75 citations · 269 across the 19 of their papers we have counts for
5 papers · 1 filter
Reinforcement Learning for Quantitative Trading
Shuo Sun, Rundong Wang, Bo An
Quantitative trading (QT), which refers to the usage of mathematical models and data-driven techniques in analyzing the financial market, has been a popular topic in both academia…
Multi-Class Classification from Single-Class Data with Confidences
Yuzhou Cao, Lei Feng, Senlin Shu +4
Can we learn a multi-class classifier from only data of a single class? We show that without any assumptions on the loss functions, models, and optimizers, we can successfully lear…
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise
Hongxin Wei, Lue Tao, Renchunzi Xie +1
Learning with noisy labels is a practically challenging problem in weakly supervised learning. In the existing literature, open-set noises are always considered to be poisonous for…
On the Robustness of Average Losses for Partial-Label Learning
Jiaqi Lv, Biao Liu, Lei Feng +6
Partial-label learning (PLL) utilizes instances with PLs, where a PL includes several candidate labels but only one is the true label (TL). In PLL, identification-based strategy (I…
Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu +3
Weakly supervised learning has drawn considerable attention recently to reduce the expensive time and labor consumption of labeling massive data. In this paper, we investigate a no…