Complex non-backtracking matrix for directed graphs - 惯性聚合

推荐订阅源

PCI Perspectives

博客园 - Franky

MIT News - Artificial intelligence

Privacy International News Feed

The Exploit Database - CXSecurity.com

Full Disclosure

The Register - Security

Proofpoint News Feed

Threat Research - Cisco Blogs

cs.CL updates on arXiv.org

人人都是产品经理

Last Week in AI

Hugging Face - Blog

Simon Willison's Weblog

CTFtime.org: upcoming CTF events

Know Your Adversary

CXSECURITY Database RSS Feed - CXSecurity.com

Privacy & Cybersecurity Law Blog

罗磊的独立博客

让小产品的独立变现更简单 - ezindie.com

Schneier on Security

酷壳 – CoolShell

freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More

The Blog of Author Tim Ferriss

Palo Alto Networks Blog

Google DeepMind News

Apple Machine Learning Research

Recorded Future

About on SuperTechFans

博客园 - 【当耐特】

Help Net Security

宝玉的分享

CERT Recently Published Vulnerability Notes

DataBreaches.Net

美团技术团队

Cybersecurity and Infrastructure Security Agency CISA

Vulnerabilities – Threatpost

stat.ML updates on arXiv.org

Conformalized Super Learner Pack only the essentials: Adaptive dictionary learning for kernel ridge regression Pliable rejection sampling SOC-ICNN: From Polyhedral to Conic Geometry for Learning Convex Surrogate Functions Concave Statistical Utility Maximization Bandits via Influence-Function Gradients The Sample Complexity of Multicalibration Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions Quotient-Space Diffusion Models There Will Be a Scientific Theory of Deep Learning A Kernel Nonconformity Score for Multivariate Conformal Prediction A single algorithm for both restless and rested rotting bandits Even More Guarantees for Variational Inference in the Presence of Symmetries CLT-Optimal Parameter Error Bounds for Linear System Identification Calibeating Prediction-Powered Inference Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction Learning to Emulate Chaos: Adversarial Optimal Transport Regularization Differentially Private Model Merging Early Detection of Latent Microstructure Regimes in Limit Order Books Too Sharp, Too Sure: When Calibration Follows Curvature On Bayesian Softmax-Gated Mixture-of-Experts Models Efficient Symbolic Computations for Identifying Causal Effects Decentralized Machine Learning with Centralized Performance Guarantees via Gibbs Algorithms The Origin of Edge of Stability Calibrating conditional risk Cold-Start Forecasting of New Product Life-Cycles via Conditional Diffusion Models Properties and limitations of geometric tempering for gradient flow dynamics Online Survival Analysis: A Bandit Approach under Cox PH Model Rethinking Intrinsic Dimension Estimation in Neural Representations Geometric Layer-wise Approximation Rates for Deep Networks Cover meets Robbins while Betting on Bounded Data: $\ln n$ Regret and Almost Sure $\ln\ln n$ Regret SMART: A Spectral Transfer Approach to Multi-Task Learning On the Stability and Generalization of First-order Bilevel Minimax Optimization Meta Additive Model: Interpretable Sparse Learning With Auto Weighting Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints Achieving the Kesten-Stigum bound in the non-uniform hypergraph stochastic block model Generalization at the Edge of Stability Phase Transitions in the Fluctuations of Functionals of Random Neural Networks Ultrametric OGP - parametric RDT \emph{symmetric} binary perceptron connection Budgeted Online Influence Maximization Separating Geometry from Probability in the Analysis of Generalization Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics Analytical Extraction of Conditional Sobol' Indices via Basis Decomposition of Polynomial Chaos Expansions Fast estimation of Gaussian mixture components via centering and singular value thresholding S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control Beyond Bellman: High-Order Generator Regression for Continuous-Time Policy Evaluation ParamBoost: Gradient Boosted Piecewise Cubic Polynomials Sparse Network Inference under Imperfect Detection and its Application to Ecological Networks Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models Discrete Tilt Matching Curiosity-Critic: Cumulative Prediction Error Improvement as a Tractable Intrinsic Reward for World Model Training Adaptive multi-fidelity optimization with fast learning rates Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback Stylistic-STORM (ST-STORM) : Perceiving the Semantic Nature of Appearance Collective Kernel EFT for Pre-activation ResNets PRIM-cipal components analysis One-Shot Generative Flows: Existence and Obstructions Structural interpretability in SVMs with truncated orthogonal polynomial kernels Amortized Optimal Transport from Sliced Potentials MinShap: A Modified Shapley Value Approach for Feature Selection Unsupervised feature selection using Bayesian Tucker decomposition Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits Best of both worlds: Stochastic & adversarial best-arm identification Scalable Model-Based Clustering with Sequential Monte Carlo Expert-Guided Class-Conditional Goodness-of-Fit Scores for Interpretable Classification with Informative Missingness: An Application to Seismic Monitoring Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks Gating Enables Curvature: A Geometric Expressivity Gap in Attention Zeroth-Order Optimization at the Edge of Stability Differentially Private Conformal Prediction CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization Generative Augmented Inference Improving Machine Learning Performance with Synthetic Augmentation PAC-MCTS: Bias-Aware Pruning for Robust LLM-Guided Search and Planning Path-Sampled Integrated Gradients Heat and Matérn Kernels on Matchings Doubly Outlier-Robust Online Infinite Hidden Markov Model Momentum Further Constrains Sharpness at the Edge of Stochastic Stability Multistage Conditional Compositional Optimization BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization Sandpile Economics: Theory, Identification, and Evidence Online learning with noisy side observations Spectral Thompson sampling Covariance-adapting algorithm for semi-bandits with application to sparse rewards Ordinary Least Squares is a Special Case of Transformer Metric-Aware Principal Component Analysis (MAPCA):A Unified Framework for Scale-Invariant Representation Learning Robust Low-Rank Tensor Completion based on M-product with Weighted Correlated Total Variation and Sparse Regularization Joint Representation Learning and Clustering via Gradient-Based Manifold Optimization Universality of Gaussian-Mixture Reverse Kernels in Conditional Diffusion Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression A short proof of near-linear convergence of adaptive gradient descent under fourth-order growth and convexity Some Theoretical Limitations of t-SNE Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing Rare Event Analysis via Stochastic Optimal Control Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version

Complex non-backtracking matrix for directed graphs

Keishi Sando, Hideitsu Hino · 2025-07-16 · via stat.ML 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。