Tensorizing Subgraph Search in the Supernet

01/04/2021
by   Hansi Yang, et al.
0

Recently, a special kind of graph, i.e., supernet, which allows two nodes connected by multi-choice edges, has exhibited its power in neural architecture search (NAS) by searching for better architectures for computer vision (CV) and natural language processing (NLP) tasks. In this paper, we discover that the design of such discrete architectures also appears in many other important learning tasks, e.g., logical chain inference in knowledge graphs (KGs) and meta-path discovery in heterogeneous information networks (HINs). Thus, we are motivated to generalize the supernet search problem on a broader horizon. However, none of the existing works are effective since the supernet topology is highly task-dependent and diverse. To address this issue, we propose to tensorize the supernet, i.e., unify the subgraph search problems by a tensor formulation and encode the topology inside the supernet by a tensor network. We further propose an efficient algorithm that admits both stochastic and deterministic objectives to solve the search problem. Finally, we perform extensive experiments on diverse learning tasks, i.e., architecture design for CV, logic inference for KG, and meta-path discovery for HIN. Empirical results demonstrate that our method leads to better performance and architectures.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

10/08/2020

Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks

Neural Architecture Search (NAS) methods, which automatically learn enti...
04/21/2021

Making Differentiable Architecture Search less local

Neural architecture search (NAS) is a recent methodology for automating ...
06/12/2020

NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing

Neural Architecture Search (NAS) is a promising and rapidly evolving res...
09/06/2019

Efficient Automatic Meta Optimization Search for Few-Shot Learning

Previous works on meta-learning either relied on elaborately hand-design...
08/04/2021

Generic Neural Architecture Search via Regression

Most existing neural architecture search (NAS) algorithms are dedicated ...
04/25/2020

Deep Multimodal Neural Architecture Search

Designing effective neural networks is fundamentally important in deep m...
04/21/2021

Searching to Sparsify Tensor Decomposition for N-ary Relational Data

Tensor, an extension of the vector and matrix to the multi-dimensional c...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.