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08/17/2023
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces
As responsible AI gains importance in machine learning algorithms, prope...
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03/01/2023
A Persian Benchmark for Joint Intent Detection and Slot Filling
Natural Language Understanding (NLU) is important in today's technology ...
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02/07/2023
Robustness Implies Fairness in Casual Algorithmic Recourse
Algorithmic recourse aims to disclose the inner workings of the black-bo...
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12/13/2022
On the Relationship Between Explanation and Prediction: A Causal View
Explainability has become a central requirement for the development, dep...
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12/21/2021
On the Adversarial Robustness of Causal Algorithmic Recourse
Algorithmic recourse seeks to provide actionable recommendations for ind...
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10/13/2020
On the Fairness of Causal Algorithmic Recourse
While many recent works have studied the problem of algorithmic fairness...
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10/10/2020
Scaling Guarantees for Nearest Counterfactual Explanations
Counterfactual explanations (CFE) are being widely used to explain algor...
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10/08/2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Machine learning is increasingly used to inform decision-making in sensi...
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06/11/2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Recent work has discussed the limitations of counterfactual explanations...
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02/14/2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions
As machine learning is increasingly used to inform consequential decisio...
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05/27/2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions
Predictive models are being increasingly used to support consequential d...
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12/18/2018
Deep Variational Sufficient Dimensionality Reduction
We consider the problem of sufficient dimensionality reduction (SDR), wh...
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11/07/2018
SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections
Supervised dimensionality reduction strategies have been of great intere...
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11/24/2017
JADE: Joint Autoencoders for Dis-Entanglement
The problem of feature disentanglement has been explored in the literatu...
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09/18/2017
A Summary Of The Kernel Matrix, And How To Learn It Effectively Using Semidefinite Programming
Kernel-based learning algorithms are widely used in machine learning for...
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06/09/2016
