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Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Photonic reservoir computing with complex networks4h◆XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control4h◆Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents4h◆Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks4h◆The One-Word Census: Answer-Choice Conformity Across 44 Language Models4h◆Creative Integration: A Decidable Criterion of Creativity4h◆BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi4h◆Joint Optimization for Greedy Longest-match Tokenization4h◆Kimi K3: Open Frontier Intelligence4h◆The Few-shot Dilemma: Over-prompting Large Language Models4h◆Speculative Pipeline Decoding: Higher-Accuracy Drafting with Hidden Latency via Pipeline Parallelism4h◆Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram4h◆StageGuard: Physiologically Constrained Sleep Staging4h◆Soft-Constrained Optimization of Latent Space in Variational Autoencoders4h◆Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment4h◆Analyzing the Importance of Blank for CTC-Based Knowledge Distillation4h◆Predicting Channel Closures in the Lightning Network with Machine Learning4h◆Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structures4h◆MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback4h◆Cursor makes its biggest India push yet ahead of SpaceX acquisition with localized pricing4h◆Photonic reservoir computing with complex networks4h◆XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control4h◆Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents4h◆Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks4h◆The One-Word Census: Answer-Choice Conformity Across 44 Language Models4h◆Creative Integration: A Decidable Criterion of Creativity4h◆BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi4h◆Joint Optimization for Greedy Longest-match Tokenization4h◆Kimi K3: Open Frontier Intelligence4h◆The Few-shot Dilemma: Over-prompting Large Language Models4h◆Speculative Pipeline Decoding: Higher-Accuracy Drafting with Hidden Latency via Pipeline Parallelism4h◆Bayesian Complete-Pooling in Cross-Subject Classification for Motor Imagery Electroencephalogram4h◆StageGuard: Physiologically Constrained Sleep Staging4h◆Soft-Constrained Optimization of Latent Space in Variational Autoencoders4h◆Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment4h◆Analyzing the Importance of Blank for CTC-Based Knowledge Distillation4h◆Predicting Channel Closures in the Lightning Network with Machine Learning4h◆Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structures4h◆MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback4h◆
Tag

#clustering

9 articles tagged #clustering

arxiv4d ago

External Clustering Validation by the Homogeneity-Parsimony Trade-off

arXiv:2607.20799v1 Announce Type: new Abstract: Scalar metrics are often used to evaluate clusterings against known classes, but they can obscure a fundamental trade-off: clusterings should be informative about class labels while avoiding unnecessary fragmentation. Here we describe normalized scores

#clustering#evaluation#information-theoryRead on arxiv →
arxiv6d agobullish

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A Reinforcement-Learning-Augmented Liquid-Fueled Reactor Network Model for Predicting Lean Blowout in Gas Turbine Combustors

arXiv:2607.19281v1 Announce Type: new Abstract: This study introduces a reinforcement learning (RL) framework for generating optimal liquid-fueled reactors to improve lean blowout (LBO) predictions in gas turbine combustors. Existing approaches for determining cluster boundaries rely on manual heuri

K-AC2 models#reinforcement-learning#clustering#gas-turbineRead on arxiv →
arxivJul 10

Persistent Multiscale Density-based Clustering

arXiv:2512.16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumptions about the data. Density-based clustering algorithms are particularly well-suited for EDA becaus

DBHDPL4 models · +1#clustering#density-based#machine-learningRead on arxiv →
arxivJun 18

SCAN: Enhance Time Series Anomaly Detection via Multi-Scale Neighborhood-Centered Clustering

arXiv:2606.19255v1 Announce Type: new Abstract: Time series anomaly detection plays a crucial role in a wide range of real-world applications. Reconstruction-based methods have become the mainstream paradigm, but they suffer from over-generalization and under-generalization problems, which are chall

#anomaly-detection#machine-learning#clusteringRead on arxiv →
arxivJun 15bullish

Expert-Driven Survival Machines: Improving Stratification and Interpretability in Multiple Clinical Cohorts

arXiv:2606.14608v1 Announce Type: cross Abstract: Survival prediction plays a central role for healthcare providers and clinical researchers. Accurate risk stratification enables early intervention and improved patient management. Most existing deep survival models learn one common feature represent

AD1 model#survival-prediction#deep-learning#clusteringRead on arxiv →
arxivMay 15bullish

K-Models: a Flexible and Interpretable Method for Ordinal Clustering with Application to Antigen-Antibody Interaction Profiles

arXiv:2605.14828v1 Announce Type: cross Abstract: Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaningful insights when the data-generating process follows a specific underlying structure and an ordinal

K-1 model#clustering#interpretability#machine-learningRead on arxiv →
arxivMay 11bullish

Simple KNN-Based Outlier Detection Achieves Robust Clustering

arXiv:2605.07130v1 Announce Type: new Abstract: Being robust to the presence of outliers is crucial for applying clustering algorithms in practice. In the $\textit{robust $k$-Means}$ problem (i.e., $k$-Means with outliers), the goal is to remove $z$ outliers and minimize the $k$-Means cost on the re

#clustering#outlier-detection#machine-learningRead on arxiv →
arxivApr 27bullish

Robust Fuzzy local k-plane clustering with mixture distance of hinge loss and L1 norm

arXiv:2604.22405v1 Announce Type: new Abstract: K-plane clustering (KPC), hyperplane clustering, and mixture regression all essentially fall within the same class of problems. This problem can be conceptualized as clustering in relatively high-dimensional K subspaces or K linear manifolds. Tradition

RF1 model#clustering#machine-learning#robustnessRead on arxiv →
arxivApr 3

Causal K-Means Clustering

arXiv:2405.03083v5 Announce Type: replace-cross Abstract: Causal effects are often characterized with population summaries. These might provide an incomplete picture when there are heterogeneous treatment effects across subgroups. Since the subgroup structure is typically unknown, it is more challen

#clustering#causal-inference#machine-learningRead on arxiv →