11 citations · 53 across the 14 of their papers we have counts for
7 papers · 1 filter
Random at First, Fast at Last: NTK-Guided Fourier Pre-Processing for Tabular DL
Renat Sergazinov, Jing Wu, Shao-An Yin
While random Fourier features are a classic tool in kernel methods, their utility as a pre-processing step for deep learning on tabular data has been largely overlooked. Motivated…
TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data
Suiyao Chen, Jing Wu, Yunxiao Wang +6
Representation learning is a fundamental aspect of modern artificial intelligence, driving substantial improvements across diverse applications. While selfsupervised contrastive le…
The New Agronomists: Language Models are Experts in Crop Management
Jing Wu, Zhixin Lai, Suiyao Chen +3
Crop management plays a crucial role in determining crop yield, economic profitability, and environmental sustainability. Despite the availability of management guidelines, optimiz…
SwitchTab: Switched Autoencoders Are Effective Tabular Learners
Jing Wu, Suiyao Chen, Qi Zhao +9
Self-supervised representation learning methods have achieved significant success in computer vision and natural language processing, where data samples exhibit explicit spatial or…
ReConTab: Regularized Contrastive Representation Learning for Tabular Data
Suiyao Chen, Jing Wu, Naira Hovakimyan +1
Representation learning stands as one of the critical machine learning techniques across various domains. Through the acquisition of high-quality features, pre-trained embeddings s…
Balanced Training for Sparse GANs
Yite Wang, Jing Wu, Naira Hovakimyan +1
Over the past few years, there has been growing interest in developing larger and deeper neural networks, including deep generative models like generative adversarial networks (GAN…
Optimizing Nitrogen Management with Deep Reinforcement Learning and Crop Simulations
Jing Wu, Ran Tao, Pan Zhao +2
Nitrogen (N) management is critical to sustain soil fertility and crop production while minimizing the negative environmental impact, but is challenging to optimize. This paper pro…