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Every paper Pith has read. Search by title, abstract, or pith.
883 papers in math.ST · page 5
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Extending sigma-algebra restores L1-L∞ duality for uncertain measures
Can the $L^1$-$L^\infty$ duality be restored for non-dominated families of probability measures?
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Isotropic normalization yields consistent dynamic network trajectories
Multiscale Euclidean Network Trajectories: Second-Moment Geometry, Attribution, and Change Points
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Normalization removes ambiguity from network time trajectories
Multiscale Euclidean Network Trajectories: Second-Moment Geometry, Attribution, and Change Points
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Generic kernels place models transversely to degeneracy loci
Transversality and Geometric Regularisation in Distributional Statistical Models
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An augmented transfer regression estimator recovers regression parameters when covariates…
Augmented transfer regression learning for completely missing covariates
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Mean independence identifies source nodes generically
Causal discovery under mean independence and linearity
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Perturbing prefixes improves language model extrapolation
Perturbation is All You Need for Extrapolating Language Models
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Threshold breakdown point finds smallest contamination fraction to force estimator shift
The Threshold Breakdown Point
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Threshold breakdown point finds smallest contamination to alter estimators
The Threshold Breakdown Point
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Thinned quantile share is unconditionally feasible
Thinned Quantile Shares are Universally Feasible
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Purification links mixed-state metrology bounds to pure states with extra parameters
Quantum metrology of mixed states via purification
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Power can fall when adding more permutations to Monte Carlo tests
More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests
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Consistent metric loss learning possible iff no infinite Littlestone trees
Realizable Bayes-Consistency for General Metric Losses
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No infinite gamma-Littlestone tree means realizable Bayes consistency
Realizable Bayes-Consistency for General Metric Losses
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Bernstein intervals deliver safe coverage and minimax widths for kernel smoothers
Empirical Bernstein Confidence Intervals for Kernel Smoothers: A Safe and Sharp Way to Exhaust Assumed Smoothness
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Bernstein bounds give kernel smoothers safe minimax intervals
Empirical Bernstein Confidence Intervals for Kernel Smoothers: A Safe and Sharp Way to Exhaust Assumed Smoothness
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Ordering constraint improves estimates of scale powers in exponentials
Improved estimation of positive powers of scale parameters of exponential distributions under a prior information
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Vanishing L2 regularization converges softmax MAB
Vanishing L2 regularization for the softmax Multi Armed Bandit
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Spike rate parameters estimated efficiently in large neuron networks
LAN property for the parameter of the jump rate in mean field interacting systems of neurons
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Shrinking partitions yield asymptotic normality for jump process rates
Local estimation of transition rates of jump processes through discretization
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T-posterior produces randomised estimators with non-asymptotic bounds
Statistical Inference via T-Posterior Randomised Estimators
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Gamma smoothing yields optimal rates and shorter EB intervals for Poisson data
Poisson Empirical Bayes via Gamma-Smoothed Nonparametric Maximum Likelihood
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Smoothness improves rates for Wasserstein barycenters
Smoothed estimation of Wasserstein barycenters
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Classifier enforces user bound on positives to raise minority detection
Imbalanced Classification under Capacity Constraints
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Population covariates with survey data identify small-area treatment effects
Causal Small Area Estimation with Survey-only Covariates
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Kernel discrepancy defines intrinsic ESS for manifold MCMC
Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
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Martingales get Gaussian bounds at n^{-1/4} rate with polylog(d) cost
Berry-Esseen bounds for multivariate martingale difference sequences in the Kolmogorov distance
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Tweedie kernels unify estimation of zero-inflated densities
Tweedie-based nonparametric estimation for semicontinuous mixed densities
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Uncountably many inaccessible decisions exist in every finite probability space
Uncountably many conditionally inaccessible decisions exist in every finite probability space
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Schur-concave copulas equal closure of associative convex hulls
Characterizing Schur-concave commutative copulas as the closure of associative ones
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Schur-concave commutative copulas equal closure of associative copula hull
Characterizing Schur-concave commutative copulas as the closure of associative ones
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Stats framework recovers behavioral parameters from daily traffic trajectories
Statistical Inference of Day-to-Day Traffic Dynamics
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Variance mismatch biases means only in low-SNR Gaussian mixtures
The interplay of signal-to-noise ratio and variance misspecification in Gaussian mixtures
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Uniform representation yields simultaneous confidence regions for time series
Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
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Moments of group functions computed from Fourier coefficients alone
Statistics of a multi-factor function from its Fourier transform
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The paper gives matching upper and lower bounds on the number of samples needed for…
On the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization
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Risk parameter unifies MML with NML minimax coding
Entropic Strict Minimum Message Length and Its Connections to PAC-Bayes and NML
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Risk parameter tunes MML from Bayesian to minimax
Entropic Strict Minimum Message Length and Its Connections to PAC-Bayes and NML
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Eigenvalue method cuts Monte Carlo paths from 1M to 10
Fast Monte-Carlo
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Polynomial approximation controls regret by Hellinger distance in Gaussian empirical Bayes
Sharp regret-Hellinger bounds for Gaussian empirical Bayes via polynomial approximation
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Two-step method estimates quantiles of panel slope heterogeneity
Estimation and Inference for the $\tau$-Quantile of Individual Heterogeneous Coefficient
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Extreme value theory enables extrapolation beyond training data
Extrapolation in Statistical Learning with Extreme Value Theory
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Estimator recovers latent clusters and matches oracle rates
Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality
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ECE stays low despite high overconfidence risk
Beyond ECE: Calibrated Size Ratio, Risk Assessment, and Confidence-Weighted Metrics
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Adaptive CATE model stabilizes policy-value estimates under weak overlap
Adaptive Targeted Maximum Likelihood Estimation of the Mean Potential Outcome under a Treatment Rule
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The paper proves that scale-invariant upper bounds on self-normalized martingales exist…
Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression
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Ranked set sampling improves quantile estimator efficiency
L-Estimation of Population Quantiles Using Ranked Set Sampling
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Uniform generators speed Pearson IV sampling for all shapes
The Pearson IV distribution: Random variate generation and applications
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Truncation bias sets floor for high-dimensional mean testing
Mean Testing under Truncation beyond Gaussian
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Quantile TVD solutions form exact minmax intervals at each point
An Exact Pointwise Characterization for Total Variation Denoising in Quantile Regression