66 citations · 136 across the 8 of their papers we have counts for
4 papers · 1 filter
Quantized Adaptive Subgradient Algorithms and Their Applications
Ke Xu, Jianqiao Wangni, Yifan Zhang +3
Data explosion and an increase in model size drive the remarkable advances in large-scale machine learning, but also make model training time-consuming and model storage difficult.…
Efficient Test-Time Model Adaptation without Forgetting
Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4
Test-time adaptation (TTA) seeks to tackle potential distribution shifts between training and testing data by adapting a given model w.r.t. any testing sample. This task is particu…
Multi-scale Attention Flow for Probabilistic Time Series Forecasting
Shibo Feng, Chunyan Miao, Ke Xu +4
The probability prediction of multivariate time series is a notoriously challenging but practical task. On the one hand, the challenge is how to effectively capture the cross-serie…
Boost Test-Time Performance with Closed-Loop Inference
Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +6
Conventional deep models predict a test sample with a single forward propagation, which, however, may not be sufficient for predicting hard-classified samples. On the contrary, we…