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Found 3 papers, 1 papers with code
Can Perturbations Help Reduce Investment Risks? Risk-Aware Stock Recommendation via Split Variational Adversarial Training
By lowering the volatility of the stock recommendation model, SVAT effectively reduces investment risks and outperforms state-of-the-art baselines by more than 30% in terms of risk-adjusted profits.
HINNPerf: Hierarchical Interaction Neural Network for Performance Prediction of Configurable Systems
Due to the complex interactions among multiple options and the high cost of performance measurement under a huge configuration space, it is challenging to study how different configurations influence the system performance.
Towards Better Forecasting by Fusing Near and Distant Future Visions
Multivariate time series forecasting is an important yet challenging problem in machine learning.
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