arXiv Machine Learning
Jul 7
Hierarchical Scaffolding Enables Human-Like Cognitive Selectivity under Data Scarcity
arXiv:2607. 04709v1 Announce Type: new Abstract: Modern machine learning systems demand extensive datasets for visual recognition.
Unsupervised Cognition
arXiv:2409. 18624v4 Announce Type: replace Abstract: Unsupervised learning methods have a soft inspiration in cognition models.
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arXiv Machine Learning
Jul 17
Cross-Cluster Weighted Forests
arXiv:2105. 07610v5 Announce Type: replace-cross Abstract: Building trustworthy machine learning algorithms for biological applications requires adapting to data heterogeneity from different sources, batches, distributions, or studies.
arXiv AI
Jun 4
ClustRecNet: A Novel End-to-End Deep Learning Framework for Clustering Algorithm Recommendation
arXiv:2509. 25289v4 Announce Type: replace-cross Abstract: Identifying an effective clustering algorithm for a given dataset remains a fundamental unsupervised learning issue.
arXiv Machine Learning
Aug 4
Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data
arXiv:2608. 00346v1 Announce Type: new Abstract: Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates classification accuracy.
arXiv AI
Jun 9
A Geometric Unification of Concept Learning with Concept Cones
arXiv:2512. 07355v2 Announce Type: replace Abstract: Two traditions of interpretability have evolved side by side but seldom spoken to each other: Concept Bottleneck Models (CBMs), which prescribe what a concept should be, and Sparse Autoencoders (SAEs), which discover what concepts emerge.
arXiv AI
Jul 1
Creating Intelligence: A Computational Foundation for AGI
arXiv:2606. 31819v1 Announce Type: new Abstract: This work introduces a new computational theory of mind grounded in set theory and hyperdimensional computing.
arXiv AI
Jul 7
HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy
arXiv:2607. 04353v1 Announce Type: cross Abstract: Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups.
arXiv Machine Learning
Jun 8
Explaining Unsupervised Disease Staging in Huntington's Disease: Insights into Model Representations and Clusters
arXiv:2606. 07135v1 Announce Type: new Abstract: Huntington's disease (HD) is a progressive neurodegenerative disorder that affects motor, cognitive, and behavioral functions, where accurate characterization of disease progression remains essential to improve patient outcome and quality of life.
arXiv AI
Jul 2
Identifying Latent Concepts and Structures for Generalized Category Discovery
arXiv:2607. 00620v1 Announce Type: cross Abstract: Generalized Category Discovery (GCD) aims to recognize known classes while autonomously discovering novel ones in open-world settings.
arXiv AI
Jun 16
CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
arXiv:2506. 22427v2 Announce Type: replace-cross Abstract: We propose CLoVE (Clustering of Loss Vector Embeddings), a novel algorithm for Clustered Federated Learning (CFL).
arXiv Machine Learning
Jun 8
Enhancing Conformal Prediction via Class Similarity
arXiv:2511. 19359v2 Announce Type: replace Abstract: Conformal Prediction (CP) has emerged as a powerful statistical framework for high-stakes classification applications.
arXiv Machine Learning
Jun 25
Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning
arXiv:2606. 25770v1 Announce Type: new Abstract: Data scarcity is a major bottleneck in medical Multiple Instance Learning (MIL), especially for rare diseases or expensive modalities.