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Yang Liu

10 papers hereh-index 450 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author9

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.CV3
  • cs.CL1
same name
  • Yang Liu — 129 papers, h 73
  • Yang Liu — 94 papers, h 65
  • Yang Liu — 41 papers, h 63
  • Yang Liu — 38 papers, h 23
  • Yang Liu — 35 papers, h 27
  • Yang Liu — 34 papers, h 39

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedImproving Resnet-9 Generalization Trained on Small Datasets

2 citations · 4 across the 10 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Accelerating the Low-Rank Decomposed Models

Habib Hajimolahoseini, Walid Ahmed, Austin Wen +1

Tensor decomposition is a mathematically supported technique for data compression. It consists of applying some kind of a Low Rank Decomposition technique on the tensors or matrice…

cs.CV2024

Is 3D Convolution with 5D Tensors Really Necessary for Video Analysis?

Habib Hajimolahoseini, Walid Ahmed, Austin Wen +1

In this paper, we present a comprehensive study and propose several novel techniques for implementing 3D convolutional blocks using 2D and/or 1D convolutions with only 4D and/or 3D…

cs.CL2024

Single Parent Family: A Spectrum of Family Members from a Single Pre-Trained Foundation Model

Habib Hajimolahoseini, Mohammad Hassanpour, Foozhan Ataiefard +2

This paper introduces a novel method of Progressive Low Rank Decomposition (PLRD) tailored for the compression of large language models. Our approach leverages a pre-trained model,…

cs.CV2024

SkipViT: Speeding Up Vision Transformers with a Token-Level Skip Connection

Foozhan Ataiefard, Walid Ahmed, Habib Hajimolahoseini +7

Vision transformers are known to be more computationally and data-intensive than CNN models. These transformer models such as ViT, require all the input image tokens to learn the r…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.