statistical properties
Characteristics that describe how an AI model behaves with respect to probability and statistics, including aspects like bias, variance, consistency, and convergence, which are critical for evaluating model reliability.
- Computational Efficiency under Covariate Shift in Kernel Ridge Regression
- Convolution Goes Higher-Order: A Biologically Inspired Mechanism Empowers Image Classification
- Efficient Randomized Experiments Using Foundation Models
- Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
- Feature-aware Modulation for Learning from Temporal Tabular Data
- Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation
- On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts
- On the Stability of Graph Convolutional Neural Networks: A Probabilistic Perspective
- Secure and Confidential Certificates of Online Fairness
- Unraveling Metameric Dilemma for Spectral Reconstruction: A High-Fidelity Approach via Semi-Supervised Learning
- Vertical Federated Feature Screening