Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks
Fuente:
arXiv
Guardado en:
| Autores principales: | Sohn, Jy-yong, Kwon, Dohyun, An, Seoyeon, Lee, Kangwook |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models
por: Lee, Chungpa, et al.
Publicado: (2026)
por: Lee, Chungpa, et al.
Publicado: (2026)
How to Correctly Report LLM-as-a-Judge Evaluations
por: Lee, Chungpa, et al.
Publicado: (2025)
por: Lee, Chungpa, et al.
Publicado: (2025)
Analysis of Using Sigmoid Loss for Contrastive Learning
por: Lee, Chungpa, et al.
Publicado: (2024)
por: Lee, Chungpa, et al.
Publicado: (2024)
Implicit Hypersurface Approximation Capacity in Deep ReLU Networks
por: Vallin, Jonatan, et al.
Publicado: (2024)
por: Vallin, Jonatan, et al.
Publicado: (2024)
Discrete Functional Geometry of ReLU Networks via ReLU Transition Graphs
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective
por: Kim, Joonkyu, et al.
Publicado: (2025)
por: Kim, Joonkyu, et al.
Publicado: (2025)
On the Similarities of Embeddings in Contrastive Learning
por: Lee, Chungpa, et al.
Publicado: (2025)
por: Lee, Chungpa, et al.
Publicado: (2025)
The Geometry of ReLU Networks through the ReLU Transition Graph
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
Pathwise Explanation of ReLU Neural Networks
por: Lim, Seongwoo, et al.
Publicado: (2025)
por: Lim, Seongwoo, et al.
Publicado: (2025)
N-ReLU: Zero-Mean Stochastic Extension of ReLU
por: Manik, Md Motaleb Hossen, et al.
Publicado: (2025)
por: Manik, Md Motaleb Hossen, et al.
Publicado: (2025)
Memorization capacity of deep ReLU neural networks characterized by width and depth
por: Yang, Xin, et al.
Publicado: (2026)
por: Yang, Xin, et al.
Publicado: (2026)
Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback
por: Kim, Jungtaek, et al.
Publicado: (2026)
por: Kim, Jungtaek, et al.
Publicado: (2026)
The Resurrection of the ReLU
por: Horuz, Coşku Can, et al.
Publicado: (2025)
por: Horuz, Coşku Can, et al.
Publicado: (2025)
A Theoretical Framework for Preventing Class Collapse in Supervised Contrastive Learning
por: Lee, Chungpa, et al.
Publicado: (2025)
por: Lee, Chungpa, et al.
Publicado: (2025)
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
por: Min, Hancheng, et al.
Publicado: (2023)
por: Min, Hancheng, et al.
Publicado: (2023)
The Cost of Robustness: Tighter Bounds on Parameter Complexity for Robust Memorization in ReLU Nets
por: Kim, Yujun, et al.
Publicado: (2025)
por: Kim, Yujun, et al.
Publicado: (2025)
Optimal Sets and Solution Paths of ReLU Networks
por: Mishkin, Aaron, et al.
Publicado: (2023)
por: Mishkin, Aaron, et al.
Publicado: (2023)
On Size-Independent Sample Complexity of ReLU Networks
por: Sellke, Mark
Publicado: (2023)
por: Sellke, Mark
Publicado: (2023)
Online Realizable Regression and Applications for ReLU Networks
por: Doron-Arad, Ilan, et al.
Publicado: (2026)
por: Doron-Arad, Ilan, et al.
Publicado: (2026)
Convexity in ReLU Neural Networks: beyond ICNNs?
por: Gagneux, Anne, et al.
Publicado: (2025)
por: Gagneux, Anne, et al.
Publicado: (2025)
SurvReLU: Inherently Interpretable Survival Analysis via Deep ReLU Networks
por: Sun, Xiaotong, et al.
Publicado: (2024)
por: Sun, Xiaotong, et al.
Publicado: (2024)
Constructive Universal Approximation and Finite Sample Memorization by Narrow Deep ReLU Networks
por: Hernández, Martín, et al.
Publicado: (2024)
por: Hernández, Martín, et al.
Publicado: (2024)
Stochastic Bandits with ReLU Neural Networks
por: Xu, Kan, et al.
Publicado: (2024)
por: Xu, Kan, et al.
Publicado: (2024)
On Space Folds of ReLU Neural Networks
por: Lewandowski, Michal, et al.
Publicado: (2025)
por: Lewandowski, Michal, et al.
Publicado: (2025)
Soft Task-Aware Routing of Experts for Equivariant Representation Learning
por: Jeon, Jaebyeong, et al.
Publicado: (2025)
por: Jeon, Jaebyeong, et al.
Publicado: (2025)
Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks
por: Lee, Hyungu, et al.
Publicado: (2025)
por: Lee, Hyungu, et al.
Publicado: (2025)
Optimizing DDPM Sampling with Shortcut Fine-Tuning
por: Fan, Ying, et al.
Publicado: (2023)
por: Fan, Ying, et al.
Publicado: (2023)
ReLU-KAN: New Kolmogorov-Arnold Networks that Only Need Matrix Addition, Dot Multiplication, and ReLU
por: Qiu, Qi, et al.
Publicado: (2024)
por: Qiu, Qi, et al.
Publicado: (2024)
Three Quantization Regimes for ReLU Networks
por: Ou, Weigutian, et al.
Publicado: (2024)
por: Ou, Weigutian, et al.
Publicado: (2024)
Topological Expressivity of ReLU Neural Networks
por: Ergen, Ekin, et al.
Publicado: (2023)
por: Ergen, Ekin, et al.
Publicado: (2023)
Hidden Minima in Two-Layer ReLU Networks
por: Arjevani, Yossi
Publicado: (2023)
por: Arjevani, Yossi
Publicado: (2023)
On the Local Complexity of Linear Regions in Deep ReLU Networks
por: Patel, Niket, et al.
Publicado: (2024)
por: Patel, Niket, et al.
Publicado: (2024)
Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient
por: Dinh, Vu C., et al.
Publicado: (2024)
por: Dinh, Vu C., et al.
Publicado: (2024)
ReLU Networks as Random Functions: Their Distribution in Probability Space
por: Chaudhari, Shreyas, et al.
Publicado: (2025)
por: Chaudhari, Shreyas, et al.
Publicado: (2025)
Noisy Interpolation Learning with Shallow Univariate ReLU Networks
por: Joshi, Nirmit, et al.
Publicado: (2023)
por: Joshi, Nirmit, et al.
Publicado: (2023)
Training a Two Layer ReLU Network Analytically
por: Barbu, Adrian
Publicado: (2023)
por: Barbu, Adrian
Publicado: (2023)
Implicit Regularization Towards Rank Minimization in ReLU Networks
por: Timor, Nadav, et al.
Publicado: (2022)
por: Timor, Nadav, et al.
Publicado: (2022)
The Symmetries of Three-Layer ReLU Networks
por: Gegenfurtner, Johanna Marie, et al.
Publicado: (2026)
por: Gegenfurtner, Johanna Marie, et al.
Publicado: (2026)
When Are Bias-Free ReLU Networks Effectively Linear Networks?
por: Zhang, Yedi, et al.
Publicado: (2024)
por: Zhang, Yedi, et al.
Publicado: (2024)
Brownian ReLU(Br-ReLU): A New Activation Function for a Long-Short Term Memory (LSTM) Network
por: Awiakye-Marfo, George, et al.
Publicado: (2026)
por: Awiakye-Marfo, George, et al.
Publicado: (2026)
Ejemplares similares
-
Fine-Tuning Without Forgetting In-Context Learning: A Theoretical Analysis of Linear Attention Models
por: Lee, Chungpa, et al.
Publicado: (2026) -
How to Correctly Report LLM-as-a-Judge Evaluations
por: Lee, Chungpa, et al.
Publicado: (2025) -
Analysis of Using Sigmoid Loss for Contrastive Learning
por: Lee, Chungpa, et al.
Publicado: (2024) -
Implicit Hypersurface Approximation Capacity in Deep ReLU Networks
por: Vallin, Jonatan, et al.
Publicado: (2024) -
Discrete Functional Geometry of ReLU Networks via ReLU Transition Graphs
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)