A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Microarchitectural exploitation and other hardware attacks.
State-of-the-art neural cardinality estimators for join queries
TIP2022 Adaptive Boosting (AdaBoost) for Domain Adaptation ? :woman_shrugging: Why not ! 🙆♀️
Generating realistic test data or simulating load with authentic, dynamic data using the Gatling framework and JavaFaker
This file covers all concepts of R language..
#大语言模型#BiBiER: A Bilingual Bimodal Emotion Recognition Method with Improved Generalization through Data Augmentation
This project aims to analyze the citation network of arXiv papers. We use Python to clean the data and create a Neo4j network to visualize and analyze the citation relationships between arXiv papers.
Adaptive data sampling and transmission in a wireless sensor node as a function of energy reserves
#计算机科学#Here is Task 5: Credit card fraud detection using machine learning, for my data science internship with Codsoft
A Python package for flexible subset selection for data visualization.
Process of data preparaton in R.
Code and Data for paper: Variation across Scales: Measurement Fidelity under Twitter Data Sampling (ICWSM '20)
#自然语言处理#Some nlp utils file I write to reuse
A method for sampling a balanced dataset from biased signals by leveraging statistical distributions derived from the data.
#计算机科学#Here is Task 5: Credit card fraud detection using machine learning, for my data science internship with Codsoft
This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.