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Every paper Pith has read. Search by title, abstract, or pith.
6894 papers in stat · page 3
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ALO cuts conformal prediction runtime while matching coverage
Accelerating Conformal Prediction via Approximate Leave-One-Out
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Prior-informed model isolates T2D protein network changes
Prior-informed conditional Gaussian graphical models: an application to protein interaction network reconstruction
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Tabular foundation models calibrate conformal intervals on energy graphs
Relational and Sequential Conformal Inference for Energy Time Series over Graphs via Foundation Models
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First-order regret bounds now hold for MDPs despite unknown transitions
Policy Optimization Achieves Data-Dependent Regret Bounds in MDPs with Unknown Transitions
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Screening at state level then local refinement cuts nitrogen rates
Near-Optimal Nitrogen Recommendations for Precision Agriculture via Sequential Screening and Hierarchical Refinement
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Gaussian kernel regression gains sandwich variance and bootstrap
Statistical Inference for Gaussian Kernel Robust Regression with the gkrreg Package
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Forecast sequences are auto-calibrated exactly when they form martingales
Calibrated Probability Forecast Sequences and Measure-Valued Martingales
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Optimal split minimizes conformal prediction interval length
On Optimal Data Splitting for Split Conformal Prediction
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Binary reduction separates error roles in minimax testing bounds
High-Confidence Minimax Testing with Prescribed Errors
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Reverse KL regularization yields global convergence for SAIL
On the Convergence of Self-Improving Online LLM Alignment
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FPCA rates for manifold-indexed data depend on intrinsic dimension d
Functional Principal Component Analysis for Manifold-Indexed Data
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Limited adaptivity yields kappa-free regret for slate GLM bandits
Contextual Slate GLM Bandits with Limited Adaptivity
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Langevin dynamics concentrate on hidden indices below temperature 1
The Geometry of Statistical Feature Learning in Mean-Field Langevin Dynamics
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Raw scores beat demographic corrections for some classifications
On the choice of using raw or demographically-corrected scores
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Calibration merges survey samples to sharpen regression estimates
Improving Efficiency of Regression Analyses by Integrating Data from Population-Representative Surveys: A Model-Assisted Calibration Approach
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Renyi inequalities characterize majorization of statistical experiments
Multivariate majorization of continuous statistical experiments
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New methods enable simultaneous bands for incomplete functional time series
Simultaneous Inference for Partially Observed Functional Time Series
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Constrained k-means recovers true centers from magnitude-decaying MNAR data
MNAR-$k$-means: A $k$-means Clustering for Data Missing Not at Random with Magnitude-Decaying Probability
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Algorithm recovers graph from one Glauber trajectory without mixing
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
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Average propensity sets semiparametric bound for sequential experiments
Semiparametric Efficiency in Sequential Experiments: Characterization and Design via Average Propensity
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Sequential designs match i.i.d
Semiparametric Efficiency in Sequential Experiments: Characterization and Design via Average Propensity
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Tabular in-context learners match on protein fitness with fixed reps
Can Tabular In-Context Learners Generalize to Biomolecular Property Prediction?
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BAR penalty with smoothing yields oracle rank regression for censored data
Censored broken adaptive ridge rank regression via induced smoothing
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Hybrid swap cuts cost of dynamic GP inference on disjoint grids
Dynamic Gaussian Processes and the Vanilla-SPDE Exchange
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Two-stage method estimates parameters and Lévy densities in switching jumps
Two-stage semiparametric inference for regime-switching jump diffusions with unknown L\'evy densities
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Bayesian model turns RCV poll counts into win probabilities
Bayesian Uncertainty Quantification for Ranked Choice Voting Polls
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Debiased ML with Bayesian priors estimates supply effects on bookings
Estimating Supply Incrementality in Two-sided Marketplaces: A Causal Machine Learning Approach
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GP model adds terrain data for better wind power predictions
Spatio-Temporal Gaussian Process for Building Terrain-Incorporating Wind Power Curves
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Sparse tree chains match ensemble accuracy for most samples
Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again
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Hybrid PCA estimator is asymptotically normal for leading eigenvector
Hybrid principal component analysis in multivariate allometric regression
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Clustering on spend correlations separates marketing channel effects
Hierarchical Clustering As a Novel Solution to the Notorious Multicollinearity Problem in Observational Causal Inference
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Exchangeable bootstrap plus box calibration fixes hazard band coverage
Simultaneous confidence bands for cumulative hazard via exchangeable bootstrap and box calibration
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Edge sampling yields finite-sample error control for network tests
Universal Inference for model selection on networks
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Residual-on-residual regression stabilizes causal estimates
Residual-on-Residual Regression as a Tool for Effect Estimation in Observational Data
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Dual-TV regularizers bound tensor error near minimax rate
Exponential-Family Tensor Completion via Nonconvex Dual Total-Variation Regularization
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Personalized thresholds lift job marketplace metrics while respecting guardrails
Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments: Evidence from a Job Marketplace
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SGD self-stabilizes at edge of stability for large steps
SGD at the Edge of Stability: Stochastic Stabilization with Large Learning Rates
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Noisy experts force exponential horizon dependence for offline imitation
Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback
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Cluster-level cross-fitting fixes coverage in survey TMLE
Cross-Fitted Survey-Weighted TMLE with Design-Based Variance for Causal Machine Learning
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Neural network forecasts next alternating event time
Dynamic Prediction of Alternating Recurrent Events via Neural Network
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Regenerative chains get data-dependent DKW bands
A data-dependent DKW inequality for regenerative Markov chains
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New method estimates largest minimizer for regression change points
Analysis of gradual changes in nonparametric regression based on a new optimization method in the non-unique case
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Random forest plateau tuning settles at ensemble size scaling as 1/ε²
A Stationary-Distribution Theory for Triplet-Based Plateau Search in Random Forest Ensemble-Size Selection
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Matrix products converge to free log-normal spectral law
Geometric Dyson Brownian Motions and the Free Log-Normal Limit for a Non-Square Product of Random Matrices
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Extended counting theory identifies scattering network design factors
Separation Capacity of Scattering Networks
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Error models outperform lag models for census non-response prediction
Spatial Dependence in the Self-Response: Spatial Dependence, Modeling, and Operational Consequences
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Closed-form inertial model fits GRPO reward curves at R² ≥ 0.91
Predictable GRPO: A Closed-Form Model of Training Dynamics
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GRPO training follows a closed-form damped oscillator
Predictable GRPO: A Closed-Form Model of Training Dynamics
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Conservative offline training increases reward hacking in online adaptation
Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models
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Norms encode semantic specificity in contrastive embeddings
Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms