34 citations · 56 across the 67 of their papers we have counts for
5 papers · 1 filter
Combating Label Distribution Shift for Active Domain Adaptation
Sehyun Hwang, Sohyun Lee, Sungyeon Kim +2
We consider the problem of active domain adaptation (ADA) to unlabeled target data, of which subset is actively selected and labeled given a budget constraint. Inspired by recent a…
Towards Sequence-Level Training for Visual Tracking
Minji Kim, Seungkwan Lee, Jungseul Ok +2
Despite the extensive adoption of machine learning on the task of visual object tracking, recent learning-based approaches have largely overlooked the fact that visual tracking is…
Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning
Byungchan Ko, Jungseul Ok
In deep reinforcement learning (RL), data augmentation is widely considered as a tool to induce a set of useful priors about semantic consistency and improve sample efficiency and…
MetaSSD: Meta-Learned Self-Supervised Detection
Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon +1
Deep learning-based symbol detector gains increasing attention due to the simple algorithm design than the traditional model-based algorithms such as Viterbi and BCJR. The supervis…
Few-Shot Unlearning by Model Inversion
Youngsik Yoon, Jinhwan Nam, Hyojeong Yun +3
We consider a practical scenario of machine unlearning to erase a target dataset, which causes unexpected behavior from the trained model. The target dataset is often assumed to be…