ResearchTrend.AI
Probabilistic Line Searches for Stochastic Optimization
v1v2v3v4 (latest)

Probabilistic Line Searches for Stochastic Optimization

Maren Mahsereci
Philipp Hennig
    ODL
ArXiv (abs)PDFHTML

Papers citing "Probabilistic Line Searches for Stochastic Optimization"

10 / 10 papers shown
Title
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
KOALA: A Kalman Optimization Algorithm with Loss Adaptivity
A. Davtyan
Sepehr Sameni
L. Cerkezi
Givi Meishvili
Adam Bielski
Paolo Favaro
ODL
143
3
0
07 Jul 2021
Coupling Adaptive Batch Sizes with Learning Rates
Coupling Adaptive Batch Sizes with Learning Rates
Lukas Balles
Javier Romero
Philipp Hennig
ODL
156
110
0
15 Dec 2016
Learning to learn by gradient descent by gradient descent
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
134
2,009
0
14 Jun 2016
Learning to Optimize
Learning to Optimize
Ke Li
Jitendra Malik
63
258
0
06 Jun 2016
Using Deep Q-Learning to Control Optimization Hyperparameters
Using Deep Q-Learning to Control Optimization Hyperparameters
Samantha Hansen
60
40
0
12 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.1K
150,433
0
22 Dec 2014
Streaming Variational Bayes
Streaming Variational Bayes
Tamara Broderick
N. Boyd
Andre Wibisono
Ashia Wilson
Michael I. Jordan
88
346
0
25 Jul 2013
Stochastic Variational Inference
Stochastic Variational Inference
Matt Hoffman
David M. Blei
Chong-Jun Wang
John Paisley
BDL
277
2,628
0
29 Jun 2012
Fast Variational Inference in the Conjugate Exponential Family
Fast Variational Inference in the Conjugate Exponential Family
J. Hensman
M. Rattray
Neil D. Lawrence
BDL
74
134
0
22 Jun 2012
No More Pesky Learning Rates
No More Pesky Learning Rates
Tom Schaul
Sixin Zhang
Yann LeCun
143
478
0
06 Jun 2012