48 citations · 52 across the 3 of their papers we have counts for
5 papers
Safe Exploration by Solving Early Terminated MDP
Hao Sun, Ziping Xu, Meng Fang +4
Safe exploration is crucial for the real-world application of reinforcement learning (RL). Previous works consider the safe exploration problem as Constrained Markov Decision Proce…
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori +2
In real-world decision-making problems, for instance in the fields of finance, robotics or autonomous driving, keeping uncertainty under control is as important as maximizing expec…
Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder
Hao Sun, Jiadong Guo, Edward J. Kim +1
The increasing amount of data in astronomy provides great challenges for machine learning research. Previously, supervised learning methods achieved satisfactory recognition accura…
Bayesian Symbolic Regression
Ying Jin, Weilin Fu, Jian Kang +2
Interpretability is crucial for machine learning in many scenarios such as quantitative finance, banking, healthcare, etc. Symbolic regression (SR) is a classic interpretable machi…
Adaptive Regularization of Labels
Qianggang Ding, Sifan Wu, Hao Sun +2
Recently, a variety of regularization techniques have been widely applied in deep neural networks, such as dropout, batch normalization, data augmentation, and so on. These methods…