3 citations · 8 across the 15 of their papers we have counts for
6 papers · 1 filter
Towards Automated Model Design on Recommender Systems
Tunhou Zhang, Dehua Cheng, Yuchen He +10
The increasing popularity of deep learning models has created new opportunities for developing AI-based recommender systems. Designing recommender systems using deep neural network…
MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning
Jianyi Zhang, Hao Frank Yang, Ang Li +5
Previous studies on federated learning (FL) often encounter performance degradation due to data heterogeneity among different clients. In light of the recent advances in multimodal…
MonoSparse-CAM: Efficient Tree Model Processing via Monotonicity and Sparsity in CAMs
Tergel Molom-Ochir, Brady Taylor, Hai Li +1
While the tree-based machine learning (TBML) models exhibit superior performance compared to neural networks on tabular data and hold promise for energy-efficient acceleration usin…
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS
Hao Fu, Tunhou Zhang, Hai Li +1
Recent advances in Out-of-Distribution (OOD) Detection is the driving force behind safe and reliable deployment of Convolutional Neural Networks (CNNs) in real world applications.…
CSCO: Connectivity Search of Convolutional Operators
Tunhou Zhang, Shiyu Li, Hsin-Pai Cheng +3
Exploring dense connectivity of convolutional operators establishes critical "synapses" to communicate feature vectors from different levels and enriches the set of transformations…
Peeking Behind the Curtains of Residual Learning
Tunhou Zhang, Feng Yan, Hai Li +1
The utilization of residual learning has become widespread in deep and scalable neural nets. However, the fundamental principles that contribute to the success of residual learning…