Search Results for author:
Found 6 papers, 1 papers with code
Research on Optimizing Real-Time Data Processing in High-Frequency Trading Algorithms using Machine Learning
High-frequency trading (HFT) represents a pivotal and intensely competitive domain within the financial markets.
DataGpt-SQL-7B: An Open-Source Language Model for Text-to-SQL
In addressing the pivotal role of translating natural language queries into SQL commands, we propose a suite of compact, fine-tuned models and self-refine mechanisms to democratize data access and analysis for non-expert users, mitigating risks associated with closed-source Large Language Models.
Ranked #1 on
Text-To-SQL
on spider
(Exact Match Accuracy (Dev) metric, using extra
training data)
Patent Value Characterization -- An Empirical Analysis of Elevator Industry Patents
The global patent application count has steadily increased, achieving eight consecutive years of growth. The global patent industry has shown a general trend of expansion.
Physics Symbolic Learner for Discovering Ground-Motion Models Via NGA-West2 Database
Ground-motion model (GMM) is the basis of many earthquake engineering studies.
Federated Learning Hyper-Parameter Tuning from a System Perspective
In this paper, we propose FedTune, an automatic FL hyper-parameter tuning algorithm tailored to applications' diverse system requirements in FL training.
Client Selection in Federated Learning: Principles, Challenges, and Opportunities
As a privacy-preserving paradigm for training Machine Learning (ML) models, Federated Learning (FL) has received tremendous attention from both industry and academia.
