output
20142025
most citedCE-Net: Context Encoder Network for 2D Medical Image Segmentation

2.3k citations

Showing cs.LGShow all

14 papers · 1 filter

cs.LG20233 cited

ROMO: Retrieval-enhanced Offline Model-based Optimization

Mingcheng Chen, Haoran Zhao, Yuxiang Zhao +4

Data-driven black-box model-based optimization (MBO) problems arise in a great number of practical application scenarios, where the goal is to find a design over the whole space ma…

cs.LG20232 cited

Towards Better Modeling with Missing Data: A Contrastive Learning-based Visual Analytics Perspective

Laixin Xie, Yang Ouyang, Longfei Chen +2

Missing data can pose a challenge for machine learning (ML) modeling. To address this, current approaches are categorized into feature imputation and label prediction and are prima…

cs.LG202227 cited

Federated Fuzzy Neural Network with Evolutionary Rule Learning

Leijie Zhang, Ye Shi, Yu-Cheng Chang +1

Distributed fuzzy neural networks (DFNNs) have attracted increasing attention recently due to their learning abilities in handling data uncertainties in distributed scenarios. Howe…

cs.LG202210 cited

Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization

Ye Shi, Leijie Zhang, Zehong Cao +2

Recently, distributed semi-supervised learning (DSSL) algorithms have shown their effectiveness in leveraging unlabeled samples over interconnected networks, where agents cannot sh…

cs.LG202211 cited

ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learning

Haozhe Wang, Chao Du, Panyan Fang +4

Real-Time Bidding (RTB) is an important mechanism in modern online advertising systems. Advertisers employ bidding strategies in RTB to optimize their advertising effects subject t…

cs.LG20212 cited

SoGCN: Second-Order Graph Convolutional Networks

Peihao Wang, Yuehao Wang, Hua Lin +1

Graph Convolutional Networks (GCN) with multi-hop aggregation is more expressive than one-hop GCN but suffers from higher model complexity. Finding the shortest aggregation range t…