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pro vyhledávání: '"Kim, Kangil"'
Autor:
Park, Jinwook, Kim, Kangil
Neural parameterization has significantly advanced unsupervised grammar induction. However, training these models with a traditional likelihood loss for all possible parses exacerbates two issues: 1) $\textit{structural optimization ambiguity}$ that
Externí odkaz:
http://arxiv.org/abs/2407.16181
In the feature space, the collapse between features invokes critical problems in representation learning by remaining the features undistinguished. Interpolation-based augmentation methods such as mixup have shown their effectiveness in relieving the
Externí odkaz:
http://arxiv.org/abs/2401.14696
Symmetries of input and latent vectors have provided valuable insights for disentanglement learning in VAEs.However, only a few works were proposed as an unsupervised method, and even these works require known factor information in training data. We
Externí odkaz:
http://arxiv.org/abs/2401.08897
Revisiting Softmax Masking: Stop Gradient for Enhancing Stability in Replay-based Continual Learning
In replay-based methods for continual learning, replaying input samples in episodic memory has shown its effectiveness in alleviating catastrophic forgetting. However, the potential key factor of cross-entropy loss with softmax in causing catastrophi
Externí odkaz:
http://arxiv.org/abs/2309.14808
Autor:
Kwon, Minchan, Kim, Kangil
In real life, adversarial attack to deep learning models is a fatal security issue. However, the issue has been rarely discussed in a widely used class-incremental continual learning (CICL). In this paper, we address problems of applying adversarial
Externí odkaz:
http://arxiv.org/abs/2305.13678
Knowledge distillation is an approach to transfer information on representations from a teacher to a student by reducing their difference. A challenge of this approach is to reduce the flexibility of the student's representations inducing inaccurate
Externí odkaz:
http://arxiv.org/abs/2204.08922
Publikováno v:
In Journal of Water Process Engineering November 2024 67
Autor:
Kim, Kangil1 (AUTHOR) interpres87@gmail.com
Publikováno v:
Religions. Aug2024, Vol. 15 Issue 8, p985. 10p.
Autor:
Lee, Heejae, Shin, Yongwook, Kim, Kangil, Kim, Haekwang, Kang, Joonseok, Yoo, Jewan, Kang, Sung Un, Yoo, Youngsuk, Hong, Yong Cheol
Publikováno v:
In Chemical Engineering Journal 15 July 2024 492