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Gradient descent follows the regularization path for general losses

Gradient descent follows the regularization path for general losses

19 June 2020
Ziwei Ji
Miroslav Dudík
Robert Schapire
Matus Telgarsky
    AI4CE
    FaML
ArXivPDFHTML

Papers citing "Gradient descent follows the regularization path for general losses"

14 / 14 papers shown
Title
Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations
Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations
Yize Zhao
Tina Behnia
V. Vakilian
Christos Thrampoulidis
60
8
0
20 Feb 2025
When does compositional structure yield compositional generalization? A kernel theory
When does compositional structure yield compositional generalization? A kernel theory
Samuel Lippl
Kim Stachenfeld
NAI
CoGe
73
5
0
26 May 2024
General Loss Functions Lead to (Approximate) Interpolation in High
  Dimensions
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
Kuo-Wei Lai
Vidya Muthukumar
31
5
0
13 Mar 2023
Iterative regularization in classification via hinge loss diagonal
  descent
Iterative regularization in classification via hinge loss diagonal descent
Vassilis Apidopoulos
T. Poggio
Lorenzo Rosasco
S. Villa
29
2
0
24 Dec 2022
Importance Tempering: Group Robustness for Overparameterized Models
Importance Tempering: Group Robustness for Overparameterized Models
Yiping Lu
Wenlong Ji
Zachary Izzo
Lexing Ying
42
7
0
19 Sep 2022
On the Implicit Bias in Deep-Learning Algorithms
On the Implicit Bias in Deep-Learning Algorithms
Gal Vardi
FedML
AI4CE
34
72
0
26 Aug 2022
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Imbalance Trouble: Revisiting Neural-Collapse Geometry
Christos Thrampoulidis
Ganesh Ramachandra Kini
V. Vakilian
Tina Behnia
26
69
0
10 Aug 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity
Benefits of Additive Noise in Composing Classes with Bounded Capacity
A. F. Pour
H. Ashtiani
33
3
0
14 Jun 2022
Robust Training under Label Noise by Over-parameterization
Robust Training under Label Noise by Over-parameterization
Sheng Liu
Zhihui Zhu
Qing Qu
Chong You
NoLa
OOD
27
106
0
28 Feb 2022
Stability vs Implicit Bias of Gradient Methods on Separable Data and
  Beyond
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond
Matan Schliserman
Tomer Koren
24
23
0
27 Feb 2022
Thinking Outside the Ball: Optimal Learning with Gradient Descent for
  Generalized Linear Stochastic Convex Optimization
Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization
I Zaghloul Amir
Roi Livni
Nathan Srebro
30
6
0
27 Feb 2022
On Margin Maximization in Linear and ReLU Networks
On Margin Maximization in Linear and ReLU Networks
Gal Vardi
Ohad Shamir
Nathan Srebro
50
28
0
06 Oct 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu
Tianyu Ding
Jinxin Zhou
Xiao Li
Chong You
Jeremias Sulam
Qing Qu
27
194
0
06 May 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
27
93
0
02 Mar 2021
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