Search Results for author:
Found 7 papers, 3 papers with code
Self-Supervised Learning for User Localization
Following this, we utilize the encoder portion of the AE models to extract relevant features from labeled data, and finetune an MLP-based Position Estimation Model to accurately deduce user locations.
From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing
This paper comprehensively reviews the application of machine learning (ML) and AI in finance, specifically in the context of asset pricing.
RAGIC: Risk-Aware Generative Adversarial Model for Stock Interval Construction
This promising outcome suggests that our approach effectively addresses the challenges of stock market prediction while incorporating vital risk considerations.
HI-GAN: Hierarchical Inpainting GAN with Auxiliary Inputs for Combined RGB and Depth Inpainting
To address the above challenges, we propose Hierarchical Inpainting GAN (HI-GAN), a novel approach comprising three GANs in a hierarchical fashion for RGBD inpainting.
Margin Trader: A Reinforcement Learning Framework for Portfolio Management with Margin and Constraints
In the field of portfolio management using reinforcement learn- ing, existing approaches have mainly focused on cash-only trading, overlooking the potential benefits and risks of margin trading.
Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative Network
Predicting the Stock movement attracts much attention from both industry and academia.
SafeLight: A Reinforcement Learning Method toward Collision-free Traffic Signal Control
Traffic signal control is safety-critical for our daily life.
