activity
20142024
most citedJoint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning

42 citations · 181 across the 44 of their papers we have counts for

collaborators

44 papers

cs.LG2024

Optimal Kernel Choice for Score Function-based Causal Discovery

Wenjie Wang, Biwei Huang, Feng Liu +4

Score-based methods have demonstrated their effectiveness in discovering causal relationships by scoring different causal structures based on their goodness of fit to the data. Rec…

cs.NI202442 cited

Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning

Tianfu Wang, Li Shen, Qilin Fan +3

As an essential resource management problem in network virtualization, virtual network embedding (VNE) aims to allocate the finite resources of physical network to sequentially arr…

eess.IV20245 cited

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…

cs.CV2024

Training-Free Robust Interactive Video Object Segmentation

Xiaoli Wei, Zhaoqing Wang, Yandong Guo +3

Interactive video object segmentation is a crucial video task, having various applications from video editing to data annotating. However, current approaches struggle to accurately…

cs.LG2024

Tackling Noisy Labels with Network Parameter Additive Decomposition

Jingyi Wang, Xiaobo Xia, Long Lan +5

Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows…

cs.LG20241 cited

Extracting Clean and Balanced Subset for Noisy Long-tailed Classification

Zhuo Li, He Zhao, Zhen Li +3

Real-world datasets usually are class-imbalanced and corrupted by label noise. To solve the joint issue of long-tailed distribution and label noise, most previous works usually aim…