Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.

Ningjia Huang

dblp:326/7278 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Efficient and distributed learning · 60% Deep learning architectures and training · 40%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Efficient and distributed learning › model compression › pruning › structured pruning
channel pruning
0.612022
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions · ICLR 2022
Machine learning › Deep learning architectures and training
convolutional neural network
0.612022
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions · ICLR 2022
Machine learning › Deep learning architectures and training › convolutional neural network › convolution design
group convolution
0.612022
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions · ICLR 2022
Machine learning › Efficient and distributed learning
model compression
0.612022
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions · ICLR 2022
Machine learning › Efficient and distributed learning › model compression
pruning
0.612022
Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions · ICLR 2022

Methods — techniques the papers use, named apart from their topics

lottery ticket hypothesis · 0.6
YearPublicationVenuePosition
2022 Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions
Shaochen Zhong, Guanqun Zhang, Ningjia Huang
ICLR3