Author: Parichit
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Extended abstract of our IEEE DSAA24 paper is now available
The extended abstract of our paper, “p-ClustVal: A Novel p-adic Approach for Enhanced Clustering of High-Dimensional scRNASeq Data” is available at IEEE Xplore (https://ieeexplore.ieee.org/document/10722799)
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Enhancing Cluster Discernment in High Dimensional Single Cell RNA Sequencing Data
Excited to share that our recent work on using alternate data representation for enhancing cluster discernment in high dimensional single cell RNA Sequencing data has been accepted at the 11th IEEE International Conference on Data Science & Analytics (DSAA 2024).
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Group Pic
Our group pic. From left, Mehmet, Parichit, Dr. Kurban, Mert, Hasan and Fahrettin. We thought it would be nice to take the picture before some people leave for their parent campus.
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Special Session: Advancing Materials Science with Data Science – IEEE DSAA 2024
We are glad to announce that we are organizing the special session-“Advancing Materials Science Through Data Science:Innovations, Applications and Challenges” at 11th IEEE, International Conference on Data Science & Analytics, 2024. Many thanks to all those who submitted their papers. We will see you all there 🙂 More Info: https://www.dsaa2024-specialsession-data-driven-material-science.com/homepage
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Accepted Paper: Enhancing K-Means with Data-Centric AI
Our paper – “What Data-Centric AI can Do for Kmeans: a Faster, Robust Kmeans-d” has been accepted at the Proceedings of the 41st International Conference on Machine Learning (ICML), Data-Centric Machine Learning Workshop (DMLR), to be held in Vienna, Austria.
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What Data-Centric AI Can Do For kmeans–a Faster, Robust kmeans-d
Parichit Sharma, Hasan Kurban, Mehmet M. Dalkilic – Proceedings of the 41st International Conference on Machine Learning (ICML), Vienna, Austria, Data Centric Machine Learning Research Workshop (DMLR), 2024 (Accepted)
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p-ClustVal–Enhancing Clustering and Valuation with a Novel p-adic Approach in High-Dimensional Genomics Data
Parichit Sharma, Sarthak Mishra, Hasan Kurban, Mehmet M. Dalkilic – International Journal of Data Science and Analytics (under-review)
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Geometric-k-means–An Unbounded, Accurate and Energy-Efficient k-means
Parichit Sharma, Hasan Kurban, Marcin Malec, Oguzhan Kulekci, Mehmet Dalkilic – Machine Learning (under-review)
Kurban Intelligence Lab 