분류 전체보기148 [2023-2] 김동한 - Forecasting at scale https://peerj.com/preprints/3190.pdf Forecasting at Scale Facebook의 prophet 논문 리뷰 1. Abstract ● 예측(forecasting)은 데이터 사이언스에서 중요한 업무중 하나 ● 중요성에도 불구하고, 다양한 분야의 시계열 분야가 존재하고, 시계열 분석 전문가가 희귀함 ● 목적 : 해석이 가능한 parameter(모수), domain지식이 있는 사람은 직관적으로 조절가능하게 하는 모형(시계열 분석에 대한 전문성이 떨어지더라도) 2. Introduction 문제점 ● 완전한 자동예측 기술은 flexibility가 떨어져서, tuning하기 어렵고, 적절한 가정을 포함하기 힘듦 ● 도메인 지식이 깊은 전문가가 시계열에 대한 이해가 떨어지는 경우.. 2024. 1. 2. [2023-2] 현시은 - 3D image reconstruction from 2D CT slices(3DTV-CON2014) 원본 논문 링크 : https://ieeexplore.ieee.org/document/6874742 3D image reconstruction from 2D CT slicesIn this paper, a 3D reconstruction algorithm using CT slices of human pelvis is presented. We propose the method for 3D image reconstruction that is based on a combination of the SURF (Speeded-Up Robust Features) descriptor and SSD (Sum of Squared Differenieeexplore.ieee.orgAbstract이 논문에서는 정확한 인체 골반의.. 2024. 1. 2. [2023-2] 황재연 - Efficient Estimation of Word Representations inVector Space https://arxiv.org/abs/1301.3781 Efficient Estimation of Word Representations in Vector Space We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best per arxiv.org Abstract 단어의 연속 벡터를 표현하기 위한 새로운 2가지 모델.. 2023. 12. 3. [2023-2] 전상완 - Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks All machine learning algorithms use a loss, cost, utility or reward function to encode the learning objective and oversee the learning process. This function that supervises learning is a frequently unrecognized hyperparameter that determines how incorrect arxiv.org 개념 설명 더보기 .. 2023. 12. 2. 이전 1 ··· 31 32 33 34 35 36 37 다음
