research
∙
06/12/2020
Task-similarity Aware Meta-learning through Nonparametric Kernel Regression
Meta-learning refers to the process of abstracting a learning rule for a...
share
research
∙
05/08/2020
On Training and Evaluation of Neural Network Approaches for Model Predictive Control
The contribution of this paper is a framework for training and evaluatio...
research
∙
05/07/2020
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University
We provide a predictive analysis of the spread of COVID-19, also known a...
research
∙
03/29/2020
High-dimensional Neural Feature using Rectified Linear Unit and Random Matrix Instance
We design a ReLU-based multilayer neural network to generate a rich high...
research
∙
11/26/2019
Learning sparse linear dynamic networks in a hyper-parameter free setting
We address the issue of estimating the topology and dynamics of sparse l...
research
∙
11/26/2019
Recursive Prediction of Graph Signals with Incoming Nodes
Kernel and linear regression have been recently explored in the predicti...
research
∙
11/06/2018
Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise
In presence of sparse noise we propose kernel regression for predicting ...
research
∙
11/05/2018
Supervised Linear Regression for Graph Learning from Graph Signals
We propose a supervised learning approach for predicting an underlying g...
research
∙
03/15/2018
Gaussian Processes Over Graphs
We propose Gaussian processes for signals over graphs (GPG) using the ap...
research
∙
03/12/2018
Multi-kernel Regression For Graph Signal Processing
We develop a multi-kernel based regression method for graph signal proce...
research
∙
03/12/2018
Extreme Learning Machine for Graph Signal Processing
In this article, we improve extreme learning machines for regression tas...
research
∙
03/12/2018
R3Net: Random Weights, Rectifier Linear Units and Robustness for Artificial Neural Network
We consider a neural network architecture with randomized features, a si...
research
∙
12/12/2017
Learning Sparse Graphs for Prediction and Filtering of Multivariate Data Processes
We address the problem of prediction and filtering of multivariate data ...
research
∙
08/29/2017
