Practicing Trustworthy Machine Learning

Index

Symbols

• 8-bit precision formats, Quantized ML

A

• additive models
  • GA2Ms (generalized additive models plus interactions), Generalized additive models plus interactions
  • GAM (generalized additive model), Generalized additive models
• adversarial bias mitigation, Adversarial bias mitigation
• adversarial robustness methods, Evaluating Robustness, Adversarial Robustness
  • attack examples, creating, Creating Adversarial Examples-Creating Adversarial Examples
  • computer vision, HopSkipJump attack, The HopSkipJump attack on ImageNet-The HopSkipJump attack on ImageNet
  • targeted attacks, Evaluating Robustness
  • untargeted attacks, Evaluating Robustness
• adversarial training, robustness and, Improving Robustness
• adversaries, privacy and, Adversarial success
• AIID (AI Incident Database), AI Incident Database
• aleatoric uncertainty, Aleatoric uncertainty
• algorithms, quantum computing and, Quantum Machine Learning
• Among Us game, Unity and Unreal Environments
• anomalies, MLOps and trustworthiness, Anomaly detection
• anthropomorphizing ML system, Shallow Human-AI Comparison Antipattern
• antipatterns
  • human-AI comparison antipatterns, Shallow Human-AI Comparison Antipattern
  • hyperbolic or just plain wrong antipattern, Hyperbolic or Just Plain Wrong Antipattern
  • uncritical PR piece antipattern, Uncritical PR Piece Antipattern-Uncritical PR Piece Antipattern
• Apple CSAM (Child Sexual Abuse Material), Case 1: Apple’s CSAM
• application-level evaluation, Evaluating the Usefulness of Interpretation or Explanation Methods
• assessment stages
  • data collection ...