Search Results for author:
Found 7 papers, 4 papers with code
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning
For unsupervised feature set representation pretraining, we regard a feature set as a feature-feature interaction graph, and develop an unsupervised graph contrastive learning encoder to embed feature sets into vectors.
Evolutionary Large Language Model for Automated Feature Transformation
Feature transformation aims to reconstruct the feature space of raw features to enhance the performance of downstream models.
Neuro-Symbolic Embedding for Short and Effective Feature Selection via Autoregressive Generation
Within the learned embedding space, we leverage a multi-gradient search algorithm to find more robust and generalized embeddings with the objective of improving model performance and reducing feature subset redundancy.
Feature Selection as Deep Sequential Generative Learning
(2) We leverage the trained feature subset utility evaluator as a gradient provider to guide the identification of the optimal feature subset embedding;(3) We decode the optimal feature subset embedding to autoregressively generate the best feature selection decision sequence with autostop.
Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agent
A deep Q-network, pre-trained with the original features and their corresponding pseudo labels, is employed to improve the efficacy of the exploration process in feature selection.
Self-optimizing Feature Generation via Categorical Hashing Representation and Hierarchical Reinforcement Crossing
Feature generation aims to generate new and meaningful features to create a discriminative representation space. A generated feature is meaningful when the generated feature is from a feature pair with inherent feature interaction.
Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset
To the best of our knowledge, it is currently the largest manually-annotated Chinese dataset for open event extraction.
