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08/28/2023
RecRec: Algorithmic Recourse for Recommender Systems
Recommender systems play an essential role in the choices people make in...
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11/27/2022
RecXplainer: Post-Hoc Attribute-Based Explanations for Recommender Systems
Recommender systems are ubiquitous in most of our interactions in the cu...
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07/12/2022
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence
Explainable artificial intelligence (XAI) methods lack ground truth. In ...
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06/14/2021
Pitfalls of Explainable ML: An Industry Perspective
As machine learning (ML) systems take a more prominent and central role ...
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06/14/2021
Counterfactual Explanations for Machine Learning: Challenges Revisited
Counterfactual explanations (CFEs) are an emerging technique under the u...
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06/07/2021
Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
Explainable machine learning (ML) has gained traction in recent years du...
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02/05/2021
Removing biased data to improve fairness and accuracy
Machine learning systems are often trained using data collected from his...
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11/26/2020
ShapeFlow: Dynamic Shape Interpreter for TensorFlow
We present ShapeFlow, a dynamic abstract interpreter for TensorFlow whic...
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11/26/2020
Debug-Localize-Repair: A Symbiotic Construction for Heap Manipulations
We present Wolverine, an integrated Debug-Localize-Repair environment fo...
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10/20/2020
Counterfactual Explanations for Machine Learning: A Review
Machine learning plays a role in many deployed decision systems, often i...
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07/16/2020
Facets of Fairness in Search and Recommendation
Several recent works have highlighted how search and recommender systems...
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01/22/2020
