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pro vyhledávání: '"Pal, P. R."'
Uncovering new therapeutic uses of existing drugs, drug repositioning offers a fast and cost-effective strategy and holds considerable significance in the realm of drug discovery and development. In recent years, deep learning techniques have emerged
Externí odkaz:
http://arxiv.org/abs/2407.11812
Autor:
Singh, Neeraj Kumar, Pal, Nikhil R.
In this era of artificial intelligence, deep neural networks like Convolutional Neural Networks (CNNs) have emerged as front-runners, often surpassing human capabilities. These deep networks are often perceived as the panacea for all challenges. Unfo
Externí odkaz:
http://arxiv.org/abs/2311.08314
Autor:
Saha, Aytijhya, Pal, Nikhil R.
In this paper, we present a novel embedded feature selection method based on a Multi-layer Perceptron (MLP) network and generalize it for group-feature or sensor selection problems, which can control the level of redundancy among the selected feature
Externí odkaz:
http://arxiv.org/abs/2310.20524
Autor:
Das, Suchismita, Pal, Nikhil R.
When a data set has significant differences in its class and cluster structure, selecting features aiming only at the discrimination of classes would lead to poor clustering performance, and similarly, feature selection aiming only at preserving clus
Externí odkaz:
http://arxiv.org/abs/2307.03902
Autor:
Das, Suchismita, Pal, Nikhil R.
Publikováno v:
Lecture Notes in Computer Science, vol 13756. Springer, Cham, 2022
Recently, several studies have claimed that using class-specific feature subsets provides certain advantages over using a single feature subset for representing the data for a classification problem. Unlike traditional feature selection methods, the
Externí odkaz:
http://arxiv.org/abs/2208.01294
A major limitation of fuzzy or neuro-fuzzy systems is their failure to deal with high-dimensional datasets. This happens primarily due to the use of T-norm, particularly, product or minimum (or a softer version of it). Thus, there are hardly any work
Externí odkaz:
http://arxiv.org/abs/2201.03187
Nonlinear Dimensionality Reduction for Data Visualization: An Unsupervised Fuzzy Rule-based Approach
Autor:
Das, Suchismita, Pal, Nikhil R.
Publikováno v:
IEEE Transactions on Fuzzy Systems ( Volume: 30, Issue: 7, July 2022)
Here, we propose an unsupervised fuzzy rule-based dimensionality reduction method primarily for data visualization. It considers the following important issues relevant to dimensionality reduction-based data visualization: (i) preservation of neighbo
Externí odkaz:
http://arxiv.org/abs/2004.03922
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Autor:
Lin, Chin-Teng, Huang, Kuan-Chih, Liu, Yu-Ting, Lin, Yang-Yin, Hsieh, Tsung-Yu, Pal, Nikhil R., Wu, Shang-Lin, Fang, Chieh-Ning, Cao, Zehong
Kohonen's Adaptive Subspace Self-Organizing Map (ASSOM) learns several subspaces of the data where each subspace represents some invariant characteristics of the data. To deal with the imbalance classification problem, earlier we have proposed a meth
Externí odkaz:
http://arxiv.org/abs/1906.02772