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Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization

Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization

21 August 2023
M. D. Santis
Jordan Frécon
Francesco Rinaldi
Saverio Salzo
Martin Schmidt
Martin Schmidt
ArXivPDFHTML

Papers citing "Relax and penalize: a new bilevel approach to mixed-binary hyperparameter optimization"

13 / 13 papers shown
Title
Data Distillation: A Survey
Data Distillation: A Survey
Noveen Sachdeva
Julian McAuley
DD
63
74
0
11 Jan 2023
Advancing Model Pruning via Bi-level Optimization
Advancing Model Pruning via Bi-level Optimization
Yihua Zhang
Yuguang Yao
Parikshit Ram
Pu Zhao
Tianlong Chen
Min-Fong Hong
Yanzhi Wang
Sijia Liu
72
67
0
08 Oct 2022
Amortized Implicit Differentiation for Stochastic Bilevel Optimization
Amortized Implicit Differentiation for Stochastic Bilevel Optimization
Michael Arbel
Julien Mairal
118
59
0
29 Nov 2021
Data Summarization via Bilevel Optimization
Data Summarization via Bilevel Optimization
Zalan Borsos
Mojmír Mutný
Marco Tagliasacchi
Andreas Krause
57
8
0
26 Sep 2021
Delta-STN: Efficient Bilevel Optimization for Neural Networks using
  Structured Response Jacobians
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians
Juhan Bae
Roger C. Grosse
32
24
0
26 Oct 2020
On the Iteration Complexity of Hypergradient Computation
On the Iteration Complexity of Hypergradient Computation
Riccardo Grazzi
Luca Franceschi
Massimiliano Pontil
Saverio Salzo
81
195
0
29 Jun 2020
Learning Discrete Structures for Graph Neural Networks
Learning Discrete Structures for Graph Neural Networks
Luca Franceschi
Mathias Niepert
Massimiliano Pontil
X. He
GNN
39
411
0
28 Mar 2019
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi
P. Frasconi
Saverio Salzo
Riccardo Grazzi
Massimiliano Pontil
168
722
0
13 Jun 2018
Hyperparameter optimization with approximate gradient
Hyperparameter optimization with approximate gradient
Fabian Pedregosa
78
449
0
07 Feb 2016
Gradient-based Hyperparameter Optimization through Reversible Learning
Gradient-based Hyperparameter Optimization through Reversible Learning
D. Maclaurin
David Duvenaud
Ryan P. Adams
DD
116
941
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
316
149,474
0
22 Dec 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio
Francis R. Bach
Simon Lacoste-Julien
ODL
79
1,817
0
01 Jul 2014
The composite absolute penalties family for grouped and hierarchical
  variable selection
The composite absolute penalties family for grouped and hierarchical variable selection
P. Zhao
Guilherme V. Rocha
Bin Yu
99
672
0
02 Sep 2009
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