Rust 1.0–1.5 as of 2015Currently issuing regular releases every six weeks with a train-based release model. Some highlights for Rust 1.0 to 1.5:Nov 23, 2020Nov 23, 2020
Review: The Science of AddictionSpecial TIME Edition — What We Know. What We’re LearningNov 30, 2019Nov 30, 2019
MixNet on Tensorflow Lite구글이 새로운 경량화 네트워크 MixNet를 공개했습니다. 논문 제목 MixNet: Mixed Depthwise Convolutional Kernels에서 알 수 있듯이 Depthwise Convolution이라는 연산을 잘 섞어서(=AutoML)…Jul 29, 20191Jul 29, 20191
Paper#3 Guided Meta-Policy SearchTheir previous work MAML is a computation-intensive meta-learning method.Apr 4, 2019Apr 4, 2019
Paper#2 Online Model Distillation for Efficient Video InferenceThey proposed online distillation mechanism that is motivated by teacher-student architecture. Student network called JITNet is finetuned…Feb 26, 2019Feb 26, 2019
Paper#1 [MVOS-OL] Online Meta Adaptation for Fast Video Object SegmentationThere are two adaptations that update a segmentation network on video in inference time. The first part, meta-learner, updates the base…Feb 25, 2019Feb 25, 2019
Paper#0 [CARN] Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual NetworkCARN connects all the layers densely and achieves comparable results in terms of performance(PSNR) and computation(MAC) on…Feb 24, 2019Feb 24, 2019
[카카오 아레나] 쇼핑몰 상품 카테고리 분류 대회 리뷰 Part 4— 맺음말좋은 결과로 마무리했기 때문에 지금은 행복한 기억처럼 느껴지지만 데이터셋을 지워버려서 시간을 날려먹은 기억, 리더보드의 순위를 확인한다고 매분마다 새로고침하던 것을 떠올리면 마냥 행복하지는 않았던 것 같습니다.Feb 11, 2019Feb 11, 2019
![Paper#1 [MVOS-OL] Online Meta Adaptation for Fast Video Object Segmentation](https://miro.medium.com/v2/resize:fill:160:106/1*A_vzobneOZg5lDDturmJAA.png)
![Paper#1 [MVOS-OL] Online Meta Adaptation for Fast Video Object Segmentation](https://miro.medium.com/v2/resize:fill:320:214/1*A_vzobneOZg5lDDturmJAA.png)
![Paper#0 [CARN] Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network](https://miro.medium.com/v2/resize:fill:160:106/1*1PP8HCgkPrxvkdmLQnbTDQ.png)
![Paper#0 [CARN] Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network](https://miro.medium.com/v2/resize:fill:320:214/1*1PP8HCgkPrxvkdmLQnbTDQ.png)
![[카카오 아레나] 쇼핑몰 상품 카테고리 분류 대회 리뷰 Part 4— 맺음말](https://miro.medium.com/v2/resize:fill:160:106/1*KufIAYVvVZwfyZMc2qu1qA.png)
![[카카오 아레나] 쇼핑몰 상품 카테고리 분류 대회 리뷰 Part 4— 맺음말](https://miro.medium.com/v2/resize:fill:320:214/1*KufIAYVvVZwfyZMc2qu1qA.png)
