1 citations · 2 across the 4 of their papers we have counts for
4 papers
PTCMIL: Multiple Instance Learning via Prompt Token Clustering for Whole Slide Image Analysis
Beidi Zhao, SangMook Kim, Hao Chen +4
Multiple Instance Learning (MIL) has advanced WSI analysis but struggles with the complexity and heterogeneity of WSIs. Existing MIL methods face challenges in aggregating diverse…
PMKLC: Parallel Multi-Knowledge Learning-based Lossless Compression for Large-Scale Genomics Database
Hui Sun, Yanfeng Ding, Liping Yi +5
Learning-based lossless compressors play a crucial role in large-scale genomic database backup, storage, transmission, and management. However, their 1) inadequate compression rati…
Federated Model Heterogeneous Matryoshka Representation Learning
Liping Yi, Han Yu, Chao Ren +3
Model heterogeneous federated learning (MHeteroFL) enables FL clients to collaboratively train models with heterogeneous structures in a distributed fashion. However, existing MHet…
LESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image Screening
Beidi Zhao, Wenlong Deng, Zi Han +5
In computational pathology, multiple instance learning (MIL) is widely used to circumvent the computational impasse in giga-pixel whole slide image (WSI) analysis. It usually consi…