Tech Times

LLM Data Mixture Breaks When Training Pools Shift: Causal Inference Offers Fix

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Frontiers

Evaluating XAI techniques under class imbalance using CPRD data

The need for eXplainable Artificial Intelligence (XAI) in healthcare is more critical than ever, especially as regulatory frameworks such as the European Union Artificial Intelligence (EU AI) Act ...
IEEE

Shape Penalized Decision Forests for Imbalanced Data Classification

Abstract: Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional ...
GitHub

A Python Library for Social Event Detection

🔍 Automatically identifying and analyzing events from social media platforms (Twitter, Facebook, etc.) 🌎 Covering diverse event types from natural disasters to viral phenomena 🤖 Leveraging AI to ...
Scientific Research Publishing

Ensemble Machine Learning Models in Financial Distress Prediction: Evidence from China ()

1 Urban Governance and Design Society Hub, Hong Kong University of Science and Technology, Guangzhou, China. 2 School of Accounting and Finance, Faculty of Business, The Hong Kong Polytechnic ...
GitHub

TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification

Official Pytorch implementation of ICML 2022 paper "TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification" This work investigates the phenomenon that imbalance handling algorithms ...