activity
20222026
most citedTitle2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset

2 citations · 4 across the 26 of their papers we have counts for

collaborators
Showing 2024Show all

8 papers · 1 filter

cs.LG2024

Topology-aware Reinforcement Feature Space Reconstruction for Graph Data

Wangyang Ying, Haoyue Bai, Kunpeng Liu +1

Feature space is an environment where data points are vectorized to represent the original dataset. Reconstructing a good feature space is essential to augment the AI power of data…

cs.LG2024

Reinforcement Feature Transformation for Polymer Property Performance Prediction

Xuanming Hu, Dongjie Wang, Wangyang Ying +1

Polymer property performance prediction aims to forecast specific features or attributes of polymers, which has become an efficient approach to measuring their performance. However…

cs.LG2024

Revolutionizing Biomarker Discovery: Leveraging Generative AI for Bio-Knowledge-Embedded Continuous Space Exploration

Wangyang Ying, Dongjie Wang, Xuanming Hu +3

Biomarker discovery is vital in advancing personalized medicine, offering insights into disease diagnosis, prognosis, and therapeutic efficacy. Traditionally, the identification an…

cs.LG2024

Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning

Wangyang Ying, Dongjie Wang, Xuanming Hu +3

Feature transformation is to derive a new feature set from original features to augment the AI power of data. In many science domains such as material performance screening, while…

cs.LG2024★ 1 cited

Evolutionary Large Language Model for Automated Feature Transformation

Nanxu Gong, Chandan K. Reddy, Wangyang Ying +2

Feature transformation aims to reconstruct the feature space of raw features to enhance the performance of downstream models. However, the exponential growth in the combinations of…

cs.LG2024★ 1 cited

Neuro-Symbolic Embedding for Short and Effective Feature Selection via Autoregressive Generation

Nanxu Gong, Wangyang Ying, Dongjie Wang +1

Feature selection aims to identify the optimal feature subset for enhancing downstream models. Effective feature selection can remove redundant features, save computational resourc…

cs.LG2024

Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agent

Xinyuan Wang, Dongjie Wang, Wangyang Ying +3

Feature selection prepares the AI-readiness of data by eliminating redundant features. Prior research falls into two primary categories: i) Supervised Feature Selection, which iden…

cs.LG2024

Feature Selection as Deep Sequential Generative Learning

Wangyang Ying, Dongjie Wang, Haifeng Chen +1

Feature selection aims to identify the most pattern-discriminative feature subset. In prior literature, filter (e.g., backward elimination) and embedded (e.g., Lasso) methods have…