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14 papers · 1 filter
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…
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…
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…
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…
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…
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…