Principal Component Analysis

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Period ending 2026-09-21

8 new papers

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Period ending 2026-09-14

8 new papers

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Period ending 2026-09-07

4 new papers

A weekly snapshot of new work published in Principal Component Analysis.

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279 papers

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  1. Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data

    May 18, 2026Ariane Delrocq, Wu S. Zihan, Guillaume Bellec +1Singular Learning TheorySynaptic Plasticity

  2. Principal Component Analysis for Lunar Crater Detection

    May 16, 2026Travis Driver, John A. ChristianLunar SurfacePhase-Folded Light Curves

  3. Topo-GS: Continuous Volumetric Embedding of High-Dimensional Data via Topological Gaussian Splatting

    May 16, 2026João Paulo Gois, Luis Gustavo NonatoVolumeTopological Data Analysis

  4. Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification

    May 15, 2026Mónika Farsang, Ramin Hasani, Daniela Rus +1Time-Series ClassificationState Space Models

  5. Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds

    May 15, 2026Guoji Fu, Taiji Suzuki, Wee Sun Lee +1Statistical ManifoldWasserstein Distance

  6. Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models

    May 14, 2026Libin Zhu, Damek Davis, Dmitriy Drusvyatskiy +1Kernel Ridge RegressionKernel Method

  7. Distance-Matrix Wasserstein Statistics for Scalable Gromov--Wasserstein Learning

    May 14, 2026Ao Xu, Tieru WuGromov--WassersteinWasserstein Distance

  8. nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI

    May 14, 2026Shantanu Sarkar, Jose L. Contreras-VidalElectroencephalography Spatial Super-ResolutionBrain-Computer Interface

  9. Learning with Shallow Neural Networks on Cluster-Structured Features

    May 14, 2026Elisabetta Cornacchia, Laurent MassouliéLow-Dimensional StructureTwo-Layer Neural Networks

  10. RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression

    May 14, 2026Zhengjia Zhong, Shuyan Ke, Zaizhou Lin +3Calibration-Free Low-Bit Vector QuantizationCodebooks

  11. Nearest-Neighbor Radii under Dependent Sampling

    May 14, 2026Yuanyuan Gao, Yilong Hou, Zhexiao LinApproximate Nearest-Neighbor SearchIntrinsic Dimensionality

  12. Semantic Feature Segmentation for Interpretable Predictive Maintenance in Complex Systems

    May 14, 2026Emilio Mastriani, Alessandro Costa, Federico Incardona +2Predictive MaintenanceModel Interpretability

  13. Stochastic global optimization of continuous functions via random walks on Grassmannians

    May 13, 2026Kartik Gupta, Stephen D. Miller, Pradeep Ravikumar +1Stochastic OptimizationLow-Dimensional Structure

  14. Beyond Explained Variance: A Cautionary Tale of PCA

    May 13, 2026Gionni MarchettiPrincipal Component AnalysisPersistent Homology

  15. Seconds-Aligned PCA-DAC Latent Diffusion for Symbolic-to-Audio Drum Rendering

    May 13, 2026Konstantinos Soiledis, Maximos Kaliakatsos Papakostas, Dimos Makris +1Identity-Conditioned Latent Diffusion ModelsWaveforms

  16. A Resampling-Based Framework for Network Structure Learning in High-Dimensional Data

    May 12, 2026Ziwei Huang, Zeyuan Song, Paola Sebastiani +1Complex NetworksHigh-Dimensional Data

  17. NOFE - Neural Operator Function Embedding

    May 12, 2026Lars Uebbing, Harald L. Joakimsen, Siyan Chen +6Dimensionality ReductionFourier Neural Operators

  18. A nonlinear extension of parametric model embedding for dimensionality reduction in parametric shape design

    May 12, 2026Andrea Serani, Giorgio Palma, Matteo DiezDimensionality ReductionSuperquadrics

  19. FastUMAP: Scalable Dimensionality Reduction via Bipartite Landmark Sampling

    May 12, 2026Hongmin LiDimensionality ReductionStatistical Manifold

  20. Novel GPU Boruta algorithms for feature selection from high-dimensional data

    May 11, 2026Xurui Li, Zhiguo Gan, Jiaming Zhang +2Feature SelectionFeature Importance

  21. Accelerating Power Method with Fast Sketching for Stronger Low-Rank Approximation

    May 10, 2026Shabarish Chenakkod, Michał DerezińskiLow-Rank FactorizationPrincipal Component Analysis

  22. Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation

    May 8, 2026Joon Ha Kim, Geon-Woo Kim, Anoop Rachakonda +1ProfilingLLM Inference Efficiency

  23. When Diffusion Model Can Ignore Dimension: An Entropy-Based Theory

    May 8, 2026Ahmad Aghapour, Erhan BayraktarDiffusion SamplingHigh-Dimensional Data

  24. How Big Should a Wireless Foundation Model Be?

    May 8, 2026Wei-Lun Cheng, Wanjiun LiaoWireless NetworksWireless Foundation Models

  25. Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples

    May 8, 2026Yicen Li, Ruiyang Hong, Anastasis Kratsios +2Image ClusteringHierarchical

  26. Feature Dimensionality Outweighs Model Complexity in Breast Cancer Subtype Classification Using TCGA-BRCA Gene Expression Data

    May 7, 2026Meena Al HasaniNon-Small Cell Lung CancerHigh-Dimensional Data

  27. CPCANet: Deep Unfolding Common Principal Component Analysis for Domain Generalization

    May 6, 2026Yu-Hsi Chen, Abd-Krim SeghouaneMultimodal Domain GeneralizationDomain Generalization

  28. Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models

    May 6, 2026Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4HallucinationsIntrinsic Dimensionality

  29. A Simulated Federated Analysis of MS-Induced Brain Lesions

    May 6, 2026Evelyn Trautmann, Joël Federer-Gsponer, Markus C. Elze +1Federated LearningMultiple Sclerosis

  30. Capabilities of Auto-encoders and Principal Component Analysis of the Reduction of Microstructural Images; Application on the Acceleration of Phase-Field Simulations

    May 5, 2026Seifallah Fetni, Thinh Quy Duc Pham, Truong Vinh Hoang +4Masked AutoencodersPorous Media

  31. Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions

    May 5, 2026Sarthak Choudhary, Atharv Singh Patlan, Nils Palumbo +3Backdoor AttacksDetection Framework

  32. Most ReLU Networks Admit Identifiable Parameters

    May 5, 2026Moritz Grillo, Guido MontúfarRectified Linear Unit NetworksIntrinsic Dimensionality

  33. DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data

    May 5, 2026Al Zadid Sultan Bin Habib, Gianfranco Doretto, Donald A. AdjerohTabular LearningHigh-Dimensional Data

  34. Provable Accuracy Collapse in Embedding-Based Representations under Dimensionality Mismatch

    May 5, 2026Dionysis Arvanitakis, Vaggos Chatziafratis, Yiyuan LuoEmbedding DimensionIntrinsic Dimensionality

  35. Distributed Deep Variational Approach for Privacy-preserving Data Release

    May 4, 2026Zahir Alsulaimawi, Huaping LiuFederated LearningDistributional Learning

  36. Dimensionality-Aware Anomaly Detection in Learned Representations of Self-Supervised Speech Models

    May 4, 2026Sandra Arcos-Holzinger, Sarah M. Erfani, James Bailey +1Wav2VecRepresentation Learning

  37. DR-SNE: Density-Regularized Stochastic Neighbor Embedding

    May 3, 2026Maksim KazanskiiDimensionality ReductionDensity Ratio Estimation

  38. Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise

    May 3, 2026Kumar Shubham, Pavan Karjol, Kiran M K +1Noisy LabelsHigh-Dimensional Data

  39. Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation

    May 2, 2026Genki OsadaIntrinsic DimensionalityCondition Number

  40. Controlled Paraphrase Geometry in Sentence Embedding Space: Local Manifold Modeling and Latent Probing

    May 1, 2026Leonid BedratyukLatent Cluster GeometryGeometry-Aware Foundation Model

  41. A dimensional R2 regression metric

    May 1, 2026Jaesung Yoo, Stefan Lemke, Jian Zhong Guo +2Intrinsic DimensionalityKernel Ridge Regression

  42. Bridging Graph Drawing and Dimensionality Reduction with Stochastic Stress Optimization

    May 1, 2026Daniel Hangan, Stephen Kobourov, Jacob MillerDimensionality ReductionStochastic Gradient Descent

  43. Class Angular Distortion Index for Dimensionality Reduction

    May 1, 2026Kaviru Gunaratne, Stephen Kobourov, Jacob MillerDimensionality ReductionDistance

  44. When Does Structure Matter in Continual Learning? Dimensionality Controls When Modularity Shapes Representational Geometry

    Apr 30, 2026Kathrin Korte, Joachim Winter Pedersen, Eleni Nisioti +1Continual Learning MethodsPlasticity

  45. Lifting Embodied World Models for Planning and Control

    Apr 28, 2026Alex N. Wang, Trevor Darrell, Pavel Izmailov +2Efficient World-Action ModelAction Space

  46. Value-Aware Product Recommendation by Customer Segmentation using a suitable High-Dimensional Similarity Measure

    Apr 28, 2026María Florencia Acosta, Rodrigo García Arancibia, Pamela Llop +2RecommendationHigh-Dimensional Data

  47. Investigation into In-Context Learning Capabilities of Transformers

    Apr 28, 2026Rushil Chandrupatla, Leo Bangayan, Sebastian LengIn-Context LearningIn-Context

  48. Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds

    Apr 28, 2026Liuzhuozheng Li, Zhiyuan Zhan, Shuhong Liu +5Generative ModelsHigh-Dimensional Data

  49. DiRe-RAPIDS: Topology-faithful dimensionality reduction at scale

    Apr 28, 2026Alexander Kolpakov, Igor RivinDimensionality ReductionTopological Data Analysis

  50. The Optimal Sample Complexity of Multiclass and List Learning

    Apr 27, 2026Chirag PabbarajuMulticlass ClassificationOptimal Sample Complexity

  51. Diffusion-Guided Feature Selection via Nishimori Temperature: Noise-Based Spectral Embedding

    Apr 27, 2026Vasiliy S. Usatyuk, Denis A. Sapozhnikov, Sergey I. EgorovFeature SelectionFeature Learning

  52. Information bottleneck for learning the phase space of dynamics from high-dimensional experimental data

    Apr 27, 2026K. Michael Martini, Eslam Abdelaleem, Paarth Gulati +1Phase SpaceHigh-Dimensional Data

  53. Quantum Kernel Advantage over Classical Collapse in Medical Foundation Model Embeddings

    Apr 27, 2026Sebastian Cajas Ordóñez, Felipe Ocampo Osorio, Dax Enshan Koh +10Quantum KernelsMedical Image Classification

  54. Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface

    Apr 27, 2026Hiromitsu Goto, Tao Tao, Zheng-Lin ChiaKinematic ChainPrincipal Component Analysis

  55. Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework

    Apr 27, 2026You Yang, Fei WangNeural Partial Differential Equation SolversPartial Differential Equations

  56. High-dimensional Semi-supervised Classification via the Fermat Distance

    Apr 26, 2026Ruoxu Tan, Yiming ZangSemi-Supervised LearningHigh-Dimensional Data

  57. Come Together: Analyzing Popular Songs Through Statistical Embeddings

    Apr 24, 2026Matthew Esmaili Mallory, Mark Glickman, Jason BrownEmbedding DimensionSheet Music

  58. Assessing the impact of dimensionality reduction on clustering performance - a systematic study

    Apr 23, 2026Ousmane Assani Amate, Elyes Lounissi, Mohammadreza Bakhtyari +3Dimensionality ReductionImage Clustering

  59. Causal Disentanglement-Inspired Degradation Representation Learning for Full-Reference Image Quality Assessment

    Apr 23, 2026Zhen Zhang, Jielei Chu, Tian Zhang +5Image Quality AssessmentRepresentation Learning

  60. Amortized Vine Copulas for High-Dimensional Density and Information Estimation

    Apr 22, 2026Houman SafaaiGaussian CopulaMaximum Likelihood