3 citations · 6 across the 8 of their papers we have counts for
9 papers
ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB
Yifan Wu, Yuhan Li, Zhenhua Wang +6
Cloud-native serverless data warehouses achieve fine-grained elasticity by decoupling storage from compute, yet determining the optimal resource allocation for highly heterogeneous…
SafeLoad: Efficient Admission Control Framework for Identifying Memory-Overloading Queries in Cloud Data Warehouses
Yifan Wu, Yuhan Li, Zhenhua Wang +8
Memory overload is a common form of resource exhaustion in cloud data warehouses. When database queries fail due to memory overload, it not only wastes critical resources such as C…
TableCopilot: A Table Assistant Empowered by Natural Language Conditional Table Discovery
Lingxi Cui, Guanyu Jiang, Huan Li +3
The rise of LLM has enabled natural language-based table assistants, but existing systems assume users already have a well-formed table, neglecting the challenge of table discovery…
HMI: Hierarchical Knowledge Management for Efficient Multi-Tenant Inference in Pretrained Language Models
Jun Zhang, Jue Wang, Huan Li +6
The significant computational demands of pretrained language models (PLMs), which often require dedicated hardware, present a substantial challenge in serving them efficiently, esp…
NLCTables: A Dataset for Marrying Natural Language Conditions with Table Discovery
Lingxi Cui, Huan Li, Ke Chen +2
With the growing abundance of repositories containing tabular data, discovering relevant tables for in-depth analysis remains a challenging task. Existing table discovery methods p…
A Comprehensive Study of Shapley Value in Data Analytics
Hong Lin, Shixin Wan, Zhongle Xie +4
Over the recent years, Shapley value (SV), a solution concept from cooperative game theory, has found numerous applications in data analytics (DA). This paper presents the first co…
Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI
Lingxi Cui, Huan Li, Ke Chen +2
Machine learning (ML) on tabular data is ubiquitous, yet obtaining abundant high-quality tabular data for model training remains a significant obstacle. Numerous works have focused…
FL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
Hong Lin, Lidan Shou, Ke Chen +2
Federated learning (FL) is a promising approach for learning a model from data distributed on massive clients without exposing data privacy. It works effectively in the ideal feder…
CARAT: Contrastive Feature Reconstruction and Aggregation for Multi-Modal Multi-Label Emotion Recognition
Cheng Peng, Ke Chen, Lidan Shou +1
Multi-modal multi-label emotion recognition (MMER) aims to identify relevant emotions from multiple modalities. The challenge of MMER is how to effectively capture discriminative f…