Tag: Classification

All the articles with the tag "Classification".

• Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets

  Published: 15 May, 2025 |  at  11:06 AM

  

  90.25 🤔

  This paper systematically evaluates machine learning classifiers and imbalance learning techniques on two cybersecurity datasets, revealing that XGB and RF perform robustly, while sampling and ensembling effects vary, emphasizing the need for dataset-specific method selection.

• Always Skip Attention

  Published: 8 May, 2025 |  at  11:06 AM

  

  89.20 🤔

  This paper theoretically demonstrates the ill-conditioning of Self-Attention Blocks in Vision Transformers without skip connections, highlights their role as regularizers, and proposes Token Graying (SVD and DCT) to improve input token conditioning, achieving modest performance gains in supervised and self-supervised tasks.

• Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models

  Published: 16 May, 2025 |  at  11:30 AM

  

  89.11 🤔

  This paper provides a theoretical analysis using Contextual Stochastic Block Models to demonstrate that graph attention mechanisms are beneficial for node classification only when structure noise exceeds feature noise, proposes a multi-layer GAT to achieve perfect classification at lower SNR thresholds, and validates these findings through synthetic and real-world experiments.

• Facets of Disparate Impact: Evaluating Legally Consistent Bias in Machine Learning

  Published: 15 May, 2025 |  at  11:09 AM

  

  89.11 🤔

  This paper introduces the Objective Fairness Index (OFI), a legally grounded metric for evaluating bias in machine learning by comparing marginal benefits across groups, demonstrating its ability to detect algorithmic bias in applications like COMPAS and Folktable's Adult Employment dataset where traditional Disparate Impact fails.

• Large Language Models are Miscalibrated In-Context Learners

  Published: 25 May, 2025 |  at  11:24 AM

  

  88.84 🤔

  本文通过对大型语言模型在低资源场景下的校准问题进行深入分析，揭示上下文学习（ICL）未一致改善校准效果，并提出自集成方法显著提升校准性能（平均降低ECE 43%），同时维持或略提升任务性能。