Hussein Mozannar
Hussein Mozannar
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When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming
We provide a method to decide when to display suggestions in AI-assisted programming systems based on the programmer’s feedback. We show that we can avoid displaying a significant fraction of suggestions that would have been rejected.
Hussein Mozannar
,
Gagan Bansal
,
Adam Fourney
,
Eric Horvitz
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Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration
We build new machine learning algorithms that can predict whether a patient is pregnant and whether they will have a high-risk pregnancy. We then integrate these algorithms into a user interface and evaluate it with nurses.
Hussein Mozannar
,
Yuria Utsumi
,
Irene Y Chen
,
Stephanie S Gervasi
,
Michele Ewing
,
Aaron Smith-McLallen
,
David Sontag
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Who Should Predict? Exact Algorithms For Learning to Defer to Humans
We provide algorithms that can provably minimize the learning to defer objective and provide an experimental benchmark to study human-deferral algorithms.
Hussein Mozannar
,
Hunter Lang
,
Dennis Wei
,
Prasanna Sattigeri
,
Subhro Das
,
David Sontag
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Sample Efficient Learning of Predictors that Complement Humans
We characterize theoretically the gain from building ML classifiers that complement humans, show how do this by reducing any multiclass loss to a cost-sensitive loss and create human-label efficient algorithms based on active learning.
Mohammad-Amin Charusaie
,
Hussein Mozannar
,
David Sontag
,
Samira Samadi
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Slides
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Teaching Humans When To Defer to a Classifier via Exemplars
We develop an onboarding stage for teaching users when to rely on AI systems and when not to.
Hussein Mozannar
,
Arvind Satyanarayan
,
David Sontag
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Consistent Estimators for Learning to Defer to an Expert
We develop learning algorithms based on novel surrogate losses that know when to predict and when to defer to a human.
Hussein Mozannar
,
David Sontag
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Fair learning with private demographic data
We build a procedure to learn a fair predictor (e.g. satisfies equalized odds) when the demographic attributes are privatized.
Hussein Mozannar
,
Mesrob Ohannessian
,
Nathan Srebro
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From fair decision making to social equality
The study of fairness in intelligent decision systems has mostly ignored long-term influence on the underlying population. Yet fairness …
Hussein Mouzannar
,
Mesrob I Ohannessian
,
Nathan Srebro
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Neural Arabic Question Answering
We develop learning algorithms based on novel surrogate losses that know when to predict and when to defer to a human.
Hussein Mozannar
,
Karl El Hajal
,
Elie Maamary
,
Hazem Hajj
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Damage Identification in Social Media Posts using Multimodal Deep Learning
Social media has recently become a digital lifeline used to relay information and locate survivors in disaster situations. Currently, …
Hussein Mouzannar
,
Yara Rizk
,
Mariette Awad
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