activity
20182024
most citedBeyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models

3 citations · 7 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2024★ 3 cited

Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models

Yuyan Shi, Jialu Ma, Jin Yang +2

Medical image segmentation plays an important role in many image-guided clinical approaches. However, existing segmentation algorithms mostly rely on the availability of fully anno…

cs.CV2023★ 1 cited

Competitive Ensembling Teacher-Student Framework for Semi-Supervised Left Atrium MRI Segmentation

Yuyan Shi, Yichi Zhang, Shasha Wang

Semi-supervised learning has greatly advanced medical image segmentation since it effectively alleviates the need of acquiring abundant annotations from experts and utilizes unlabe…

math.ST2023★ 1 cited

Pivotal Estimation of Linear Discriminant Analysis in High Dimensions

Ethan X. Fang, Yajun Mei, Yuyang Shi +2

We consider the linear discriminant analysis problem in the high-dimensional settings. In this work, we propose PANDA(PivotAl liNear Discriminant Analysis), a tuning-insensitive me…

cs.LG2022★ 2 cited

On PAC-Bayesian reconstruction guarantees for VAEs

Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet +1

Despite its wide use and empirical successes, the theoretical understanding and study of the behaviour and performance of the variational autoencoder (VAE) have only emerged in the…

stat.ME2021

Mixed Effects Envelope Models

Yuyang Shi, Linquan Ma, Lan Liu

When multiple measures are collected repeatedly over time, redundancy typically exists among responses. The envelope method was recently proposed to reduce the dimension of respons…

q-fin.PM2018

Robust Log-Optimal Strategy with Reinforcement Learning

Yifeng Guo, Xingyu Fu, Yuyan Shi +1

We proposed a new Portfolio Management method termed as Robust Log-Optimal Strategy (RLOS), which ameliorates the General Log-Optimal Strategy (GLOS) by approximating the tradition…