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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Rohan
About me
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Portfolio item number 1
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publications
BLE beacon based indoor positioning using variance-weighted KNN.
Published in Korean Communication Society, 2018
This work uses variance weighted of RSSI along with KNN to extract user position.
Recommended citation: Rohan Kumar Yadav, Jae-Young Pyun (2018). "BLE beacon based indoor positioning using variance-weighted KNN." Korean Communication Society. http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07565027&language=ko_KR&language=ko_KR#
Geomagnetic Field Based Indoor Landmark Classification Using Deep Learning.
Published in IEEE Access, 2019
This work uses Geomagnetic field to classify landmark in a big indoor environment using LSTM based model.
Recommended citation: Bimal Bhattarai, Rohan Kumar Yadav, Hui-Seon Gang, Jae-Young Pyun (2019). "Geomagnetic Field Based Indoor Landmark Classification Using Deep Learning." IEEE Access. https://ieeexplore.ieee.org/document/8660396
Trusted K Nearest Bayesian Estimation for Indoor Positioning System.
Published in IEEE Access, 2019
This work uses KNN to filter the reference point and bayesian estiamtion to calulate position. Then it is integrated to PDR based positioning using kalmanfilter.
Recommended citation: Rohan Kumar Yadav, Bimal Bhattarai, Hui-Seon Gang, Jae-Young Pyun (2019). "Trusted K Nearest Bayesian Estimation for Indoor Positioning System." IEEE Access. https://ieeexplore.ieee.org/document/8695741
Indoor Space Classification Using Cascaded LSTM.
Published in ICIEA, 2020
This work classifies the space in Indoor Enviromnment iwth RSSI and Geomagnetic Field using cascaded LSTM.
Recommended citation: Rohan Kumar Yadav, Bimal Bhattarai, Lei Jiao, Ole-Christoffer Granmo, and Morten Goodwin (2020). "Indoor Space Classification Using Cascaded LSTM." ICIEA. https://ieeexplore.ieee.org/document/9248347
Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis.
Published in AAAI, 2021
Interpretability in Aspect-Based Sentiment Analysis using Tsetlin Machine.
Recommended citation: Rohan Kumar Yadav, Lei Jiao, Ole-Christoffer Granmo, and Morten Goodwin (2021). "Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis." AAAI. http://academicpages.github.io/files/paper3.pdf
Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling.
Published in International Conference on Machine Learning (ICML 2021), 2021
CUDA version of Tsetlin Machine.
Recommended citation: K. Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan K. Yadav (2021). "Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling." ICML. https://arxiv.org/abs/2009.04861
Positionless Aspect based Sentiment Analysis Using Attention Mechanism.
Published in Knowledge-Based System, 2021
Apsect based sentiment analysis using masking technique to get rid of trainable positional embedding.
Recommended citation: Rohan Kumar Yadav, Lei Jiao, Morten Goodwin and Ole-Christoffer Granmo (2021). "Positionless Aspect based Sentiment Analysis Using Attention Mechanism." Knowledge-Based System. NA
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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