Search Results for author:
Found 7 papers, 1 papers with code
User-Oriented Smart General AI System under Causal Inference
An inevitable component of general AI is tacit knowledge that depends upon user-specific comprehension of task information and individual model design preferences that are related to user technical experiences.
A Brief Summary of Interactions Between Meta-Learning and Self-Supervised Learning
Meta-learning can be applied to improve model generalization capability and to construct general AI algorithms.
A Brief Survey of Associations Between Meta-Learning and General AI
This paper briefly reviews the history of meta-learning and describes its contribution to general AI.
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
Unlike deep learning, meta-learning can be applied to few-shot high-dimensional datasets and considers further improving model generalization to unseen tasks.
Measurement Error in Nutritional Epidemiology: A Survey
This article reviews bias-correction models for measurement error of exposure variables in the field of nutritional epidemiology.
Holding-Based Evaluation upon Actively Managed Stock Mutual Funds in China
We conclude that most actively managed funds have positive stock selection ability but not asset allocation ability, which is due to the difficulty in predicting policy changes.
Post-Lasso Inference for High-Dimensional Regression
In this paper, we consider variable selection from a new perspective motivated by the frequently occurred phenomenon that relevant variables are not completely distinguishable from noise variables on the solution path.
Methodology
