statistical inference
The process of drawing conclusions about populations based on samples of data, using statistical methods. It forms the basis for many AI techniques, enabling the generalization of insights beyond the training data.
- An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds
- An Optimized Franz-Parisi Criterion and its Equivalence with SQ Lower Bounds
- Asymptotic theory of SGD with a general learning-rate
- Bayesian Concept Bottleneck Models with LLM Priors
- Bridging Human and LLM Judgments: Understanding and Narrowing the Gap
- DMWM: Dual-Mind World Model with Long-Term Imagination
- DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testing
- Efficient Randomized Experiments Using Foundation Models
- Handling Missing Responses under Cluster Dependence with Applications to Language Model Evaluation
- Network two-sample test for block models
- Optimal community detection in dense bipartite graphs
- PUATE: Efficient ATE Estimation from Treated (Positive) and Unlabeled Units
- Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
- Statistical Inference for Gradient Boosting Regression
- Statistical Inference under Performativity
- Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
- Valid Selection among Conformal Sets
- When Data Can't Meet: Estimating Correlation Across Privacy Barriers