Vinod Kumar Chauhan

Orcid: 0000-0001-8195-548X

According to our database1, Vinod Kumar Chauhan authored at least 25 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

Legend:

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Bibliography

2024
GTAGCN: Generalized Topology Adaptive Graph Convolutional Networks.
CoRR, 2024

2023
Indic script family and its offline handwriting recognition for characters/digits and words: a comprehensive survey.
Artif. Intell. Rev., December, 2023

Improving Diagnostics with Deep Forest Applied to Electronic Health Records.
Sensors, July, 2023

Real-time large-scale supplier order assignments across two-tiers of a supply chain with penalty and dual-sourcing.
Comput. Ind. Eng., February, 2023

A Brief Review of Hypernetworks in Deep Learning.
CoRR, 2023

Dynamic Inter-treatment Information Sharing for Heterogeneous Treatment Effects Estimation.
CoRR, 2023

Synthesizing Mixed-type Electronic Health Records using Diffusion Models.
CoRR, 2023

Adversarial De-confounding in Individualised Treatment Effects Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A network science approach to identify disruptive elements of an airline.
CoRR, 2022

Exploitation of material consolidation trade-offs in a multi-tier complex supply networks.
CoRR, 2022

Trolley optimisation: An extension of bin packing to load PCB components.
CoRR, 2022

COPER: Continuous Patient State Perceiver.
Proceedings of the IEEE-EMBS International Conference on Biomedical and Health Informatics, 2022

2021
LIBS2ML: A library for scalable second order machine learning algorithms.
Softw. Impacts, 2021

The relationship between nested patterns and the ripple effect in complex supply networks.
Int. J. Prod. Res., 2021

HCR-Net: A deep learning based script independent handwritten character recognition network.
CoRR, 2021

2020
Stochastic trust region inexact Newton method for large-scale machine learning.
Int. J. Mach. Learn. Cybern., 2020

A self controlled RDP approach for feature extraction in online handwriting recognition using deep learning.
Appl. Intell., 2020

2019
SAAGs: Biased stochastic variance reduction methods for large-scale learning.
Appl. Intell., 2019

Problem formulations and solvers in linear SVM: a review.
Artif. Intell. Rev., 2019

2018
SAAGs: Biased Stochastic Variance Reduction Methods.
CoRR, 2018

Faster Algorithms for Large-scale Machine Learning using Simple Sampling Techniques.
CoRR, 2018

Faster learning by reduction of data access time.
Appl. Intell., 2018

2017
Trust Region Levenberg-Marquardt Method for Linear SVM.
Proceedings of the Ninth International Conference on Advances in Pattern Recognition, 2017

Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems.
Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016
Online Support Vector Machine Based on Minimum Euclidean Distance.
Proceedings of International Conference on Computer Vision and Image Processing, 2016


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