7 papers
Optimal plug-in Gaussian processes for modeling derivatives
Zejian Liu, Meng Li
Derivatives are a key nonparametric functional in wide-ranging applications where the rate of change of an unknown function is of interest. In the Bayesian paradigm, Gaussian proce…
Photovoltaic potential of tin perovskites revealed through layer-by-layer investigation of optoelectronic and charge transport properties
Mahmoud H. Aldamasy, Artem Musiienko, Marin Rusu +15
Tin perovskites are the most promising environmentally friendly alternative to lead perovskites. Among tin perovskites, FASnI3 (CH4N2SnI3) shows optimum band gap, and easy processa…
SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings
Renjie Wei, Zechun Liu, Yuchen Fan +3
Deep neural networks for image super-resolution (SR) have demonstrated superior performance. However, the large memory and computation consumption hinders their deployment on resou…
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
Yonggan Fu, Haichuan Yang, Jiayi Yuan +5
Efficient deep neural network (DNN) models equipped with compact operators (e.g., depthwise convolutions) have shown great potential in reducing DNNs' theoretical complexity (e.g.,…
DNA: Differentiable Network-Accelerator Co-Search
Yongan Zhang, Yonggan Fu, Weiwen Jiang +5
Powerful yet complex deep neural networks (DNNs) have fueled a booming demand for efficient DNN solutions to bring DNN-powered intelligence into numerous applications. Jointly opti…
Intelligent Model Update Strategy for Sequential Recommendation
Zheqi Lv, Wenqiao Zhang, Zhengyu Chen +2
Modern online platforms are increasingly employing recommendation systems to address information overload and improve user engagement. There is an evolving paradigm in this researc…