On Statistical Estimation of Edge-Reinforced Random Walks - 惯性聚合

推荐订阅源

博客园 - Franky

Proofpoint News Feed

Palo Alto Networks Blog

Hackread – Cybersecurity News, Data Breaches, AI and More

The Register - Security

Security @ Cisco Blogs

Simon Willison's Weblog

Recorded Future

大猫的无限游戏

Microsoft Research Blog - Microsoft Research

Tailwind CSS Blog

cs.CV updates on arXiv.org

Cyber Security Advisories - MS-ISAC

Application and Cybersecurity Blog

True Tiger Recordings

有赞技术团队

Cisco Talos Blog

Hacker News - Newest: "LLM"

The GitHub Blog

cs.AI updates on arXiv.org

博客园 - 叶小钗

Hugging Face - Blog

Hacker News: Ask HN

Security Archives - TechRepublic

Future of Privacy Forum

PCI Perspectives

Help Net Security

让小产品的独立变现更简单 - ezindie.com

The Blog of Author Tim Ferriss

Netflix TechBlog - Medium

罗磊的独立博客

Apple Machine Learning Research

Security Latest

美团技术团队

博客园 - 三生石上(FineUI控件)

Schneier on Security

CERT Recently Published Vulnerability Notes

cs.LG updates on arXiv.org

IKNO: Infinite-order Kernel Neural Operators Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift Cross-domain benchmarks reveal when coordinated AI agents improve scientific inference from partial evidence Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift What are the Right Symmetries for Formal Theorem Proving? Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification Machine learning prediction of obstructive coronary artery disease using opportunistic coronary calcium and epicardial fat assessments from CT calcium scoring scans Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation How Many Different Outputs Can a Transformer Generate? Support-aware offline policy selection for advertising marketplaces Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation Harnesses for Inference-Time Alignment over Execution Trajectories Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning Double descent for least-squares interpolation on contaminated data: A simulation study Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines Can Transformers Learn to Verify During Backtracking Search? Same Architecture, Different Capacity: Optimizer-Induced Spectral Scaling Laws Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents Alike Parts: A Feature-Informed Approach to Local and Global Prototype Explanations An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning Provable Joint Decontamination for Benchmarking Multiple Large Language Models Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling AgForce Enables Antigen-conditioned Generative Antibody Design ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking Skill Weaving: Efficient LLM Improvement via Modular Skillpacks One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs Bandit Convex Optimization with Gradient Prediction Adaptivity Predicting Performance of Symbolic and Prompt Programs with Examples DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs Toward Understanding Adversarial Distillation: Why Robust Teachers Fail Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents Symbolic Density Estimation for Discrete Distributions LCGuard: Latent Communication Guard for Safe KV Sharing in Multi-Agent Systems TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos Thermodynamic Irreversibility of Training Algorithms Tabular foundation models for robust calibration of near-infrared chemical sensing data Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising Three Costs of Amortizing Gaussian Process Inference with Neural Processes How Sparsity Allocation Shapes Label-Free Post-Pruning Recoverability Calibration, Uncertainty Communication, and Deployment Readiness in CKD Risk Prediction: A Framework Evaluation Study Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Noise Schedule Design for Diffusion Models: An Optimal Control Perspective From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs When to Switch, Not Just What: Transition Quality Prediction in Clash Royale Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization One-Way Policy Optimization for Self-Evolving LLMs Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective Evaluation of Pipelines for Data Integration into Knowledge Graphs A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes Detecting Atypical Clients in Federated Learning via Representation-Level Divergence Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy CausalGuard: Conformal Inference under Graph Uncertainty Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning Manifold-Guided Attention Steering Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs Dynamic Mixture of Latent Memories for Self-Evolving Agents Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation $\textit{BlockFormer}$ : Transformer-based inference from interaction maps When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation

On Statistical Estimation of Edge-Reinforced Random Walks

Qinghua (Dev · 2026-05-23 · via cs.LG 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。