6 citations · 15 across the 16 of their papers we have counts for
6 papers · 1 filter
Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection
Jungwook Seo, Sangwon Son, Minjeong Kim +3
Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or localized oscillatory fluctuat…
SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
Low-Rank Adaptation (LoRA) enables efficient adaptation of large pretrained models to downstream tasks by parameterizing weight updates with low-rank matrices. In this paper, we in…
Find A Winning Sign: Sign Is All We Need to Win the Lottery
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
The Lottery Ticket Hypothesis (LTH) posits the existence of a sparse subnetwork (a.k.a. winning ticket) that can generalize comparably to its over-parameterized counterpart when tr…
Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning
Sungyong Baik, Janghoon Choi, Heewon Kim +3
In few-shot learning scenarios, the challenge is to generalize and perform well on new unseen examples when only very few labeled examples are available for each task. Model-agnost…
Meta-Learning with Adaptive Hyperparameters
Sungyong Baik, Myungsub Choi, Janghoon Choi +2
Despite its popularity, several recent works question the effectiveness of MAML when test tasks are different from training tasks, thus suggesting various task-conditioned methodol…
Learning to Forget for Meta-Learning
Sungyong Baik, Seokil Hong, Kyoung Mu Lee
Few-shot learning is a challenging problem where the goal is to achieve generalization from only few examples. Model-agnostic meta-learning (MAML) tackles the problem by formulatin…