activity
20212024
most citedFLoRA: Single-shot Hyper-parameter Optimization for Federated Learning

13 citations · 29 across the 16 of their papers we have counts for

collaborators

15 papers

cs.CL2023

A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models

Yi Zhou, Jose Camacho-Collados, Danushka Bollegala

Various types of social biases have been reported with pretrained Masked Language Models (MLMs) in prior work. However, multiple underlying factors are associated with an MLM such…

eess.AS2023

Super Denoise Net: Speech Super Resolution with Noise Cancellation in Low Sampling Rate Noisy Environments

Junkang Yang, Hongqing Liu, Lu Gan +1

Speech super-resolution (SSR) aims to predict a high resolution (HR) speech signal from its low resolution (LR) corresponding part. Most neural SSR models focus on producing the fi…

cs.CE2023

Generalizable and explainable prediction of potential miRNA-disease associations based on heterogeneous graph learning

Yi Zhou, Meixuan Wu, Chengzhou Ouyang +1

Biomedical research has revealed the crucial role of miRNAs in the progression of many diseases, and computational prediction methods are increasingly proposed for assisting biolog…

cs.CL2023

Together We Make Sense -- Learning Meta-Sense Embeddings from Pretrained Static Sense Embeddings

Haochen Luo, Yi Zhou, Danushka Bollegala

Sense embedding learning methods learn multiple vectors for a given ambiguous word, corresponding to its different word senses. For this purpose, different methods have been propos…

cs.CL2023

Solving Cosine Similarity Underestimation between High Frequency Words by L2 Norm Discounting

Saeth Wannasuphoprasit, Yi Zhou, Danushka Bollegala

Cosine similarity between two words, computed using their contextualised token embeddings obtained from masked language models (MLMs) such as BERT has shown to underestimate the ac…

eess.IV20235 cited

Dual Residual Attention Network for Image Denoising

Wencong Wu, Shijie Liu, Yi Zhou +2

In image denoising, deep convolutional neural networks (CNNs) can obtain favorable performance on removing spatially invariant noise. However, many of these networks cannot perform…