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https://arxiv.org/abs/2003.02237v2

https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1468-0394.2005.00299.x Making sense of card sorting data Abstract: Among the knowledge elicitation techniques card sorting is notable for its simplicity of use, its focus on subjects' terminology (rather than that of external experts) and its ability to e... onlinelibrary.wiley.com Abstract 지식 추출 기술 중 카드소팅은 주제 용어의 초점 및 잠재적 지식을 이끌어내는 능력으로 유명하다. 대용..

https://arxiv.org/abs/2002.06274v2 Single Unit Status in Deep Convolutional Neural Network Codes for Face Identification: Sparseness Redefined Deep convolutional neural networks (DCNNs) trained for face identification develop representations that generalize over variable images, while retaining subject (e.g., gender) and image (e.g., viewpoint) information. Identity, gender, and viewpoint codes ..

https://arxiv.org/abs/1912.06779v2 Predictive Precompute with Recurrent Neural Networks In both mobile and web applications, speeding up user interface response times can often lead to significant improvements in user engagement. A common technique to improve responsiveness is to precompute data ahead of time for specific activities. However, arxiv.org abstract 웹 어플리케이션 및 모바일 어플리케이션에서 사용하는 인터페이스..

https://arxiv.org/abs/2002.10674v1 Separating the Effects of Batch Normalization on CNN Training Speed and Stability Using Classical Adaptive Filter Theory Batch Normalization (BatchNorm) is commonly used in Convolutional Neural Networks (CNNs) to improve training speed and stability. However, there is still limited consensus on why this technique is effective. This paper uses concepts from the ..