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Found 9 papers, 2 papers with code
CAMP: A Context-Aware Cricket Players Performance Metric
We propose Context-Aware Metric of player Performance, CAMP, to quantify individual players' contributions toward a cricket match outcome.
Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers
In this paper, we analyze the effect on fairness in the context of graph data (node attributes) imputation using different embedding and neural network methods.
Efficient Approximate Kernel Based Spike Sequence Classification
More specifically, we improve the quality of the approximate kernel using domain knowledge (computed using information gain) and efficient preprocessing (using minimizers computation) to classify coronavirus spike protein sequences corresponding to different variants (e. g., Alpha, Beta, Gamma).
Effective and scalable clustering of SARS-CoV-2 sequences
Using a $k$-mer based feature vector generation and efficient feature selection methods, our approach is effective in identifying variants, as well as being efficient and scalable to millions of sequences.
Fair Allocation Based Soft Load Shedding
However, these solutions are not fair in terms of electricity distribution.
Effect of Analysis Window and Feature Selection on Classification of Hand Movements Using EMG Signal
In this paper, we investigate the effect of the analysis window and feature selection on classification accuracy of different hand and wrist movements using time-domain features.
Short-Term Load Forecasting Using AMI Data
A prominent feature of \textsc{fmf} is that it works at any level of user-specified granularity, both in the temporal (from a single hour to days) and spatial dimensions (a single household to groups of consumers).
Predicting Attributes of Nodes Using Network Structure
Predicting node attributes in such graphs is an important problem with applications in many domains like recommendation systems, privacy preservation, and targeted advertisement.
Efficient Data Analytics on Augmented Similarity Triplets
Data analysis require a pairwise proximity measure over objects.
