Search Results for author:
Found 10 papers, 4 papers with code
CamPro: Camera-based Anti-Facial Recognition
The proliferation of images captured from millions of cameras and the advancement of facial recognition (FR) technology have made the abuse of FR a severe privacy threat.
TERM Model: Tensor Ring Mixture Model for Density Estimation
However, a substantial number of potential tensor permutations can lead to a tensor network with the same structure but varying expressive capabilities.
Low-Rank Multitask Learning based on Tensorized SVMs and LSSVMs
In contrast to previous MTL frameworks, our decision function in the dual induces a weighted kernel function with a task-coupling term characterized by the similarities of the task-specific factors, better revealing the explicit relations across tasks in MTL.
Tensor Regression
Tensors, as high dimensional extensions of vectors, are considered as natural representations of high dimensional data.
Tensorized LSSVMs for Multitask Regression
Multitask learning (MTL) can utilize the relatedness between multiple tasks for performance improvement.
Knowledge-Enhanced Relation Extraction Dataset
Recently, knowledge-enhanced methods leveraging auxiliary knowledge graphs have emerged in relation extraction, surpassing traditional text-based approaches.
Efficient Tensor Contraction via Fast Count Sketch
In this paper, the proposed fast count sketch (FCS) applies multiple shorter Hash functions based CS to the vector form of the input tensor, which is more accurate than TS since the spatial information of the input tensor can be preserved more sufficiently.
Bayesian Low Rank Tensor Ring Model for Image Completion
Low rank tensor ring model is powerful for image completion which recovers missing entries in data acquisition and transformation.
Hyperspectral Image Denoising with Partially Orthogonal Matrix Vector Tensor Factorization
In this paper, we present a HSI restoration method named smooth and robust low rank tensor recovery.
AMP-Net: Denoising based Deep Unfolding for Compressive Image Sensing
By unfolding the iterative optimization algorithm for model-based methods onto networks, deep unfolding methods have the good interpretation of model-based methods and the high speed of classical deep network methods.
