Category: Statistics
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Uncovering Causal Relationships in Observational Data
K-Nearest Neighbor Method Achieves Excellent Estimation Performance in Synthetic Labeling: A Non-Asymptotic Study
Vanishing Bias in Machine Learning Algorithms: A Comprehensive Review
Scalable Learning of Bayesian Neural Networks with Probabilistic Backpropagation
Uncertainty-Aware Learning to Address Residual Noise
Limits of Deep Learning in Critical Applications: Privacy Attacks and Differentially Private Generative Models
Elegant Closed Form Solutions for Partially Lifted Random Duality Theory
Algorithmic Insights into Stochastic Recommendation Systems
Uncertainty Quantification in Machine Learning Models: A Comparative Study of Surrogate Modeling Approaches
Uplift Modeling Heteroskedasticity: A Systematic Bias in Treatment Effect Estimation
Sequential Inductive Prediction Intervals: Leveraging New Data for Improved Accuracy
Improving Lightning Waveform Classification with Deep Convolutional Neural Networks
Bayesian Deep Learning and Probabilistic Perspective of Generalization
Personalized Feature Extraction through Factor Analysis: A Federated Learning Approach
Data-Driven Approach to COVID-19 Forecasting: A Survey of Recent Methods
Uncovering Local Outliers in Data: A Gaussian Mixture Model Approach
Out-of-Distribution Generalization via Risk Extrapolation: A New Principle for Nonlinear ICA
Uncovering Hidden Confounding in Observational Studies: A Machine Learning Approach
