6 papers
DSAEval: Evaluating Data Science Agents on a Wide Range of Real-World Data Science Problems
Maojun Sun, Yifei Xie, Yue Wu +5
Recent LLM-based data agents aim to automate data science tasks ranging from data analysis to deep learning. However, the open-ended nature of real-world data science problems, whi…
A Survey on Large Language Model-based Agents for Statistics and Data Science
Maojun Sun, Ruijian Han, Binyan Jiang +4
In recent years, data science agents powered by Large Language Models (LLMs), known as "data agents," have shown significant potential to transform the traditional data analysis pa…
LAMBDA: A Large Model Based Data Agent
Maojun Sun, Ruijian Han, Binyan Jiang +4
We introduce LArge Model Based Data Agent (LAMBDA), a novel open-source, code-free multi-agent data analysis system that leverages the power of large language models. LAMBDA is des…
Adaptive sieving: A dimension reduction technique for sparse optimization problems
Yancheng Yuan, Meixia Lin, Defeng Sun +1
In this paper, we propose an adaptive sieving (AS) strategy for solving general sparse machine learning models by effectively exploring the intrinsic sparsity of the solutions, whe…
HOT: An Efficient Halpern Accelerating Algorithm for Optimal Transport Problems
Guojun Zhang, Zhexuan Gu, Yancheng Yuan +1
This paper proposes an efficient HOT algorithm for solving the optimal transport (OT) problems with finite supports. We particularly focus on an efficient implementation of the HOT…
Accelerating preconditioned ADMM via degenerate proximal point mappings
Defeng Sun, Yancheng Yuan, Guojun Zhang +1
In this paper, we aim to accelerate a preconditioned alternating direction method of multipliers (pADMM), whose proximal terms are convex quadratic functions, for solving linearly…