Yuan Xie

TL;DR: Kiln is a persistent memory design that adopts a nonvolatile cache and aNonvolatile main memory to enable atomic in-place updates without logging or copy-on-write and can achieve 2× performance improvement compared with NVRAM-based persistent memory with write-ahead logging.

TL;DR: Wang et al. as discussed by the authors proposed a more flexible model, namely the Weighted Schatten $p$-Norm Minimization (WSNM), to generalize the nuclear norm minimization to the Schatten Schatten-norm minimization with weights assigned to different singular values, which not only gives better approximation to the original low-rank assumption, but also considers the importance of different rank components.

TL;DR: The proposed method has achieved highly competent objective performance compared to several state-of-the-art multi-view clustering methods and its minimization problem can be efficiently solved with theoretical convergence guarantee and relatively low computational complexity.

TL;DR: The simulation platform in this paper is calibrated using measured results from a fabricated nonvolatile processor and used to explore the design space for a nonVolatile processor with different architectures, different input power sources, and policies for maximizing forward progress.

TL;DR: This paper presents a salient instance segmentation method that produces a saliency mask with distinct object instance labels for an input image, and proposes a multiscale saliency refinement network, which generates high-quality salient region masks and salient object contours.