arXiv:1706.05544
공식 코드 · Papers with Code
Rgtsvm: Support Vector Machines on a GPU in R
원문 초록
Rgtsvm provides a fast and flexible support vector machine (SVM) implementation for the R language. The distinguishing feature of Rgtsvm is that support vector classification and support vector regression tasks are implemented on a graphical processing unit (GPU), allowing the libraries to scale to millions of examples with >100-fold improvement in performance over existing implementations. Nevertheless, Rgtsvm retains feature parity and has an interface that is compatible with the popular e1071 SVM package in R. Altogether, Rgtsvm enables large SVM models to be created by both experienced and novice practitioners.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Enhanced network anomaly detection based on deep neural networks
CNTK: Microsoft's Open-Source Deep-Learning Toolkit
Arctic Inference with Shift Parallelism: Fast and Efficient Open Source Inference System for Enterprise AI
Relative Entropy Pathwise Policy Optimization
DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic Segmentation
Scaling Attention to Very Long Sequences in Linear Time with Wavelet-Enhanced Random Spectral Attention (WERSA)
토론
이 논문과 연결된 포럼 글이 아직 없습니다.