Lesion-centered 3D mapping of colonoscopy procedures: validation of a hierarchical ensemble pipeline on public benchmark videos
研究通过构建一个四层分级管道，无需全结肠3D重建即可生成以病灶为中心的空间记录，解决了结肠镜检查过程中空间信息丢失的问题。
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Radio Map Construction with Post-Hoc Location Calibration under Quasi-Static Positioning Errors: Joint Estimation, Performance Bounds, and GNSS-Based Evaluation
本文提出一种利用无线电测量数据校准位置标签误差的无线电地图构建框架，通过高斯过程回归联合估计定位误差和无线电传播参数，有效减少系统性空间错配。
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A dictionary learning framework for graphs via filters and optimal transport
We propose a graph dictionary learning (GDL) framework where each graph is represented as a zero-mean Gaussian distribution derived from its filtered Laplacian. Each observed graph is approximated by a barycenter over learned atom graphs, computed under the filter graph distance (fGOT), a graph comparison metric sensitive to global structural properties. The reconstruction error between the observed graph and its barycenter is measured by the surrogate fGOT (sfGOT) distance, a tractable approximation of fGOT that handles graphs without known node correspondence, and is minimized end-to-end via backpropagation. We further provide a novel interpretation of sfGOT through the lens of the Hilbert-Schmidt Independence Criterion, showing that minimizing the sfGOT distance between two graphs is equivalent to maximizing statistical dependence between the spectral embedding of their nodes. Experiments on benchmark datasets demonstrate competitive performance over existing GDL methods on graph clustering and classification tasks.
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Lesion-centered 3D mapping of colonoscopy procedures: validation of a hierarchical ensemble pipeline on public benchmark videos
研究通过构建一个四层分级管道，无需全结肠3D重建即可生成以病灶为中心的空间记录，解决了结肠镜检查过程中空间信息丢失的问题。
0 citationsRead paper
Selecting k Paths with the Minimum Longest Path Length in the Stochastic Semi-Bandit Setting
研究解决在网络中选择k条路径以最小化最长传输时间的问题，提出一种半强盗算法来应对这一在线问题。
0 citationsRead paper
Radio Map Construction with Post-Hoc Location Calibration under Quasi-Static Positioning Errors: Joint Estimation, Performance Bounds, and GNSS-Based Evaluation
本文提出一种利用无线电测量数据校准位置标签误差的无线电地图构建框架，通过高斯过程回归联合估计定位误差和无线电传播参数，有效减少系统性空间错配。
0 citationsRead paper
An Efficient Out-of-Core Tomographic Imaging Framework for Edge Devices
本文提出了一种名为edgeFBP的框架，通过采用混合精度策略加速反投影内核，解决了边缘设备上因计算能力和内存限制而难以进行CT成像的问题。
0 citationsRead paper
A dictionary learning framework for graphs via filters and optimal transport
We propose a graph dictionary learning (GDL) framework where each graph is represented as a zero-mean Gaussian distribution derived from its filtered Laplacian. Each observed graph is approximated by a barycenter over learned atom graphs, computed under the filter graph distance (fGOT), a graph comparison metric sensitive to global structural properties. The reconstruction error between the observed graph and its barycenter is measured by the surrogate fGOT (sfGOT) distance, a tractable approximation of fGOT that handles graphs without known node correspondence, and is minimized end-to-end via backpropagation. We further provide a novel interpretation of sfGOT through the lens of the Hilbert-Schmidt Independence Criterion, showing that minimizing the sfGOT distance between two graphs is equivalent to maximizing statistical dependence between the spectral embedding of their nodes. Experiments on benchmark datasets demonstrate competitive performance over existing GDL methods on graph clustering and classification tasks.
0 citationsRead paper