20 citations · 29 across the 5 of their papers we have counts for
5 papers
Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation
Camilo Gomez, Pengyang Wang, Yanjie Fu
Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents based on their relevance or impor…
NAPER: Fault Protection for Real-Time Resource-Constrained Deep Neural Networks
Rian Adam Rajagede, Muhammad Husni Santriaji, Muhammad Arya Fikriansyah +3
Fault tolerance in Deep Neural Networks (DNNs) deployed on resource-constrained systems presents unique challenges for high-accuracy applications with strict timing requirements. M…
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
Yicheng Zhou, Pengfei Wang, Hao Dong +4
Urban traffic speed prediction aims to estimate the future traffic speed for improving urban transportation services. Enormous efforts have been made to exploit Graph Neural Networ…
A Comprehensive Survey on Data Augmentation
Zaitian Wang, Pengfei Wang, Kunpeng Liu +6
Data augmentation is a series of techniques that generate high-quality artificial data by manipulating existing data samples. By leveraging data augmentation techniques, AI models…
IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
Wei Fan, Shun Zheng, Pengyang Wang +5
Due to the non-stationarity of time series, the distribution shift problem largely hinders the performance of time series forecasting. Existing solutions either rely on using certa…