Search Results for author: Song Chong

Found 4 papers, 3 papers with code

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

1 code implementation5 Jul 2022 Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong, Se-Young Yun

This challenge, on the other hand, is interested in the exploration capability of MARL algorithms to efficiently learn implicit multi-stage tasks and environmental factors as well as micro-control.

SMAC+

Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning

1 code implementation NeurIPS 2021 Hayeon Lee, Sewoong Lee, Song Chong, Sung Ju Hwang

To overcome such limitations, we propose Hardware-adaptive Efficient Latency Predictor (HELP), which formulates the device-specific latency estimation problem as a meta-learning problem, such that we can estimate the latency of a model's performance for a given task on an unseen device with a few samples.

Meta-Learning Neural Architecture Search

HELP: Hardware-Adaptive Efficient Latency Prediction for NAS via Meta-Learning

1 code implementation16 Jun 2021 Hayeon Lee, Sewoong Lee, Song Chong, Sung Ju Hwang

To overcome such limitations, we propose Hardware-adaptive Efficient Latency Predictor (HELP), which formulates the device-specific latency estimation problem as a meta-learning problem, such that we can estimate the latency of a model's performance for a given task on an unseen device with a few samples.

Meta-Learning Neural Architecture Search

Simplified Stochastic Feedforward Neural Networks

no code implementations11 Apr 2017 Kimin Lee, Jaehyung Kim, Song Chong, Jinwoo Shin

In this paper, we aim at developing efficient training methods for SFNN, in particular using known architectures and pre-trained parameters of DNN.

Cannot find the paper you are looking for? You can Submit a new open access paper.