activity
20232025
most citedDivBO: Diversity-aware CASH for Ensemble Learning

4 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2025

MontePrep: Monte-Carlo-Driven Automatic Data Preparation without Target Data Instances

Congcong Ge, Yachuan Liu, Yixuan Tang +3

In commercial systems, a pervasive requirement for automatic data preparation (ADP) is to transfer relational data from disparate sources to targets with standardized schema specif…

cs.DC20252 cited

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data

Sheng Lin, Fangcheng Fu, Haoyang Li +5

With the breakthrough of Transformer-based pre-trained models, the demand for fine-tuning (FT) to adapt the base pre-trained models to downstream applications continues to grow, so…

eess.IV2025

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results

Xin Li, Kun Yuan, Bingchen Li +110

This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Qualit…

cs.DC2024

HC-SpMM: Accelerating Sparse Matrix-Matrix Multiplication for Graphs with Hybrid GPU Cores

Zhonggen Li, Xiangyu Ke, Yifan Zhu +2

Sparse Matrix-Matrix Multiplication (SpMM) is a fundamental operation in graph computing and analytics. However, the irregularity of real-world graphs poses significant challenges…

cs.CR2024

Enc2DB: A Hybrid and Adaptive Encrypted Query Processing Framework

Hui Li, Jingwen Shi, Qi Tian +4

As cloud computing gains traction, data owners are outsourcing their data to cloud service providers (CSPs) for Database Service (DBaaS), bringing in a deviation of data ownership…

cs.LG20234 cited

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…