1 citations · 1 across the 9 of their papers we have counts for
9 papers
Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
Yinsong Wang, Shahin Shahrampour
The problem of corrupted data, missing features, or missing modalities continues to plague the modern machine learning landscape. To address this issue, a class of regularization m…
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach
Yinsong Wang, Yu Ding, Shahin Shahrampour
Dynamic density estimation is ubiquitous in many applications, including computer vision and signal processing. One popular method to tackle this problem is the "sliding window" ke…
Conditional Deformable Image Registration with Spatially-Variant and Adaptive Regularization
Yinsong Wang, Huaqi Qiu, Chen Qin
Deep learning-based image registration approaches have shown competitive performance and run-time advantages compared to conventional image registration methods. However, existing…
TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality
Yinsong Wang, Shahin Shahrampour
This paper addresses a cross-modal learning framework, where the objective is to enhance the performance of supervised learning in the primary modality using an unlabeled, unpaired…
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation
Yinsong Wang, Yu Ding, Shahin Shahrampour
Real-time density estimation is ubiquitous in many applications, including computer vision and signal processing. Kernel density estimation is arguably one of the most commonly use…
Learning from Non-Random Data in Hilbert Spaces: An Optimal Recovery Perspective
Simon Foucart, Chunyang Liao, Shahin Shahrampour +1
The notion of generalization in classical Statistical Learning is often attached to the postulate that data points are independent and identically distributed (IID) random variable…
Cell Association via Boundary Detection: A Scalable Approach Based on Data-Driven Random Features
Yinsong Wang, Hessam Mahdavifar, Kamran Entesari +1
The problem of cell association is considered for cellular users present in the field. This has become a challenging problem with the deployment of 5G networks which will share the…
ORCCA: Optimal Randomized Canonical Correlation Analysis
Yinsong Wang, Shahin Shahrampour
Random features approach has been widely used for kernel approximation in large-scale machine learning. A number of recent studies have explored data-dependent sampling of features…
Distributed Parameter Estimation in Randomized One-hidden-layer Neural Networks
Yinsong Wang, Shahin Shahrampour
This paper addresses distributed parameter estimation in randomized one-hidden-layer neural networks. A group of agents sequentially receive measurements of an unknown parameter th…