:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Petrozziello, Alessio, Sommeregger, Christian, Lim, Ye-Sheen
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.01959
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Canonicalization Perspective on Invariant and Equivariant Learning
by: Ma, George, et al.
Published: (2024)

Sufficient Invariant Learning for Distribution Shift
by: Kim, Taero, et al.
Published: (2022)

Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
by: Chen, Siyu, et al.
Published: (2024)

Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality
by: Chen, Siyu, et al.
Published: (2024)

Learning Time-Scale Invariant Population-Level Neural Representations
by: Patel, Eshani, et al.
Published: (2025)

A Two-Scale Complexity Measure for Deep Learning Models
by: Datres, Massimiliano, et al.
Published: (2024)

Invariant Kernels: Rank Stabilization and Generalization Across Dimensions
by: Díaz, Mateo, et al.
Published: (2025)

TILDE-Q: A Transformation Invariant Loss Function for Time-Series Forecasting
by: Lee, Hyunwook, et al.
Published: (2022)

Learn to Rank: Visual Attribution by Learning Importance Ranking
by: Schinagl, David, et al.
Published: (2026)

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

Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models
by: Putterman, Theo, et al.
Published: (2024)

Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
by: Capogrosso, Luigi, et al.
Published: (2024)

An Improved Algorithm for Learning Drifting Discrete Distributions
by: Mazzetto, Alessio
Published: (2024)

Learning Counterfactually Invariant Predictors
by: Quinzan, Francesco, et al.
Published: (2022)

Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems
by: Li, Bingcong, et al.
Published: (2024)

Low Rank Multi-Dictionary Selection at Scale
by: Ma, Boya, et al.
Published: (2024)

Ranking with Confidence for Large Scale Comparison Data
by: Valdeira, Filipa, et al.
Published: (2022)

Metric-Aware Principal Component Analysis (MAPCA):A Unified Framework for Scale-Invariant Representation Learning
by: Leznik, Michael
Published: (2026)

InRank: Incremental Low-Rank Learning
by: Zhao, Jiawei, et al.
Published: (2023)

Scale-Invariant Fast Convergence in Games
by: Tsuchiya, Taira, et al.
Published: (2026)

On a Scale-Invariant Approach to Bundle Recommendations in Candy Crush Saga
by: Katsarou, Styliani, et al.
Published: (2024)

Probabilistic Lipschitzness and the Stable Rank for Comparing Explanation Models
by: Simpson, Lachlan, et al.
Published: (2024)

Continual Learning of Domain-Invariant Representations
by: Janetzky, Pascal, et al.
Published: (2026)

Universally Invariant Learning in Equivariant GNNs
by: Cen, Jiacheng, et al.
Published: (2025)

Invariant Learning with Annotation-free Environments
by: Le, Phuong Quynh, et al.
Published: (2025)

ScaLoRA: Optimally Scaled Low-Rank Adaptation for Efficient High-Rank Fine-Tuning
by: Zhang, Yilang, et al.
Published: (2025)

Quality Control of Lifetime Drift in Discrete Electrical Parameters in Semiconductor Devices via Transition Modeling
by: Sommeregger, Lukas, et al.
Published: (2025)

Cover Learning for Large-Scale Topology Representation
by: Scoccola, Luis, et al.
Published: (2025)

The Condition Number as a Scale-Invariant Proxy for Information Encoding in Neural Units
by: Ludwig, Oswaldo
Published: (2025)

NudgeRank: Digital Algorithmic Nudging for Personalized Health
by: Chiam, Jodi, et al.
Published: (2024)

Model-Free Active Exploration in Reinforcement Learning
by: Russo, Alessio, et al.
Published: (2024)

Monotonic Transformation Invariant Multi-task Learning
by: Murthy, Surya, et al.
Published: (2025)

Unsupervised Learning of Group Invariant and Equivariant Representations
by: Winter, Robin, et al.
Published: (2022)

Robust Invariant Representation Learning by Distribution Extrapolation
by: Yoshida, Kotaro, et al.
Published: (2025)

Distribution Shift Is Key to Learning Invariant Prediction
by: Zheng, Hong, et al.
Published: (2026)

Invariant Federated Learning for Edge Intelligence: Mitigating Heterogeneity and Asynchrony via Exit Strategy and Invariant Penalty
by: Hao, Ziruo, et al.
Published: (2025)

Ranking-aware Reinforcement Learning for Ordinal Ranking
by: Hao, Aiming, et al.
Published: (2026)

Taming Polysemanticity in LLMs: Provable Feature Recovery via Sparse Autoencoders
by: Chen, Siyu, et al.
Published: (2025)

Can Stationary Distributions of Scale-Invariant Neural Networks Be Described by the Thermodynamics of an Ideal Gas?
by: Sadrtdinov, Ildus, et al.
Published: (2025)

Augmentation Invariant Manifold Learning
by: Wang, Shulei
Published: (2022)