From the 1 of 5 linked papers with an AI index.
5 papers
Structure-Feature Aligned Graph Learning via Alternating Constrained Optimization
Chengcheng Yan, Qingsong Wang
The paper proposes a two‑view framework that aligns GNN embeddings with a structure‑free feature prior learned by an anchor network, and introduces a channel‑split adaptive gated G…
Accelerated Tensor Completion via Trace-Regularized Fully-Connected Tensor Network
Wenchao Xie, Qingsong Wang, Chengcheng Yan +1
The fully-connected tensor network (FCTN) decomposition has gained prominence in the field of tensor completion owing to its powerful capacity to capture the low-rank characteristi…
Graph Convolutional Network With Pattern-Spatial Interactive and Regional Awareness for Traffic Forecasting
Xinyu Ji, Chengcheng Yan, Jibiao Yuan +1
Traffic forecasting is significant for urban traffic management, intelligent route planning, and real-time flow monitoring. Recent advances in spatial-temporal models have markedly…
Neural Network Training via Stochastic Alternating Minimization with Trainable Step Sizes
Chengcheng Yan, Jiawei Xu, Zheng Peng +1
The training of deep neural networks is inherently a nonconvex optimization problem, yet standard approaches such as stochastic gradient descent (SGD) require simultaneous updates…
A Triple-Inertial Accelerated Alternating Optimization Method for Deep Learning Training
Chengcheng Yan, Jiawei Xu, Qingsong Wang +1
The stochastic gradient descent (SGD) algorithm has achieved remarkable success in training deep learning models. However, it has several limitations, including susceptibility to v…