137 citations · 351 across the 41 of their papers we have counts for
9 papers · 1 filter
PR-NeuS: A Prior-based Residual Learning Paradigm for Fast Multi-view Neural Surface Reconstruction
Jianyao Xu, Qingshan Xu, Xinyao Liao +4
Neural surfaces learning has shown impressive performance in multi-view surface reconstruction. However, most existing methods use large multilayer perceptrons (MLPs) to train thei…
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
Shanli Tan, Hao Cheng, Xiaohu Wu +5
Federated learning (FL) provides a privacy-preserving approach for collaborative training of machine learning models. Given the potential data heterogeneity, it is crucial to selec…
Adaptive In-Context Learning with Large Language Models for Bundle Generation
Zhu Sun, Kaidong Feng, Jie Yang +4
Most existing bundle generation approaches fall short in generating fixed-size bundles. Furthermore, they often neglect the underlying user intents reflected by the bundles in the…
Bayesian Inverse Transfer in Evolutionary Multiobjective Optimization
Jiao Liu, Abhishek Gupta, Yew-Soon Ong
Transfer optimization enables data-efficient optimization of a target task by leveraging experiential priors from related source tasks. This is especially useful in multiobjective…
Evolutionary Optimization of Physics-Informed Neural Networks: Advancing Generalizability by the Baldwin Effect
Jian Cheng Wong, Chin Chun Ooi, Abhishek Gupta +4
Physics-informed neural networks (PINNs) are at the forefront of scientific machine learning, making possible the creation of machine intelligence that is cognizant of physical law…
Large Language Models as Evolutionary Optimizers
Shengcai Liu, Caishun Chen, Xinghua Qu +2
Evolutionary algorithms (EAs) have achieved remarkable success in tackling complex combinatorial optimization problems. However, EAs often demand carefully-designed operators with…
MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation
Jiahao Xie, Wei Li, Xiangtai Li +3
We present MosaicFusion, a simple yet effective diffusion-based data augmentation approach for large vocabulary instance segmentation. Our method is training-free and does not rely…
Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects
Xinghua Qu, Hongyang Liu, Zhu Sun +4
Conversational recommender systems (CRSs) have become crucial emerging research topics in the field of RSs, thanks to their natural advantages of explicitly acquiring user preferen…
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search
Kim Yong Tan, Yueming Lyu, Yew Soon Ong +1
Approximate nearest neighbour (ANN) search is an essential component of search engines, recommendation systems, etc. Many recent works focus on learning-based data-distribution-dep…