Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
Обновлено 2024-11-13 06:41:06 +03:00
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Обновлено 2024-07-03 13:54:08 +03:00
Multi-species bioacoustic classification using deep learning algorithms
Обновлено 2024-06-18 01:58:08 +03:00
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Обновлено 2024-02-23 11:45:58 +03:00
A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
Обновлено 2024-02-15 16:24:04 +03:00
An algorithm for cross-domain NL2SQL
Обновлено 2023-07-22 23:20:17 +03:00
Synthesizer for optimal collective communication algorithms
Обновлено 2023-07-21 21:16:40 +03:00
A novel embedding training algorithm leveraging ANN search and achieved SOTA retrieval on Trec DL 2019 and OpenQA benchmarks
Обновлено 2023-06-13 00:27:31 +03:00
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Обновлено 2023-06-12 21:22:32 +03:00
Logarithmic Reinforcement Learning
Обновлено 2023-03-25 04:36:23 +03:00
Algorithms to find Bertrand Nash equilibria in pricing games
Обновлено 2022-11-28 22:12:35 +03:00
This is the implementation of the TextNAS algorithm proposed in the paper TextNAS: A Neural Architecture Search Space tailored for Text Representation.
Обновлено 2022-11-28 22:09:08 +03:00
Algorithms to find consecutive integers that are smooth
Обновлено 2022-09-09 21:16:12 +03:00