Recently, multi-task feature learning algorithms have received increasing attention and they have been successfully applied to many applications involving high-dimensional data. However, they assume that all tasks share a common set of features, which is too restrictive and may not hold in real-...
we propose a Robust Multi-Task Feature Learning algorithm (rMTFL) which simultaneously captures a common set of features among relevant tasks and identifies outlier tasks. Specifically, we decompose the weight (model) matrix for all tasks into two components. We impose the well-known group Lasso ...
(2012). Robust Multi-Task Feature Learning. Proceeding of the 18th ACM SIGKDD conference on knowledge discovery and data mining. Hao, X., Yao, X., Yan, J., Risacher, S. L., Saykin, A. J., Zhang, D., & Shen, L. (2016). Identifying multimodal intermediate phenotypes between ...
SPNv2 is a multi-scale, multi-task CNN which consists of a shared multi-scale feature encoder and multiple prediction heads that perform different tasks on a shared feature output. These tasks are all related to detection and pose estimation of a target spacecraft from an image, such as ...
novel multi-task multi-view sparse learning problem and exploit the cues from multiple views including various types of visual features, such as intensity, color, and edge, where each feature observation can be sparsely represented by a linear combination of atoms from an adaptive feature dictionary...
Multi-task Learning with Coarse Priors forRobust Part-aware Person Re-identif i cationChangxing Ding*, Member, IEEE, Kan Wang*, Pengfei Wang, and Dacheng Tao, Fellow, IEEEAbstract—Part-level representations are important for robust person re-identif i cation (ReID), but in practice feature ...
虽然sklearn中的MultiTaskLasso也是这样的目标函数,并且使用了坐标下降法来求解,但是当目标函数中的损失函数也用L2,1范数时我又懵圈了。 正当我琢磨是不是能把两部分合在一起求解一个L2,1范数时(其实是数... 查看原文 基于L2,1范数的特征选择方法
To make a robust ASR, we introduce a new model us- ing the multi-task learning deep neural networks (MTL-DNN) to... B Huang,D Ke,Z Hao,... 被引量: 6发表: 2015年 Pose-Robust and Discriminative Feature Representation by Multi-task Deep Learning for Multi-view Face Recognition ...
3.3. Multi-task learning for DOA estimation 3.3.1. Standard multi-task learning image-20220407222910382 Two inputs and two outputs: T-F mask network's input: log-magnitude spectrum DOA network's input: the phase spectrum which is multiplied by the predicted mask Two outputs are the estimated ...
A factor analysis model based on multitask learning (MTL) is developed to characterize the FFT-magnitude feature of complex high-resolution range profile (HRRP), motivated by the problem of radar automatic target recognition (RATR). The MTL mechanism makes it possible to appropriately share the ...