45 citations · 98 across the 11 of their papers we have counts for
11 papers
SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms
Yu Shen, Shiyang Liu, Qihang He +14
Big data platforms are widely used in modern enterprises, and an in-production intelligent assistant is increasingly important to help users quickly find actionable guidance and re…
SQLGovernor: An LLM-powered SQL Toolkit for Real World Application
Jie Jiang, Siqi Shen, Haining Xie +8
SQL queries in real world analytical environments, whether written by humans or generated automatically often suffer from syntax errors, inefficiency, or semantic misalignment, esp…
DataLab: A Unified Platform for LLM-Powered Business Intelligence
Luoxuan Weng, Yinghao Tang, Yingchaojie Feng +18
Business intelligence (BI) transforms large volumes of data within modern organizations into actionable insights for informed decision-making. Recently, large language model (LLM)-…
SiriusBI: A Comprehensive LLM-Powered Solution for Data Analytics in Business Intelligence
Jie Jiang, Haining Xie, Siqi Shen +12
With the proliferation of Large Language Models (LLMs) in Business Intelligence (BI), existing solutions face critical challenges in industrial deployments: functionality deficienc…
Towards General and Efficient Online Tuning for Spark
Yang Li, Huaijun Jiang, Yu Shen +8
The distributed data analytic system -- Spark is a common choice for processing massive volumes of heterogeneous data, while it is challenging to tune its parameters to achieve hig…
OpenBox: A Python Toolkit for Generalized Black-box Optimization
Huaijun Jiang, Yu Shen, Yang Li +5
Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face chall…
DivBO: Diversity-aware CASH for Ensemble Learning
Yu Shen, Yupeng Lu, Yang Li +3
The Combined Algorithm Selection and Hyperparameters optimization (CASH) problem is one of the fundamental problems in Automated Machine Learning (AutoML). Motivated by the success…
Rover: An online Spark SQL tuning service via generalized transfer learning
Yu Shen, Xinyuyang Ren, Yupeng Lu +6
Distributed data analytic engines like Spark are common choices to process massive data in industry. However, the performance of Spark SQL highly depends on the choice of configura…
DFG-NAS: Deep and Flexible Graph Neural Architecture Search
Wentao Zhang, Zheyu Lin, Yu Shen +3
Graph neural networks (GNNs) have been intensively applied to various graph-based applications. Despite their success, manually designing the well-behaved GNNs requires immense hum…
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning
Yang Li, Yu Shen, Huaijun Jiang +4
With the extensive applications of machine learning models, automatic hyperparameter optimization (HPO) has become increasingly important. Motivated by the tuning behaviors of huma…
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm
Wentao Zhang, Yu Shen, Zheyu Lin +6
Graph neural networks (GNNs) have achieved state-of-the-art performance in various graph-based tasks. However, as mainstream GNNs are designed based on the neural message passing m…