research
∙
05/25/2023
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning
In the field of quantitative trading, it is common practice to transform...
share
research
∙
03/21/2023
Style Miner: Find Significant and Stable Explanatory Factors in Time Series with Constrained Reinforcement Learning
In high-dimensional time-series analysis, it is essential to have a set ...
research
∙
07/22/2022
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution
Optimal execution is a sequential decision-making problem for cost-savin...
research
∙
08/13/2021
Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback
The delayed feedback problem is one of the imperative challenges in onli...
research
∙
07/18/2021
GuideBoot: Guided Bootstrap for Deep Contextual Bandits
The exploration/exploitation (E E) dilemma lies at the core of interac...
research
∙
10/10/2020
Trust the Model When It Is Confident: Masked Model-based Actor-Critic
It is a popular belief that model-based Reinforcement Learning (RL) is m...
research
∙
05/24/2020
GoChat: Goal-oriented Chatbots with Hierarchical Reinforcement Learning
A chatbot that converses like a human should be goal-oriented (i.e., be ...
research
∙
05/26/2019
Towards reliable and fair probabilistic predictions: field-aware calibration with neural networks
In machine learning, it is observed that probabilistic predictions somet...
research
∙
04/25/2019
Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings
Click-through rate (CTR) prediction has been one of the most central pro...
research
∙
11/18/2018
Policy Optimization with Model-based Explorations
Model-free reinforcement learning methods such as the Proximal Policy Op...
research
∙
02/12/2018
