24 citations · 26 across the 5 of their papers we have counts for
5 papers
Auto-FP: An Experimental Study of Automated Feature Preprocessing for Tabular Data
Danrui Qi, Jinglin Peng, Yongjun He +1
Classical machine learning models, such as linear models and tree-based models, are widely used in industry. These models are sensitive to data distribution, thus feature preproces…
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
Qiang Huang, Jiawei Jiang, Xi Susie Rao +10
To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed. Despite the success of these TGN…
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees
Jue Wang, Binhang Yuan, Luka Rimanic +5
Communication compression is a crucial technique for modern distributed learning systems to alleviate their communication bottlenecks over slower networks. Despite recent intensive…
Decentralized Training of Foundation Models in Heterogeneous Environments
Binhang Yuan, Yongjun He, Jared Quincy Davis +6
Training foundation models, such as GPT-3 and PaLM, can be extremely expensive, often involving tens of thousands of GPUs running continuously for months. These models are typicall…
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Xiangru Lian, Binhang Yuan, Xuefeng Zhu +24
Deep learning based models have dominated the current landscape of production recommender systems. Furthermore, recent years have witnessed an exponential growth of the model scale…