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 ? 🤷‍♀️ Why not ! 🙆‍♀️

Reinforced Data Sampling

Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)

This file covers all concepts of R language..

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.

Generating realistic test data or simulating load with authentic, dynamic data using the Gatling framework and JavaFaker

Adaptive data sampling and transmission in a wireless sensor node as a function of energy reserves

BiBiER: A Bilingual Bimodal Emotion Recognition Method with Improved Generalization through Data Augmentation

Some nlp utils file I write to reuse

Process of data preparaton in R.

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.

Code and Data for paper: Variation across Scales: Measurement Fidelity under Twitter Data Sampling (ICWSM '20)

This project demonstrates data sampling techniques in Snowflake. It covers loading datasets from S3, performing RANDOM and SYSTEM sampling methods to extract subsets, validating sampled data, and optimizing analysis on datasets.

This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.

A Semi-Supervised Multimodal Framework for Multitask Emotion and Personality Traits Recognition Using Cross-Domain Learning

A method for sampling a balanced dataset from biased signals by leveraging statistical distributions derived from the data.