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researcher

Jinho Lee

4 papers hereh-index 5115 citations11 works total

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

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1
  • q-fin.GN1
same name
  • Jinho Lee — 18 papers, h 41
  • Jinho Lee — 15 papers, h 9
  • Jinho Lee — 9 papers, h 14
  • Jinho Lee — 7 papers, h 1
  • Jinho Lee — 6 papers, h 2
  • Jinho Lee — 4 papers, h 8

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
20192022
most citedSimEx: Express Prediction of Inter-dataset Similarity by a Fleet of Autoencoders

4 citations · 8 across the 4 of their papers we have counts for

collaborators

4 papers

q-fin.GN2022★ 2 cited

Shai-am: A Machine Learning Platform for Investment Strategies

Jonghun Kwak, Jungyu Ahn, Jinho Lee +1

The finance industry has adopted machine learning (ML) as a form of quantitative research to support better investment decisions, yet there are several challenges often overlooked…

cs.CV2022★ 2 cited

It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher

Kanghyun Choi, Hye Yoon Lee, Deokki Hong +4

Model quantization is considered as a promising method to greatly reduce the resource requirements of deep neural networks. To deal with the performance drop induced by quantizatio…

cs.LG2020★ 4 cited

SimEx: Express Prediction of Inter-dataset Similarity by a Fleet of Autoencoders

Inseok Hwang, Jinho Lee, Frank Liu +1

Knowing the similarity between sets of data has a number of positive implications in training an effective model, such as assisting an informed selection out of known datasets favo…

cs.LG2019

MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design

Mayoore S. Jaiswal, Bumsoo Kang, Jinho Lee +1

Target encoding is an effective technique to deliver better performance for conventional machine learning methods, and recently, for deep neural networks as well. However, the exis…

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