39 citations · 54 across the 9 of their papers we have counts for
4 papers · 1 filter
OpenAttention: One Percent Is Enough with Tail Proxies
Hyunwoo Yu, Jongbeom Lee, Hyunbin Kim +8
Sparse attention reads only a small subset of the key-value cache, and how to treat the unread tail remains a key challenge. Discarding the tail biases the output, and sampling it…
Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak +3
Because deep learning is vulnerable to noisy labels, sample selection techniques, which train networks with only clean labeled data, have attracted a great attention. However, if t…
Core-set Sampling for Efficient Neural Architecture Search
Jae-hun Shim, Kyeongbo Kong, Suk-Ju Kang
Neural architecture search (NAS), an important branch of automatic machine learning, has become an effective approach to automate the design of deep learning models. However, the m…
Enhancing Stability in Training Conditional Generative Adversarial Networks via Selective Data Matching
Kyeongbo Kong, Kyunghun Kim, Suk-Ju Kang
Conditional generative adversarial networks (cGANs) have demonstrated remarkable success due to their class-wise controllability and superior quality for complex generation tasks.…