognition (SER), resulting in promising performance compared to traditional methods that …
Nert: Implicit neural representations for unsupervised atmospheric turbulence mitigation
W Jiang, V Boominathan… - Proceedings of the …, 2023 - openaccess.thecvf.com
The atmospheric turbulence mitigation problem has emerged as a challenging inverse
problem in the communities of computer vision and optics. However, current methods either …
problem in the communities of computer vision and optics. However, current methods either …
Artificial intelligence of things: A survey
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …
Coala: A practical and vision-centric federated learning platform
We present COALA, a vision-centric Federated Learning (FL) platform, and a suite of
benchmarks for practical FL scenarios, which we categorize into three levels: task, data, and …
benchmarks for practical FL scenarios, which we categorize into three levels: task, data, and …
Secure federated learning against model poisoning attacks via client filtering
Given the distributed nature, detecting and defending against the backdoor attack under
federated learning (FL) systems is challenging. In this paper, we observe that the cosine …
federated learning (FL) systems is challenging. In this paper, we observe that the cosine …
Vflair: A research library and benchmark for vertical federated learning
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that
allows participants with different features of the same group of users to accomplish …
allows participants with different features of the same group of users to accomplish …