How Eviction Court Governs: A Statistical Analysis of Bargaining, Templates, and Debt in Philadelphia - 惯性聚合

推荐订阅源

Help Net Security

Future of Privacy Forum

The GitHub Blog

博客园 - 叶小钗

阮一峰的网络日志

Kaspersky official blog

Google Developers Blog

freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

Privacy International News Feed

Cyber Attacks, Cyber Crime and Cyber Security

News | PayPal Newsroom

Schneier on Security

Microsoft Azure Blog

The Hacker News

Stack Overflow Blog

Security Latest

Microsoft Research Blog - Microsoft Research

Google Online Security Blog

博客园_首页

CXSECURITY Database RSS Feed - CXSecurity.com

Google DeepMind News

Y Combinator Blog

The Cloudflare Blog

Microsoft Security Blog

Cisco Talos Blog

钛媒体：引领未来商业与生活新知

Troy Hunt's Blog

Fox-IT International blog

Security @ Cisco Blogs

博客园 - 司徒正美

cs.CV updates on arXiv.org

Comments on: Blog

Threat Intelligence Blog | Flashpoint

LINUX DO - 最新话题

Tailwind CSS Blog

stat updates on arXiv.org

Spiking the training data to correct for test set contamination Optimal Non-Asymptotic Edgeworth Expansions for Multivariate Neural Network Outputs Causality as the Statistical Conscience of Artificial Intelligence: From Pearl's Ladder to Trustworthy Machines Detecting Metastable Basins in High Dimensions via Marginal Trajectory Distribution Discrimination Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction MEDAL: Manifold Embedding Distillation via Autoencoder Learning Multicalibration Boosting: Theory, Convergence, and Transferability Clustering based on Stochastic Dominance with application for risk averters and risk seekers Affinity Graph Connectivity in Convex Clustering On the Sample Complexity of Robust Binary Hypothesis Testing How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis Estimating Mixture Distributions via Stochastic Mirror Descent Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy Counterfactually Safe Reinforcement Learning Possession-Level Player Impact in the Pre-Play-by-Play NBA Era: A Video-Reconstructed RAPM Database, 1984--1996 Convergence and non-asymptotic error analysis for kinetic Langevin samplers using the exact harmonic Langevin integrator PCA score regression: the art of losing power Heritability: A Counterfactual Perspective Long Memory in Intrinsically Dynamic Factor Models Modified treatment policies that depend on the natural history of treatment Post-Processing Posterior Predictive P-values Scalable Gaussian Process for Learning Non-Ergodic Ground Motion Model from Physics-Based Simulations with Application to Power Infrastructure Assessment Using the target trial framework for combining information: external comparator analyses and other applications Trustworthy AI/ML Regression and Unbiased Causal Inference for Real-World Data Synthetic Heterogeneous-Effects LASSO: A Fixed-effects Estimation Approach for High-dimensional Mixed-effects Models Bayesian Conformal-Projective Prediction Shared hidden-factor information framework for multiple behavioral tasks Consistent Identification of Top-$K$ Nodes in Noisy Networks Adaptable High-Dimensional Change Point Detection via Ridge Regularization Logistic regression is not enough: The need for Bayesian nonparametric modelling for causal inference using observational data, exemplified by the 'gateway' effect Distributional Conformal Prediction for Markov Processes Deep Regression for Repeated Measurements under Covariate Shift Optimal Estimation of Discrete Multiview Distributions under Heteroskedastic Multinomial Sampling Information-Theoretic Reliability is Robust to Analytic Choice: A 24-Specification Multiverse on Public Cognitive Test-Retest Data Shared Keyboard: An improved Bayesian design for phase I clinical trials via Beta kernel process HawkesLLM: Semantic Uncertainty Propagation in Agentic Text Simulation When Is Next-Token Prediction Useful? Marginalization, Ergodicity, Mixture Identifiability, Local Sufficiency, RAG, Tools, and Programming Approximate Machine Unlearning through Manifold Representation Forgetting Guided by Self Mode Connectivity Human-Centered Learning Mechanics: A Dynamical Framework for Entropy-Regulated Representation Learning Anytime Training with Schedule-Free Spectral Optimization Robust OT-Guided Generative Residual Domain Adaptation for Bike-Sharing Demand Prediction under Temporal Domain Shift Any-Dimensional Invariant Universality Understanding and Improving Noisy Embedding Techniques in Instruction Finetuning KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis Instance-Optimal Estimation with Multiple LLM Judges on a Budget Optimal Dimension-Free Sampling for Regularized Classification Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Training-Free Looped Transformers Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Uncertainty-aware classification and triage of structural heart disease using electrocardiography and echocardiography metrics LLM Sparsity Prior for Robust Feature Selection Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Entropy Equivalence Testing Coupled Training with Privileged Information and Unlabeled Data Asymmetric Scaling Laws from Sparse Features Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks Learning Kernel-Based MDPs from Episodic Preferential Feedback Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Causal Additive Models with Unobserved Causal Paths and Backdoor Paths Are Targeted Data Poisoning Attacks as Effective as We Think? Near-Optimal Private Linear Regression via Iterative Hessian Mixing Certified Per-Instance Unlearning Using Individual Sensitivity Bounds Vecchia-Inducing-Points Full-Scale Approximations for Gaussian Processes Decomposition-Based Modular Conformal Prediction for Two-Stage Modeling Online Partitioned Local Depth for semi-supervised applications Amortized Simulation-Based Inference in Generalized Bayes via Neural Posterior Estimation Online monotone density estimation and log-optimal calibration Linear Regression with Unknown Truncation Beyond Gaussian Features Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes Sample correlation adjustments for robust Multi-fidelity Monte Carlo under limited pilot sampling Mixture-of-Finite-Mixtures Wishart Model for Clustering Covariance Matrices with an Application to Brain Functional Connectivity A Direct Variance Estimation (DiVE) for Meta-Analysis of Median Differences Regulatory Considerations for Using Artificial Intelligence Models to Reduce Sample Sizes in Registrational Studies Generalized Rank Regression Generalized Stochastic Approximation of the Log-Likelihood Ratio for Robust Sequential Change-Point Detection Concomitant DAG Learning: On the Roles of Noise Adaptivity, Sparsity, and Non-negativity The frame problem in quantitative practice: ontological uncertainty and epistemic humility in an age of automated inference Directional subset simulation method for reliability analysis A note on closed-form solutions for estimating sample size when externally validating a binary prediction model based on $C$-statistic precision Joint Estimation of Marginal and Heterogeneous Treatment Effects Trajectory-Oriented Optimization Via Adaptive Thompson Sampling And Grid Refinement: A Tutorial With The ADAPTIVE\_TS Package Global Sensitivity Analysis: a novel generation of mighty estimators based on rank statistics Joint Bayesian models for validating spatial health-event databases against a gold standard: separating global and local discrepancies Anticipating Continued Global Fertility Decline via Neural Forecasting Detecting and Correcting Sample-by-Sample Scale Distortion in RNA Sequencing Data StanBKT: Rethinking Parameter Estimation in Bayesian Knowledge Tracing Mode-Shape Expansion Using Physics-Constrained Gaussian Process Regression Convex Hybrid Modeling: An Operator-Based Approach Fundamental Bounds and Efficient Estimation for Dead-Time-Constrained Event Detection, with Application to Single-Photon Lidar Diffusion Fluid Antenna Systems for Resilient ISAC Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale: a self-calibrated randomized solution Joint Object Tracking and Intent Recognition Bayesian High-dimensional Grouped-regression using Sparse Projection-posterior The feasibility of multi-graph alignment: a Bayesian approach Measures of association for approximating copulas Robust copula estimation for one-shot devices with correlated failure modes Causal inference via implied interventions Latent space projections and atlases: A cautionary tale in deep neuroimaging using autoencoders Refined thresholds for inconsistency: The effect of the graph associated with incomplete pairwise comparisons

How Eviction Court Governs: A Statistical Analysis of Bargaining, Templates, and Debt in Philadelphia

Marios Papam · 2026-05-26 · via stat updates on arXiv.org

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。原文来自 — 版权归原作者所有。