12 citations · 15 across the 9 of their papers we have counts for
9 papers
AliO: Output Alignment Matters in Long-Term Time Series Forecasing
Kwangryeol Park, Jaeho Kim, Seulki Lee
Long-term Time Series Forecasting (LTSF) tasks, which leverage the current data sequence as input to predict the future sequence, have become increasingly crucial in real-world app…
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
Jaeho Kim, Seulki Lee
Unsupervised domain adaptation (UDA) for time series data remains a critical challenge in deep learning, with traditional pseudo-labeling strategies failing to capture temporal pat…
Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
Jaeho Kim, Yunseok Lee, Seulki Lee
The peer review process in major artificial intelligence (AI) conferences faces unprecedented challenges with the surge of paper submissions (exceeding 10,000 submissions per venue…
On-device Sora: Enabling Training-Free Diffusion-based Text-to-Video Generation for Mobile Devices
Bosung Kim, Kyuhwan Lee, Isu Jeong +3
We present On-device Sora, the first model training-free solution for diffusion-based on-device text-to-video generation that operates efficiently on smartphone-grade devices. To a…
On-device Sora: Enabling Training-Free Diffusion-based Text-to-Video Generation for Mobile Devices
Bosung Kim, Kyuhwan Lee, Isu Jeong +3
We present On-device Sora, the first model training-free solution for diffusion-based on-device text-to-video generation that operates efficiently on smartphone-grade devices. To a…
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
Kwangryeol Park, Seulki Lee
We propose SMMF (Square-Matricized Momentum Factorization), a memory-efficient optimizer that reduces the memory requirement of the widely used adaptive learning rate optimizers, s…
Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks
Jaewook Lee, Yoel Park, Seulki Lee
In this paper, we introduce a memory-efficient CNN (convolutional neural network), which enables resource-constrained low-end embedded and IoT devices to perform on-device vision t…
CAFO: Feature-Centric Explanation on Time Series Classification
Jaeho Kim, Seok-Ju Hahn, Yoontae Hwang +2
In multivariate time series (MTS) classification, finding the important features (e.g., sensors) for model performance is crucial yet challenging due to the complex, high-dimension…
Intermittent Learning: On-Device Machine Learning on Intermittently Powered System
Seulki Lee, Bashima Islam, Yubo Luo +1
This paper introduces intermittent learning - the goal of which is to enable energy harvested computing platforms capable of executing certain classes of machine learning tasks eff…