AI Explainability 360: Impact and Design
- 2022
- IAAI 2022
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45 results for Michael Hind
AI Explainability 360 Toolkit
- Vijay Arya
- Rachel Bellamy
- et al.
- 2021
- CODS-COMAD 2021
Which pointer analysis should I use?
- Michael Hind
- Anthony Pioli
- 2000
- ISSTA 2000
Experiences with improving the transparency of AI models and services
- Michael Hind
- Stephanie Houde
- et al.
- 2020
- CHI EA 2020
Promoting Distributed Trust in Machine Learning and Computational Simulation
- Nelson Bore
- Ravi Kiran Raman
- et al.
- 2019
- ICBC 2019
Constructing and Compressing Frames in Blockchain-based Verifiable Multi-party Computation
- Ravi Kiran Raman
- Kush R. Varshney
- et al.
- 2019
- ICASSP 2019
TED: Teaching AI to explain its decisions
- Michael Hind
- Dennis Wei
- et al.
- 2019
- AIES 2019
A loop correlation technique to improve performance auditing
- Jeremy Lau
- Matthew Arnold
- et al.
- 2007
- PACT 2007
Using HPM-sampling to drive dynamic compilation
- Dries Buytaert
- Andy Georges
- et al.
- 2007
- OOPSLA 2007
Dynamic compilation: The benefits of early investing
- Prasad Kulkarni
- Matthew Arnold
- et al.
- 2007
- VEe 2007