applicable models
discriminative
Models that learn decision boundaries directly
12 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Contrastive Explanation Method | Algorithmic | Architecture/neural Networks Paradigm/discriminative +4 | Any | The Contrastive Explanation Method (CEM) explains model decisions by generating contrastive examples that reveal what... | ||
| Out-of-Distribution Detector for Neural Networks | Algorithmic | Architecture/neural Networks Paradigm/discriminative +3 | Any | ODIN (Out-of-Distribution Detector for Neural Networks) identifies when a neural network encounters inputs significantly... | ||
| Adversarial Debiasing | Algorithmic | Architecture/neural Networks Paradigm/discriminative +4 | Any | Adversarial debiasing reduces bias by training models using a competitive adversarial setup, similar to Generative... | ||
| Homomorphic Encryption | Algorithmic | Architecture/linear Models Architecture/neural Networks/feedforward +4 | Any | Homomorphic encryption allows computation on encrypted data without decrypting it first, producing encrypted results... | ||
| Temperature Scaling | Algorithmic | Architecture/neural Networks Paradigm/discriminative +3 | Any | Temperature scaling adjusts a model's confidence by applying a single parameter (temperature) to its predictions. When a... | ||
| Feature Attribution with Integrated Gradients in NLP | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +4 | Text | Applies Integrated Gradients to natural language processing models to attribute prediction importance to individual... | ||
| Fair Adversarial Networks | Algorithmic | Architecture/neural Networks Paradigm/discriminative +6 | Any | An in-processing fairness technique that employs adversarial training with dual neural networks to learn fair... | ||
| Prejudice Remover Regulariser | Algorithmic | Architecture/linear Models/logistic Architecture/probabilistic +5 | Tabular | An in-processing fairness technique that adds a fairness penalty to machine learning models to reduce bias against... | ||
| Exponentiated Gradient Reduction | Algorithmic | Architecture/model Agnostic Paradigm/discriminative +5 | Any | An in-processing fairness technique based on Agarwal et al.'s reductions approach that transforms fair classification... | ||
| Multi-Accuracy Boosting | Algorithmic | Architecture/ensemble Paradigm/discriminative +3 | Any | An in-processing fairness technique that employs boosting algorithms to improve accuracy uniformly across demographic... | ||
| Equalised Odds Post-Processing | Algorithmic | Architecture/model Agnostic Paradigm/discriminative +3 | Any | A post-processing fairness technique based on Hardt et al.'s seminal work that adjusts classification thresholds after... | ||
| Threshold Optimiser | Algorithmic | Architecture/model Agnostic Paradigm/discriminative +3 | Any | Threshold Optimiser adjusts decision thresholds for different demographic groups after model training to satisfy... |
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