Accepted Papers
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure
Zhijie Deng, Yucen Luo and Jun Zhu
AutoHAS: Efficient Hyperparameter and Architecture Search
Xuanyi Dong, Mingxing Tan, Adams Yu, Daiyi Peng, Bogdan Gabrys and Quoc Le
Tensorizing Neural Architecture Search in the Supernet
Hansi Yang, Quanming Yao and James T. Kwok
Simulation-based Scoring for Model-based Asynchronous Hyperparameter and Neural Architecture Search
Matthias Seeger, Aaron Klein, Thibaut Lienart and Louis Tiao
Making Differentiable Architecture Search less local
Erik Bodin, Federico Tomasi and Zhenwen Dai
Width transfer: on the (in)variance of width optimization
Ting-Wu Chin, Diana Marculescu and Ari Morcos
How Powerful are Performance Predictors in Neural Architecture Search?
Colin White, Arber Zela, Binxin Ru, Yang Liu and Frank Hutter
On Adversarial Robustness: A Neural Architecture Search perspective
Chaitanya Devaguptapu, Gaurav Mittal, Devansh Agarwal and Vineeth N Balasubramanian
A multi-objective perspective on jointly tuning hardware and hyperparameters
David Salinas, Valerio Perrone, Cedric Archambeau and Olivier Cruchant
HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy and Lihi Zelnik
Cost-aware Adversarial Best Arm Identification
Nikita Ivkin, Zohar Karnin, Valerio Perrone and Giovanni Zappella
MONCAE: Multi-Objective Neuroevolution of Convolutional Autoencoders
Daniel Dimanov, Emili Balaguer-Ballester, Shahin Rostami and Colin Singleton
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution
Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias Seeger and Cedric Archambeau
How does Weight Sharing Help in Neural Architecture Search?
Yuge Zhang, Quanlu Zhang and Yaming Yang
AlphaNet: Improved Training of Supernet with Alpha-Divergence
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu and Vikas Chandra
One-Shot Neural Architecture Search Via Compressive Sensing
Minsu Cho, Mohammadreza Soltani and Chinmay Hegde
Rethinking NAS Operations for Diverse Tasks
Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Re and Ameet Talwalkar
Recovering Quantitative Models of Human Information Processing with Differentiable Architecture Search
Flexible Multi-task Networks by Learning Parameter Allocation
Krzysztof Maziarz, Efi Kokiopoulou, Andrea Gesmundo, Luciano Sbaiz, Gabor Bartok and Jesse Berent