• Understanding deep learning requires rethinking generalization

    WHY? Traditional explanation for generalization of a machine learning model was primarily concerned with tradeoff between model capacity and overfitting. If capacity of a model is too large, you must contrain the capacity to prevent overfitting. Choosing appropriate level of capacity of model has been seen as a key to...


  • Learning to See by Moving

    WHY? Feature learning in Convolution Neural Network requires many hand labeled data. It would be useful if one can use other form of supervision. In nature world, organisms acquire many essential information regarding vision by moving itself(egomotion). WHAT? This paper tried to prove that the elementary features learned by egomotion...


  • Adversarial Variational Bayes: Unifying Variational Autoencoder and Generative Adversarial Networks

    WHY? In VAE framework, the quality of the generation relies on the expressiveness of inference model. Restricting hidden variables to Gaussian distribution with KL divergence limits the expressiveness of the model. WHAT? Adversarial Variational Bayes apply gan loss to VAE framework. AVB is different from former VAE in 2 ways:...


  • Hidden Dragon (2000)

    평점: 4 아름다운 영화를 만드는데 꼭 최첨단 기술만이 필요한 건 아니라는 것을 잘 보여주는 사례. 와이어 액션도 촌스럽지 않을 수 있다.


  • April Story (1998)

    평점: 4 새로운 시작의 설렘과 혼란. 근데 러닝타임에 비해 중간에 고전영화 상영장면이 왜 이렇게 길지? 4월은 다들 뻘짓하며 보낸다는 뜻인가