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Exploring the Loss Landscape in Neural Architecture Search
v1v2v3 (latest)

Exploring the Loss Landscape in Neural Architecture Search

6 May 2020
Colin White
Sam Nolen
Yash Savani
ArXiv (abs)PDFHTML

Papers citing "Exploring the Loss Landscape in Neural Architecture Search"

7 / 7 papers shown
Title
Global optimization of graph acquisition functions for neural architecture search
Global optimization of graph acquisition functions for neural architecture search
Yilin Xie
Shiqiang Zhang
Jixiang Qing
Ruth Misener
Calvin Tsay
69
0
0
29 May 2025
Hyperparameter Optimization via Interacting with Probabilistic Circuits
Jonas Seng
Fabrizio G. Ventola
Zhongjie Yu
Kristian Kersting
TPM
68
0
0
23 May 2025
Neural Architecture Search: Insights from 1000 Papers
Neural Architecture Search: Insights from 1000 Papers
Colin White
Mahmoud Safari
R. Sukthanker
Binxin Ru
T. Elsken
Arber Zela
Debadeepta Dey
Frank Hutter
3DVAI4CE
147
143
0
20 Jan 2023
HiveNAS: Neural Architecture Search using Artificial Bee Colony
  Optimization
HiveNAS: Neural Architecture Search using Artificial Bee Colony Optimization
M. Shahawy
E. Benkhelifa
66
1
0
18 Nov 2022
Automated Dominative Subspace Mining for Efficient Neural Architecture
  Search
Automated Dominative Subspace Mining for Efficient Neural Architecture Search
Yaofo Chen
Yong Guo
Daihai Liao
Fanbing Lv
Hengjie Song
James Tin-Yau Kwok
Mingkui Tan
90
4
0
31 Oct 2022
Shortest Edit Path Crossover: A Theory-driven Solution to the
  Permutation Problem in Evolutionary Neural Architecture Search
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search
Xin Qiu
Risto Miikkulainen
104
2
0
25 Oct 2022
Learning Where To Look -- Generative NAS is Surprisingly Efficient
Learning Where To Look -- Generative NAS is Surprisingly Efficient
Jovita Lukasik
Steffen Jung
Margret Keuper
79
15
0
16 Mar 2022
1