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Architecture Search

41 papers with code · Methodology

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Progressive Neural Architecture Search

ECCV 2018 tensorflow/models

We propose a new method for learning the structure of convolutional neural networks (CNNs) that is more efficient than recent state-of-the-art methods based on reinforcement learning and evolutionary algorithms.

ARCHITECTURE SEARCH

Learning Transferable Architectures for Scalable Image Recognition

CVPR 2018 tensorflow/models

In our experiments, we search for the best convolutional layer (or "cell") on the CIFAR-10 dataset and then apply this cell to the ImageNet dataset by stacking together more copies of this cell, each with their own parameters to design a convolutional architecture, named "NASNet architecture".

ARCHITECTURE SEARCH IMAGE CLASSIFICATION

The Evolved Transformer

30 Jan 2019tensorflow/tensor2tensor

Recent works have highlighted the strengths of the Transformer architecture for dealing with sequence tasks.

ARCHITECTURE SEARCH MACHINE TRANSLATION

Auto-Keras: An Efficient Neural Architecture Search System

27 Jun 2018jhfjhfj1/autokeras

In this paper, we propose a novel framework enabling Bayesian optimization to guide the network morphism for efficient neural architecture search.

ARCHITECTURE SEARCH

DARTS: Differentiable Architecture Search

ICLR 2019 quark0/darts

This paper addresses the scalability challenge of architecture search by formulating the task in a differentiable manner.

ARCHITECTURE SEARCH IMAGE CLASSIFICATION LANGUAGE MODELLING

Efficient Neural Architecture Search via Parameter Sharing

9 Feb 2018melodyguan/enas

The controller is trained with policy gradient to select a subgraph that maximizes the expected reward on the validation set.

ARCHITECTURE SEARCH LANGUAGE MODELLING

Exploring Randomly Wired Neural Networks for Image Recognition

2 Apr 2019seungwonpark/RandWireNN

In this paper, we explore a more diverse set of connectivity patterns through the lens of randomly wired neural networks.

ARCHITECTURE SEARCH IMAGE CLASSIFICATION

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

ICLR 2019 MIT-HAN-LAB/ProxylessNAS

We address the high memory consumption issue of differentiable NAS and reduce the computational cost (GPU hours and GPU memory) to the same level of regular training while still allowing a large candidate set.

ARCHITECTURE SEARCH IMAGE CLASSIFICATION

Rethinking the Value of Network Pruning

ICLR 2019 Eric-mingjie/rethinking-network-pruning

Our observations are consistent for multiple network architectures, datasets, and tasks, which imply that: 1) training a large, over-parameterized model is often not necessary to obtain an efficient final model, 2) learned "important" weights of the large model are typically not useful for the small pruned model, 3) the pruned architecture itself, rather than a set of inherited "important" weights, is more crucial to the efficiency in the final model, which suggests that in some cases pruning can be useful as an architecture search paradigm.

ARCHITECTURE SEARCH NETWORK PRUNING

SMASH: One-Shot Model Architecture Search through HyperNetworks

ICLR 2018 ajbrock/SMASH

Designing architectures for deep neural networks requires expert knowledge and substantial computation time.

ARCHITECTURE SEARCH