:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gultekin, M. Oguzhan, Demir, Samet, Dogan, Zafer
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2509.15127
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Implicitly Normalized Online PCA: A Regularized Algorithm with Exact High-Dimensional Dynamics
by: Demir, Samet, et al.
Published: (2025)

Learnability and Competition in High-Dimensional Multi-Component ICA
by: Genc, Eser Ilke, et al.
Published: (2026)

Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions
by: Demir, Samet, et al.
Published: (2025)

How Data Mixing Shapes In-Context Learning: Asymptotic Equivalence for Transformers with MLPs
by: Demir, Samet, et al.
Published: (2025)

Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
by: Demir, Samet, et al.
Published: (2025)

Asymptotic Study of In-context Learning with Random Transformers through Equivalent Models
by: Demir, Samet, et al.
Published: (2025)

Learning Beyond the Gaussian Data: Learning Dynamics of Neural Networks on an Expressive and Cumulant-Controllable Data Model
by: Ure, Onat, et al.
Published: (2026)

Input-Label Correlation Governs a Linear-to-Nonlinear Transition in Random Features under Spiked Covariance
by: Demir, Samet, et al.
Published: (2024)

Benefits of Online Tilted Empirical Risk Minimization: A Case Study of Outlier Detection and Robust Regression
by: Yildirim, Yigit E., et al.
Published: (2025)

Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
by: Bond, Andrew, et al.
Published: (2024)

High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
by: Ildiz, M. Emrullah, et al.
Published: (2024)

Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models
by: Diakonikolas, Ilias, et al.
Published: (2024)

Stochastic Dimension-Free Zeroth-Order Estimator for High-Dimensional and High-Order PINNs
by: Liang, Zhangyong, et al.
Published: (2026)

Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning
by: Bhartari, Ananyae Kumar, et al.
Published: (2025)

LCIP: Loss-Controlled Inverse Projection of High-Dimensional Image Data
by: Wang, Yu, et al.
Published: (2026)

Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data
by: Baligodugula, Vishnu Vardhan, et al.
Published: (2025)

One-shot Robust Federated Learning of Independent Component Analysis
by: Jin, Dian, et al.
Published: (2025)

Order-Explicit Linearization of High-Dimensional $U$-Statistics
by: Ritzwoller, David M., et al.
Published: (2024)

High-Dimensional Private Linear Regression with Optimal Rates
by: Bombari, Simone, et al.
Published: (2025)

High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020)

Independent Component Discovery in Temporal Count Data
by: Chaussard, Alexandre, et al.
Published: (2026)

Independent Component Analysis by Robust Distance Correlation
by: Leyder, Sarah, et al.
Published: (2025)

Latent Chain-of-Thought Improves Structured-Data Transformers
by: Dudley, Carson, et al.
Published: (2026)

Estimating Treatment Effects with Independent Component Analysis
by: Reizinger, Patrik, et al.
Published: (2025)

Enhanced High-Dimensional Data Visualization through Adaptive Multi-Scale Manifold Embedding
by: Ni, Tianhao, et al.
Published: (2025)

How Should LLMs Consume High-Quality Data? Optimal Data Scheduling via Quality-Aware Functional Scaling Laws
by: Zhu, Zhitao, et al.
Published: (2026)

High-Dimensional False Discovery Rate Control for Dependent Variables
by: Machkour, Jasin, et al.
Published: (2024)

LLM Unlearning Should Be Form-Independent
by: Ye, Xiaotian, et al.
Published: (2025)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
by: Tran-The, Hung, et al.
Published: (2019)

Efficient Estimation of Unique Components in Independent Component Analysis by Matrix Representation
by: Matsuda, Yoshitatsu, et al.
Published: (2024)

Negotiated Representations to Prevent Overfitting in Machine Learning Applications
by: Korhan, Nuri, et al.
Published: (2023)

High-Dimensional BWDM: A Robust Nonparametric Clustering Validation Index for Large-Scale Data
by: Baragilly, Mohammed, et al.
Published: (2025)

Bayesian Inverse Games with High-Dimensional Multi-Modal Observations
by: Jain, Yash, et al.
Published: (2026)

The Rashomon Effect for Visualizing High-Dimensional Data
by: Sun, Yiyang, et al.
Published: (2026)

A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs
by: Mufti, Bilal, et al.
Published: (2024)

Accelerating Large-Scale Regularized High-Order Tensor Recovery
by: Qin, Wenjin, et al.
Published: (2025)

Orthogonal Subspace Clustering: Enhancing High-Dimensional Data Analysis through Adaptive Dimensionality Reduction and Efficient Clustering
by: Wen, Qing-Yuan, et al.
Published: (2026)

High-Dimensional Analysis of Bootstrap Ensemble Classifiers
by: Tiomoko, Malik, et al.
Published: (2025)

Nonparametric Linear Discriminant Analysis for High Dimensional Matrix-Valued Data
by: Oh, Seungyeon, et al.
Published: (2025)

Sparse Modelling for Feature Learning in High Dimensional Data
by: Neelam, Harish, et al.
Published: (2024)