Cover Image

One Rank at a Time: Cascading Error Dynamics in Sequential Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vandchali, Mahtab Alizadeh, Fangshuo, Liao, Kyrillidis, Anastasios
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SGD at the Edge of Stability: The Stochastic Sharpness Gap
by: Liao, Fangshuo, et al.
Published: (2026)

Guided by the Experts: Provable Feature Learning Dynamic of Soft-Routed Mixture-of-Experts
by: Liao, Fangshuo, et al.
Published: (2025)

Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks
by: Liao, Fangshuo, et al.
Published: (2023)

On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis
by: Liao, Fangshuo, et al.
Published: (2023)

Convergence Analysis of Two-Layer Neural Networks under Gaussian Input Masking
by: Kolomvaki, Afroditi, et al.
Published: (2026)

One Model, Two Roles: Emergent Specialization in a Shared Recurrent Transformer
by: Shen, Jucheng, et al.
Published: (2026)

Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation
by: Liao, Fangshuo, et al.
Published: (2025)

Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings
by: Farhat, Yehya, et al.
Published: (2023)

Exploiting Low-Rank Structure in Max-K-Cut Problems
by: Stevens, Ria, et al.
Published: (2026)

Unveiling Hidden Pivotal Players with GoalNet: A GNN-Based Soccer Player Evaluation System
by: Jiang, Jacky Hao, et al.
Published: (2025)

Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization
by: Zhang, Zhiwei, et al.
Published: (2025)

GHOST: Unmasking Phantom States in Mamba2 via Grouped Hidden-state Output-aware Selection & Truncation
by: Menezes, Michael, et al.
Published: (2026)

Federated Dynamical Low-Rank Training with Global Loss Convergence Guarantees
by: Schotthöfer, Steffen, et al.
Published: (2024)

AdaPaD: Adaptive Parallel Deflation for PEFT with Self-Correcting Rank Discovery
by: Su, Barbara, et al.
Published: (2026)

One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
by: Li, Zihao, et al.
Published: (2024)

When is Momentum Extragradient Optimal? A Polynomial-Based Analysis
by: Kim, Junhyung Lyle, et al.
Published: (2022)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
by: Mitra, Aritra, et al.
Published: (2023)

Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
by: Buyuktahtakin, I. Esra
Published: (2026)

Q3R: Quadratic Reweighted Rank Regularizer for Effective Low-Rank Training
by: Ghosh, Ipsita, et al.
Published: (2025)

Unbiased Gradient Low-Rank Projection
by: Pan, Rui, et al.
Published: (2025)

Tree-Preconditioned Differentiable Optimization and Axioms as Layers
by: Liao, Yuexin
Published: (2025)

Joint Problems in Learning Multiple Dynamical Systems
by: Niu, Mengjia, et al.
Published: (2023)

The Implicit Curriculum: Learning Dynamics in RL with Verifiable Rewards
by: Huang, Yu, et al.
Published: (2026)

Compressing Large Language Models using Low Rank and Low Precision Decomposition
by: Saha, Rajarshi, et al.
Published: (2024)

Deterministic Policy Gradient for Reinforcement Learning with Continuous Time and State
by: Cheng, Ziheng, et al.
Published: (2025)

Reinforcement Learning under Latent Dynamics: Toward Statistical and Algorithmic Modularity
by: Amortila, Philip, et al.
Published: (2024)

Implicit Regularization of Gradient Flow on One-Layer Softmax Attention
by: Sheen, Heejune, et al.
Published: (2024)

Sublinear Regret for a Class of Continuous-Time Linear-Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2024)

TwIST: Rigging the Lottery in Transformers with Independent Subnetwork Training
by: Menezes, Michael, et al.
Published: (2025)

Data-Driven Exploration for a Class of Continuous-Time Indefinite Linear--Quadratic Reinforcement Learning Problems
by: Huang, Yilie, et al.
Published: (2025)

Situationally-Aware Dynamics Learning
by: Murillo-Gonzalez, Alejandro, et al.
Published: (2025)

Muon Dynamics as a Spectral Wasserstein Flow
by: Peyré, Gabriel
Published: (2026)

Constrained Sliced Wasserstein Embedding
by: NaderiAlizadeh, Navid, et al.
Published: (2025)

From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making
by: Asru, Avijit Saha, et al.
Published: (2025)

Quantum EigenGame for excited state calculation
by: Quiroga, David, et al.
Published: (2025)

Kinematic Tokenization: Optimization-Based Continuous-Time Tokens for Learnable Decision Policies in Noisy Time Series
by: Kearney, Griffin
Published: (2026)

Dynamic Memory Based Adaptive Optimization
by: Szegedy, Balázs, et al.
Published: (2024)

Finite-Time Analysis of Gradient Descent for Shallow Transformers
by: Arda, Enes, et al.
Published: (2026)

Power Constrained Nonstationary Bandits with Habituation and Recovery Dynamics
by: Li, Fengxu, et al.
Published: (2025)

Almost Bayesian: The Fractal Dynamics of Stochastic Gradient Descent
by: Hennick, Max, et al.
Published: (2025)