Imagen de Portada

Grokking in Linear Models for Logistic Regression

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Das, Nataraj, Vedantam, Atreya, Lakshminarayanan, Chandrashekar
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Learning to Price: Interpretable Attribute-Level Models for Dynamic Markets
por: Sethuraman, Srividhya, et al.
Publicado: (2026)

Half-Space Feature Learning in Neural Networks
por: Yadav, Mahesh Lorik, et al.
Publicado: (2024)

ProdRev: A DNN framework for empowering customers using generative pre-trained transformers
por: Gupta, Aakash, et al.
Publicado: (2025)

Topological Signatures of Grokking
por: Tang, Yifan, et al.
Publicado: (2026)

RMLR: Extending Multinomial Logistic Regression into General Geometries
por: Chen, Ziheng, et al.
Publicado: (2024)

Grokking Explained: A Statistical Phenomenon
por: Carvalho, Breno W., et al.
Publicado: (2025)

Controlling Grokking with Nonlinearity and Data Symmetry
por: Salah, Ahmed, et al.
Publicado: (2024)

Grokfast: Accelerated Grokking by Amplifying Slow Gradients
por: Lee, Jaerin, et al.
Publicado: (2024)

Understanding Grokking Through A Robustness Viewpoint
por: Tan, Zhiquan, et al.
Publicado: (2023)

Progress Measures for Grokking on Real-world Tasks
por: Golechha, Satvik
Publicado: (2024)

Low-Dimensional and Transversely Curved Optimization Dynamics in Grokking
por: Xu, Yongzhong
Publicado: (2026)

Tracing the Path to Grokking: Embeddings, Dropout, and Network Activation
por: Salah, Ahmed, et al.
Publicado: (2025)

The Geometry of Grokking: Norm Minimization on the Zero-Loss Manifold
por: Musat, Tiberiu
Publicado: (2025)

NeuralGrok: Accelerate Grokking by Neural Gradient Transformation
por: Zhou, Xinyu, et al.
Publicado: (2025)

Grokking Finite-Dimensional Algebra
por: Notsawo, Pascal Jr Tikeng, et al.
Publicado: (2026)

Grokking Group Multiplication with Cosets
por: Stander, Dashiell, et al.
Publicado: (2023)

Muon Optimizer Accelerates Grokking
por: Tveit, Amund, et al.
Publicado: (2025)

Early-Warning Signals of Grokking via Loss-Landscape Geometry
por: Xu, Yongzhong
Publicado: (2026)

Grokking as Structural Inference: Transformers Need Bayesian Lottery Tickets
por: Hidajat, Kai, et al.
Publicado: (2026)

Grokking Beyond the Euclidean Norm of Model Parameters
por: Notsawo, Pascal Jr Tikeng, et al.
Publicado: (2025)

Grokking and Generalization Collapse: Insights from \texttt{HTSR} theory
por: Prakash, Hari K., et al.
Publicado: (2025)

Acceleration of Grokking in Learning Arithmetic Operations via Kolmogorov-Arnold Representation
por: Park, Yeachan, et al.
Publicado: (2024)

Provable Scaling Laws of Feature Emergence from Learning Dynamics of Grokking
por: Tian, Yuandong
Publicado: (2025)

Critical Data Size of Language Models from a Grokking Perspective
por: Zhu, Xuekai, et al.
Publicado: (2024)

Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent
por: Chou, Chi-Ning, et al.
Publicado: (2026)

Feature Repulsion and Spectral Lock-in: An Empirical Study of Two-Layer Network Grokking
por: Xu, Yongzhong
Publicado: (2026)

Grokking as a Falsifiable Finite-Size Transition
por: Bi, Yuda, et al.
Publicado: (2026)

Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
por: Lyu, Kaifeng, et al.
Publicado: (2023)

Towards Empirical Interpretation of Internal Circuits and Properties in Grokked Transformers on Modular Polynomials
por: Furuta, Hiroki, et al.
Publicado: (2024)

Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes
por: Mandal, Lakshmi, et al.
Publicado: (2023)

Sensitivity-Positional Co-Localization in GQA Transformers
por: Rao, Manoj Chandrashekar
Publicado: (2026)

Transitive RL: Value Learning via Divide and Conquer
por: Park, Seohong, et al.
Publicado: (2025)

The Norm-Separation Delay Law of Grokking: A First-Principles Theory of Delayed Generalization
por: Khanh, Truong Xuan, et al.
Publicado: (2026)

The Geometry of Multi-Task Grokking: Transverse Instability, Superposition, and Weight Decay Phase Structure
por: Xu, Yongzhong
Publicado: (2026)

Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold
por: Acharya, Pratyush, et al.
Publicado: (2026)

Grokking at the Edge of Numerical Stability
por: Prieto, Lucas, et al.
Publicado: (2025)

Auditable Unit-Aware Thresholds in Symbolic Regression via Logistic-Gated Operators
por: Deng, Ou, et al.
Publicado: (2025)

First-Passage Prediction of Grokking Delay: ACalibrated Law under AdamW with Causal Validation
por: Khanh, Truong Xuan, et al.
Publicado: (2026)

Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond
por: Jeffares, Alan, et al.
Publicado: (2024)

In-Context Learning in Linear vs. Quadratic Attention Models: An Empirical Study on Regression Tasks
por: Goel, Ayush, et al.
Publicado: (2026)