56 citations · 80 across the 9 of their papers we have counts for
9 papers
Elderly-Contextual Data Augmentation via Speech Synthesis for Elderly ASR
Minsik Lee, Seoi Hong, Chongmin Lee +4
Despite recent progress in automatic speech recognition (ASR), elderly ASR (EASR) remains challenging due to limited training data and the distinct acoustic and linguistic characte…
EnSiam: Self-Supervised Learning With Ensemble Representations
Kyoungmin Han, Minsik Lee
Recently, contrastive self-supervised learning, where the proximity of representations is determined based on the identities of samples, has made remarkable progress in unsupervise…
Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations
Sungheon Park, Minsik Lee, Nojun Kwak
We propose a novel framework for training neural networks which is capable of learning 3D information of non-rigid objects when only 2D annotations are available as ground truths.…
Differentiable Forward and Backward Fixed-Point Iteration Layers
Younghan Jeon, Minsik Lee, Jin Young Choi
Recently, several studies proposed methods to utilize some classes of optimization problems in designing deep neural networks to encode constraints that conventional layers cannot…
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
Jiwoong Park, Minsik Lee, Hyung Jin Chang +2
We propose a symmetric graph convolutional autoencoder which produces a low-dimensional latent representation from a graph. In contrast to the existing graph autoencoders with asym…
Neuro-Optimization: Learning Objective Functions Using Neural Networks
Younghan Jeon, Minsik Lee, Jin Young Choi
Mathematical optimization is widely used in various research fields. With a carefully-designed objective function, mathematical optimization can be quite helpful in solving many pr…
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
An activation boundary for a neuron refers to a separating hyperplane that determines whether the neuron is activated or deactivated. It has been long considered in neural networks…
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Byeongho Heo, Minsik Lee, Sangdoo Yun +1
Many recent works on knowledge distillation have provided ways to transfer the knowledge of a trained network for improving the learning process of a new one, but finding a good te…
Deep Pose Consensus Networks
Geonho Cha, Minsik Lee, Jungchan Cho +1
In this paper, we address the problem of estimating a 3D human pose from a single image, which is important but difficult to solve due to many reasons, such as self-occlusions, wil…