Name: Hyunghun Cho
Type: User
Company: Applied Data Science Lab@SNU Convergence
Bio: Research interest: Automatic Hyper-Parameter Optimization of Deep Neural Networks.
Location: Suwon Korea, Republic of
Blog: http://adsl.snu.ac.kr
Hyunghun Cho's Projects
playground for ASDL
Automated deep learning algorithms implemented in PyTorch.
Bayesian Optimization with Neural Architectures for Neural Architecture Search - https://arxiv.org/abs/1910.11858
Save schedules from calendar web app
Unmanned Aero Vehicles System for Creative Defense
A JavaScript visualization library for HTML and SVG.
Gray-box automatic hyper-parameter optimization for machine learning
data importer from others to mongodb
Do Internet of Things Yourself!
An open source python library for scalable Bayesian optimisation.
Trainer node of "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks".
Energy Usage Behavior Monitoring System Development
Code repository for Ensemble Bayesian Optimization
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Face Tracking and Counting with Intel RealSense on Java
Meta Learning for Semi-Supervised Few-Shot Classification
[ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration
Just for tutorial
for R exercises
GPU Optimization for Python
Hangul Clock Server
Internet of Things Prototyping with Arduino & Node.JS
a distributed Hyperband implementation on Steroids
HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization packages: SMAC, spearmint and hyperopt
Simple birthday congratuation card
Tuning hyperparams fast with Hyperband
Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms