arXiv AI
Jul 29
Multiclass Classification without Labels via Posterior Simplex Geometry
arXiv:2607. 24943v1 Announce Type: cross Abstract: In many classification problems, reliable instance-level labels are unavailable.
Geometry-Aware Bayesian Quantification via Compositional Data Analysis
arXiv:2607. 04977v1 Announce Type: new Abstract: Accurately estimating the unknown target label distribution is the critical first step for adapting to label shift.
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arXiv Machine Learning
Jul 22
Information Theoretic Bayesian Optimization over the Probability Simplex
arXiv:2603. 09793v2 Announce Type: replace Abstract: Bayesian optimization is a data-efficient technique that has been shown to be extremely powerful to optimize expensive, black-box, and possibly noisy objective functions.
arXiv AI
Jul 7
CuBAS: Information Geometric Curvature-Based Adaptive Sampling for Supervised Classification
arXiv:2607. 03145v1 Announce Type: cross Abstract: The informativeness of a training set is as consequential as its size, yet most sampling strategies remain agnostic to the intrinsic geometry of the data distribution.
arXiv Machine Learning
Jul 9
MARGIN: Margin-Aware Regularized Geometry for Imbalanced Vulnerability Detection
arXiv:2605. 10240v3 Announce Type: replace-cross Abstract: Software vulnerability detection is critical for ensuring software security and reliability.
arXiv AI
Jun 16
Canonical Variates in Wasserstein Metric Space
arXiv:2405. 15768v2 Announce Type: replace-cross Abstract: In this paper, we address the classification of instances represented by distributions on a vector space rather than single points.
arXiv Machine Learning
Jul 16
The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model
arXiv:2607. 13660v1 Announce Type: new Abstract: Contrastive Language-Image Pretraining (CLIP) representations form a semantic embedding space governed by cosine similarity, reflecting an intrinsic hyperspherical geometry.
arXiv AI
1d ago
DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations
arXiv:2405. 07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbitrarily imbalanced.
arXiv AI
Jul 24
CLOE: Christoffel Loss Autoencoder for Anomaly Detection
arXiv:2607. 20530v1 Announce Type: cross Abstract: Semi-supervised anomaly detection plays a key role in diverse fields such as process monitoring, healthcare, and finance.
arXiv Machine Learning
Jun 9
Similarity-Distance-Magnitude Activations
arXiv:2509. 12760v5 Announce Type: replace Abstract: We introduce the Similarity-Distance-Magnitude (SDM) activation function, a more robust and interpretable formulation of the standard softmax activation function, adding Similarity (i.
arXiv AI
Jun 11
CoVar: Confidence-Variance-Guided Pseudo-Label Selection for Semi-Supervised Learning
arXiv:2601. 11670v3 Announce Type: replace-cross Abstract: Pseudo-label selection in semi-supervised learning is commonly driven by maximum-confidence thresholds, yet confidence alone can be unreliable under model overconfidence and class imbalance.
arXiv AI
Jun 15
Rethinking Global Average Pooling: Your Classifier Is Secretly a Multi-Instance Learner
arXiv:2606. 14555v1 Announce Type: cross Abstract: Modern image classifiers widely adopt global average pooling (GAP) followed by a linear classification head.
arXiv Machine Learning
Jun 30
Conformal Prediction with Macro-Coverage Guarantees
arXiv:2606. 28598v1 Announce Type: cross Abstract: Prediction sets should have high coverage to be useful, but some coverage notions are more practically relevant than others.