47 citations · 256 across the 23 of their papers we have counts for
24 papers
Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
Chenhui Xu, Fuxun Yu, Zirui Xu +2
Recent research underscores the pivotal role of the Out-of-Distribution (OOD) feature representation field scale in determining the efficacy of models in OOD detection. Consequentl…
QuadraNet: Improving High-Order Neural Interaction Efficiency with Hardware-Aware Quadratic Neural Networks
Chenhui Xu, Fuxun Yu, Zirui Xu +3
Recent progress in computer vision-oriented neural network designs is mostly driven by capturing high-order neural interactions among inputs and features. And there emerged a varie…
Automated Runtime-Aware Scheduling for Multi-Tenant DNN Inference on GPU
Fuxun Yu, Shawn Bray, Di Wang +4
With the fast development of deep neural networks (DNNs), many real-world applications are adopting multiple models to conduct compound tasks, such as co-running classification, de…
Fed2: Feature-Aligned Federated Learning
Fuxun Yu, Weishan Zhang, Zhuwei Qin +5
Federated learning learns from scattered data by fusing collaborative models from local nodes. However, the conventional coordinate-based model averaging by FedAvg ignored the rand…
A Survey of Large-Scale Deep Learning Serving System Optimization: Challenges and Opportunities
Fuxun Yu, Di Wang, Longfei Shangguan +4
Deep Learning (DL) models have achieved superior performance in many application domains, including vision, language, medical, commercial ads, entertainment, etc. With the fast dev…
Towards Latency-aware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
Fuxun Yu, Zirui Xu, Tong Shen +12
Despite the superb performance of State-Of-The-Art (SOTA) DNNs, the increasing computational cost makes them very challenging to meet real-time latency and accuracy requirements. A…