Principal Component Analysis

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Period ending 2026-09-21

8 new papers

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

Period ending 2026-09-14

8 new papers

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

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. ELSAA: Efficient Low-Rank and Sparse Attention Approximation for Training Transformers

    Jul 22, 2026Mahdi Heidari, Mohammad Mahdi Rahimi, Jaekyun MoonEfficient Long-Context InferenceLow-Dimensional Structure

  2. Non--negative matrix factorization using the \textit{R} package \textsf{nnmf}

    Jul 22, 2026Volkan Sevinç, Nikolas Kontemeniotis, Theodoros Perdikis +1Nonnegative Matrix FactorizationMatrix Factorization

  3. A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs

    Jul 22, 2026Jiale Linghu, Hao Dong, Yangshuai WangLow-Dimensional Structure

  4. A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling

    Jul 21, 2026Eric Herrison Gyamfi, Emily L. Kang, Bledar A. Konomi +1Gaussian ProcessDimensionality Reduction

  5. GLID: Gated Local Intrinsic Dimension Repairs the Blind Spots of Face-Forgery Detectors

    Jul 21, 2026Guang Yang, Fengchen LiuFace Forgery DetectionGenerative Adversarial Network

  6. Importance Sampling and PCA for Finding Failures in Commercial Autonomous Vehicles

    Jul 20, 2026Hailey Warner, Duncan Eddy, Shreya Parjan +6Robot FailuresAutonomous Driving

  7. De-floored Principal Component Regression: When Rank Selection Alone Is Insufficient for Prediction

    Jul 18, 2026Peng ZhaoPrincipal Component AnalysisKernel Ridge Regression

  8. DINE: Distance Is Not Enough -- Learning Global Deformation Priors for Robust Soft-Tissue Point Cloud Registration

    Jul 16, 2026Sara Monji-Azad, Rohit Beer, Marvin Kinz +2Point Cloud RegistrationDeformation

  9. Multi-Scale Equilibrium under Variable Indicator Dimensionality: Faithful Reduction of Dynamic Attractors in Urban Mobility Systems

    Jul 16, 2026Ali Ghoroghi, Yacine Rezgui, Afrouz Ghaemi +2Urban EnvironmentsAttractors

  10. Spectral Concentration and Recovery in Sparse High-Dimensional Random Geometric Graphs

    Jul 15, 2026Manuel Fernandez, Yizhe ZhuExponential Random Graph ModelsLatent Cluster Geometry

  11. TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance

    Jul 15, 2026Hongye Zeng, Shreeram Athreya, Dingyuan Dai +4PrognosticsLesion Segmentation

  12. Color Pass-Through via Camera-Display Coupling

    Jul 14, 2026Ruikang Li, Molin Li, Jiarui Wu +3Image ProcessingSmartphone Photographs

  13. ACZ-GSeg: Adaptive Concentric Zone-based Two-stage Ground Segmentation for LiDAR Point Clouds

    Jul 13, 2026Ge Zhang Chunyang Wang Bin LiuLight Detection And Ranging Point CloudsVisual Grounding

  14. How to Tame Grokking: Representation Geometry as a Control Signal

    Jul 13, 2026Maksim A KazanskiiGrokkingMultilayer Perceptrons

  15. Bandit PCA with Minimax Optimal Regret

    Jul 12, 2026Moïse Blanchard, Dmitrii Ostrovskii, Aadirupa SahaPrincipal Component AnalysisRegret

  16. Mathematics of Data Science

    Jul 11, 2026Afonso S. Bandeira, Amit Singer, Thomas StrohmerDimensionality ReductionGraph Laplacians

  17. Terminal Dimension Reduction for Time Series with Applications

    Jul 10, 2026Alexander Munteanu, Matteo Russo, David Saulpic +1Dimensionality ReductionTime Series

  18. Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics

    Jul 10, 2026Hugo CuiEfficient Influence FunctionEstimators

  19. Group Invariant Spectral Embedding

    Jul 9, 2026Yeari Vigder, Paulina Hoyos, David Thong +3Graph LaplaciansSymmetry

  20. Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph

    Jul 9, 2026Duen Horng Chau, Donghao Ren, Fred Hohman +1Dimensionality ReductionHigh-Dimensional Data

  21. High-Dimensional Procrustes Matching via Tree Counts

    Jul 9, 2026Xiaochun Niu, Tselil Schramm, Jiaming XuHigh-Dimensional DataFeature Matching

  22. Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization

    Jul 8, 2026Xiangming Huang, Guannan Zhang, Lu Lu +1Generative Inverse DesignInformation-Geometric Optimization

  23. Intrinsic Green's Learning: Supervised Learning on Manifolds via Inverse PDE

    Jul 8, 2026Alexandre QuemyIntrinsic DimensionalityManifolds

  24. RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models

    Jul 7, 2026Qian Sun, Yong-Ming Tian, Jia-Wei Huang +2Time Series Foundation ModelsHigh-Dimensional Data

  25. Physics-Informed Neural Embeddings of PDE Solution Families

    Jul 7, 2026Raul Jimenez, Svitlana Mayboroda, Pavlos Protopapas +3Partial Differential Equation BenchmarksPhase Space

  26. A study of holes: Topological analysis reveals crowd dynamics regimes in a bidirectional corridor scenario

    Jul 7, 2026Sabrina Desiree Kern, Gerta KösterPersistent HomologyTopological Data Analysis

  27. Separation Capacity of Scattering Networks on Low-Dimensional Datasets

    Jul 7, 2026Konstantin Häberle, Helmut BölcskeiLow-Dimensional StructureIntrinsic Dimensionality

  28. Orthogonal Dendritic Intrinsic Networks: An Architecture for Significance-Ordered, Orthogonal Latent Spaces

    Jul 6, 2026Jeanie Schreiber, Tyrus Berry, Zeeshan AhmedPrincipal Component AnalysisMasked Autoencoders

  29. Quantum Spectral Anomaly Detection

    Jul 6, 2026Yewei Yuan, Michele Minervini, Mark M. Wilde +1N$-Qubit Stabilizer StatesPrincipal Component Analysis

  30. msPCA: An R Package for Sparse PCA with Multiple Components

    Jul 6, 2026Ryan Cory-Wright, Jean PauphiletPrincipal Component AnalysisFeature Selection

  31. Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces

    Jul 6, 2026Domiziano Doria, Matteo Becchi, Giovanni M. PavanHigh-Dimensional DataAutomatic Differentiation

  32. Dimension Reduction for Curves: Simplified and Generalized

    Jul 3, 2026Matthijs Ebbens, Jie Lu, Alexander MunteanuDimensionality ReductionCurves

  33. Transfer Learning in High-dimensional Ising Models

    Jul 3, 2026Joonho Kim, Seyoung ParkTransfer LearningTwo-Dimensional Ising Model

  34. Function-Counting Theory for Low-Dimensional Data Structures

    Jul 1, 2026Konstantin Häberle, Helmut BölcskeiLow-Dimensional StructureBinary Classification

  35. When to Truncate a Feature Ranking: A Residual-Overlap Stopping Rule for Subset Selection

    Jun 30, 2026Jesus S. Aguilar-RuizFeature SelectionFalse Discovery Rate

  36. Explaining Machine Learning and Memorization with Statistical Mechanics

    Jun 30, 2026Robin TheriaultDense Associative MemoryMachine Learning

  37. Knowledge-Driven Dimension Estimation from a Single Image -3D Asset Generation Technology for Digital Twin Construction

    Jun 29, 2026Hidenori Sakaniwa, Akihito Akai, Akihiko Hyodo3D Object DetectionMonocular Videos

  38. Simplifying Flow Matching Transformations with Low-Rank Mixture Models

    Jun 29, 2026Liam A. Kruse, Houjun Liu, Alexandros E. Tzikas +2Normalizing FlowsConditional Flow Matching

  39. Improved Multi-Dimensional Forecasting for Swap Regret

    Jun 28, 2026Joey Rivkin, Ramiro N. Deo-Campo Vuong, Robert Kleinberg +3RegretDownstream Reasoning

  40. Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification

    Jun 28, 2026Zirui Deng, Jingbo Sun, Deyu Meng +1Neural OperatorsLeast Squares

  41. Perspectives on Latent Factor Indeterminacy and its Implications for Data Representation

    Jun 27, 2026Carel F. W. PeetersExploratory Factor AnalysisIntrinsic Dimensionality

  42. Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces

    Jun 26, 2026Joyanta Jyoti Mondal, Ibne Farabi Shihab, Anuj SharmaLinear Contextual BanditsMulti-Armed Bandits

  43. Effective Covariance Dynamics in Solvable High-Dimensional GANs

    Jun 25, 2026Andrew Bond, Zafer DoğanCovariance EstimationGenerative Adversarial Network

  44. The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples

    Jun 24, 2026Nasrin Malekzadeh Goradel, Niccolo Pancino, Yaser Gholizade Atani +3Adversarial ExamplesIntrinsic Dimensionality

  45. Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices

    Jun 22, 2026Changxiao Cai, Yuchen Jiao, Gen LiDiffusion SamplingLow-Dimensional Structure

  46. On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA

    Jun 20, 2026Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar +1Differential PrivacyPrincipal Component Analysis

  47. Stitching and dimensionality effects on large artificially generated volume datasets

    Jun 18, 2026Lucas von Chamier, Jan Philipp Albrecht, Dagmar Kainmüller3D Latent Diffusion ModelGenerative Models

  48. Score Approximation for Diffusion Models on Arbitrary Low-Dimensional Structures

    Jun 18, 2026Xinhe Mu, Zaijiu Shang, Zhaoqi Zhou +4Score-Based Diffusion ModelLow-Dimensional Structure

  49. Dimensionality Reduction of QAOA Parameter Space with Kernel PCA for Max-Cut

    Jun 17, 2026Sidharth Brahmandam, Vayd RamkumarQuantum Approximate Optimization AlgorithmVariational Quantum Circuits

  50. Dimensionality Controls When Modularity Helps in Continual Learning

    Jun 16, 2026Kathrin Korte, Christian Medeiros Adriano, Joachim Winther Pedersen +2Efficient Continual LearningContinual Learning Methods

  51. Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence

    Jun 15, 2026Peng Xu, Changbo Zhu, Young-Heon Kim +1Wasserstein DistanceProbability Measures

  52. Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model

    Jun 13, 2026Siyu Chen, Beining Wu, Miao Lu +2Optimal Sample ComplexityTwo-Layer Neural Networks

  53. The Geometry of Saturation: Effective Rank Predicts When Labels Stop Helping in Few-Shot Classification

    Jun 12, 2026Arnav GuptaBinary ClassificationSaturation

  54. The Risk Shadow of Principal Component Analysis: When 99.9999% Variance Preservation Causes Catastrophic Decision Errors

    Jun 12, 2026Hamidou TembinePrincipal Component AnalysisLong-Tailed Distribution

  55. Riemannian Metric Matching for Scalable Geometric Modeling of Distributions

    Jun 12, 2026Jacob Bamberger, Adam Gosztolai, Pierre Vandergheynst +2Riemannian ManifoldsHigh-Dimensional Data

  56. Classification of Astronomical Spectra Using PCA-Compressed Flux and Inverse-Variance Features

    Jun 11, 2026Bruno Santos Meneses Barreto, Marcio EisencraftSpectraHyperspectral Image Classification

  57. What's Old is New Again: Classical Dimensionality Reduction for Efficient Saliency-Guided Biometric Attack Detection

    Jun 11, 2026Samuel Webster, Walter ScheirerBiometricsSaliency

  58. Unstable Features, Reproducible Subspaces: Understanding Seed Dependence in Sparse Autoencoders

    Jun 10, 2026Gleb Gerasimov, Timofei Rusalev, Nikita Balagansky +3Feature LearningLow-Dimensional Structure

  59. Scalable anomaly detection via a univariate Christoffel function

    Jun 10, 2026Florian Grivet, Didier Henrion, Jean-Bernard Lasserre +1Reconstruction-Based Anomaly DetectionAnomaly Detection

  60. iMaC: Translating Actions into Motion and Contact Images for Embodied World Models

    Jun 8, 2026Zhenyu Wu, Xiuwei Xu, Yukun Zhou +8Efficient World-Action ModelGeneralizable Robotic Manipulations