activity
20182022
most citedRandom Vector Functional Link Neural Network based Ensemble Deep Learning

25 citations · 33 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20228 cited

Unified Discrete Diffusion for Simultaneous Vision-Language Generation

Minghui Hu, Chuanxia Zheng, Heliang Zheng +5

The recently developed discrete diffusion models perform extraordinarily well in the text-to-image task, showing significant promise for handling the multi-modality signals. In thi…

cs.LG2022

Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification

Qiushi Shi, Ponnuthurai Nagaratnam Suganthan, Rakesh Katuwal

In this paper, we first introduce batch normalization to the edRVFL network. This re-normalization method can help the network avoid divergence of the hidden features. Then we prop…

cs.NE2021

Large Scale Global Optimization Algorithms for IoT Networks: A Comparative Study

Sotirios K. Goudos, Achilles D. Boursianis, Ali Wagdy Mohamed +4

The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine commun…

cs.CV2019

Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification

Rakesh Katuwal, P. N. Suganthan

Extreme learning machine (ELM), which can be viewed as a variant of Random Vector Functional Link (RVFL) network without the input-output direct connections, has been extensively u…

cs.CV201925 cited

Random Vector Functional Link Neural Network based Ensemble Deep Learning

Rakesh Katuwal, P. N. Suganthan, M. Tanveer

In this paper, we propose a deep learning framework based on randomized neural network. In particular, inspired by the principles of Random Vector Functional Link (RVFL) network, w…

cs.LG2018

Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces

Rakesh Katuwal, P. N. Suganthan

Both neural networks and decision trees are popular machine learning methods and are widely used to solve problems from diverse domains. These two classifiers are commonly used bas…