Daniel Alabi
According to our database1,
Daniel Alabi
authored at least 10 papers
between 2016 and 2019.
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Bibliography
2019
The Cost of a Reductions Approach to Private Fair Optimization.
CoRR, 2019
Learning to Prune: Speeding up Repeated Computations.
CoRR, 2019
Learning to Prune: Speeding up Repeated Computations.
Proceedings of the Conference on Learning Theory, 2019
2018
Systems Optimizations for Learning Certifiably Optimal Rule Lists
Proceedings of the SysML Conference 2018, February, 2018
When optimizing nonlinear objectives is no harder than linear objectives.
CoRR, 2018
Unleashing Linear Optimizers for Group-Fair Learning and Optimization.
Proceedings of the Conference On Learning Theory, 2018
2017
Learning Certifiably Optimal Rule Lists for Categorical Data.
J. Mach. Learn. Res., 2017
Learning Certifiably Optimal Rule Lists for Categorical Data.
CoRR, 2017
Learning Certifiably Optimal Rule Lists.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
2016
PFunk-H: approximate query processing using perceptual models.
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2016