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20142023
most citedAlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

129 citations · 328 across the 11 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2023★ 12 cited

Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense

Jingyuan Wang, Yufan Wu, Mingxuan Li +3

While having achieved great success in rich real-life applications, deep neural network (DNN) models have long been criticized for their vulnerability to adversarial attacks. Treme…

cs.LG2022★ 13 cited

Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction

Jiahao Ji, Jingyuan Wang, Chao Huang +5

Robust prediction of citywide traffic flows at different time periods plays a crucial role in intelligent transportation systems. While previous work has made great efforts to mode…

cs.LG2019★ 75 cited

Understanding Urban Dynamics via Context-aware Tensor Factorization with Neighboring Regularization

Jingyuan Wang, Junjie Wu, Ze Wang +2

Recent years have witnessed the world-wide emergence of mega-metropolises with incredibly huge populations. Understanding residents mobility patterns, or urban dynamics, thus becom…

cs.LG2019★ 1 cited

SVM-based Deep Stacking Networks

Jingyuan Wang, Kai Feng, Junjie Wu

The deep network model, with the majority built on neural networks, has been proved to be a powerful framework to represent complex data for high performance machine learning. In r…

cs.LG2018★ 7 cited

Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis

Jingyuan Wang, Ze Wang, Jianfeng Li +1

Recent years have witnessed the unprecedented rising of time series from almost all kindes of academic and industrial fields. Various types of deep neural network models have been…