b'Youngeun Kim'

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Featured Co-authors

Priyadarshini Panda
67 publications
Changick Kim
44 publications
Yuhang Li
35 publications
Jiwon Kim
27 publications
Leandros Tassiulas
25 publications
Dongyoon Han
24 publications
Taekyung Kim
21 publications
Abhishek Moitra
19 publications
Donghyeon Cho
16 publications
Seunghan Yang
15 publications
Abhiroop Bhattacharjee
12 publications

research

∙ 05/26/2023

Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks

Spiking Neural Networks (SNNs) have gained increasing attention as energ...

0 Youngeun Kim, et al. ∙

research

∙ 05/26/2023

Do We Really Need a Large Number of Visual Prompts?

Due to increasing interest in adapting models on resource-constrained ed...

0 Youngeun Kim, et al. ∙

research

∙ 05/11/2023

Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems

Federated Learning (FL) is a privacy-preserving distributed machine lear...

0 Yeshwanth Venkatesha, et al. ∙

research

∙ 04/25/2023

Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient

Spiking Neural Networks (SNNs) are recognized as the candidate for the n...

0 Yuhang Li, et al. ∙

research

∙ 04/02/2023

SEENN: Towards Temporal Spiking Early-Exit Neural Networks

Spiking Neural Networks (SNNs) have recently become more popular as a bi...

0 Yuhang Li, et al. ∙

research

∙ 03/30/2023

XPert: Peripheral Circuit Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing

The hardware-efficiency and accuracy of Deep Neural Networks (DNNs) impl...

0 Abhishek Moitra, et al. ∙

research

∙ 02/13/2023

Workload-Balanced Pruning for Sparse Spiking Neural Networks

Pruning for Spiking Neural Networks (SNNs) has emerged as a fundamental ...

0 Ruokai Yin, et al. ∙

research

∙ 11/26/2022

Exploring Temporal Information Dynamics in Spiking Neural Networks

Most existing Spiking Neural Network (SNN) works state that SNNs may uti...

0 Youngeun Kim, et al. ∙

research

∙ 11/14/2022

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks

We study the Human Activity Recognition (HAR) task, which predicts user ...

0 Yuhang Li, et al. ∙

research

∙ 07/04/2022

Lottery Ticket Hypothesis for Spiking Neural Networks

Spiking Neural Networks (SNNs) have recently emerged as a new generation...

1 Youngeun Kim, et al. ∙

research

∙ 06/20/2022

Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars

Spiking Neural Networks (SNNs) have recently emerged as the low-power al...

8 Abhiroop Bhattacharjee, et al. ∙

research

∙ 04/25/2022

Loss-based Sequential Learning for Active Domain Adaptation

Active domain adaptation (ADA) studies have mainly addressed query selec...

0 Kyeongtak Han, et al. ∙

research

∙ 04/11/2022

SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks

Spiking Neural Networks (SNNs) have gained huge attention as a potential...

5 Ruokai Yin, et al. ∙

research

∙ 03/24/2022

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization

Federated learning has been extensively studied and is the prevalent met...

1 Yeshwanth Venkatesha, et al. ∙

research

∙ 03/11/2022

Neuromorphic Data Augmentation for Training Spiking Neural Networks

Developing neuromorphic intelligence on event-based datasets with spikin...

10 Yuhang Li, et al. ∙

research

∙ 02/09/2022

Adversarial Detection without Model Information

Most prior state-of-the-art adversarial detection works assume that the ...

15 Abhishek Moitra, et al. ∙

research

∙ 01/31/2022

Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?

Recent Spiking Neural Networks (SNNs) works focus on an image classifica...

1 Youngeun Kim, et al. ∙

research

∙ 01/23/2022

Neural Architecture Search for Spiking Neural Networks

Spiking Neural Networks (SNNs) have gained huge attention as a potential...

14 Youngeun Kim, et al. ∙

research

∙ 01/05/2022

Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar

Binary memristive crossbars have gained huge attention as an energy-effi...

4 Youngeun Kim, et al. ∙

research

∙ 10/14/2021

Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation

Spiking Neural Networks (SNNs) have recently emerged as the low-power al...

20 Youngeun Kim, et al. ∙

research

∙ 06/11/2021

Federated Learning with Spiking Neural Networks

As neural networks get widespread adoption in resource-constrained embed...

9 Yeshwanth Venkatesha, et al. ∙

research

∙ 04/07/2021

PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks

How can we bring both privacy and energy-efficiency to a neural system o...

16 Youngeun Kim, et al. ∙

research

∙ 03/26/2021

Visual Explanations from Spiking Neural Networks using Interspike Intervals

Spiking Neural Networks (SNNs) compute and communicate with asynchronous...

11 Youngeun Kim, et al. ∙

research

∙ 10/05/2020

Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch

Spiking Neural Networks (SNNs) have recently emerged as an alternative t...

0 Youngeun Kim, et al. ∙

research

∙ 08/07/2020

Associative Partial Domain Adaptation

Partial Adaptation (PDA) addresses a practical scenario in which the tar...

0 Youngeun Kim, et al. ∙

research

∙ 07/03/2020

Domain Adaptation without Source Data

Domain adaptation assumes that samples from source and target domains ar...

14 Youngeun Kim, et al. ∙

research

∙ 05/16/2020

Partial Domain Adaptation Using Graph Convolutional Networks

Partial domain adaptation (PDA), in which we assume the target label spa...

0 Seunghan Yang, et al. ∙

research

∙ 12/03/2019

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

Visible-infrared person re-identification (VI-ReID) is an important task...

0 Seokeon Choi, et al. ∙

research

∙ 10/12/2019

Combinational Class Activation Maps for Weakly Supervised Object Localization

Weakly supervised object localization has recently attracted attention s...

24 Seunghan Yang, et al. ∙

research

∙ 10/02/2019

CNN-based Semantic Segmentation using Level Set Loss

Thesedays, Convolutional Neural Networks are widely used in semantic seg...

51 Youngeun Kim, et al. ∙

research

∙ 09/29/2019

Learning to Align Multi-Camera Domain for Unsupervised Video Person Re-Identification

Most video person re-identification (re-ID) methods are mainly based on ...

18 Youngeun Kim, et al. ∙

research

∙ 09/29/2019

RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation

In this paper, we introduce a self-supervised approach for video object ...

13 Youngeun Kim, et al. ∙