Daniel Alabi

According to our database, Daniel Alabi authored at least 9 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2020

Differentially Private Simple Linear Regression.

Daniel Alabi, Audra McMillan, Jayshree Sarathy, Adam D. Smith, Salil P. Vadhan

CoRR, 2020

2019

The Cost of a Reductions Approach to Private Fair Optimization.

Daniel Alabi

CoRR, 2019

Learning to Prune: Speeding up Repeated Computations.

Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik

Proceedings of the Conference on Learning Theory, 2019

2018

Systems Optimizations for Learning Certifiably Optimal Rule Lists.

Nicholas Larus-Stone, Elaine Angelino, Daniel Alabi, Margo Seltzer, Vassilios Kaxiras, Aditya Saligrama, Cynthia Rudin

Proceedings of the SysML Conference 2018, February, 2018

When optimizing nonlinear objectives is no harder than linear objectives.

Daniel Alabi, Nicole Immorlica, Adam Tauman Kalai

CoRR, 2018

Unleashing Linear Optimizers for Group-Fair Learning and Optimization.

Daniel Alabi, Nicole Immorlica, Adam Kalai

Proceedings of the Conference On Learning Theory, 2018

2017

Learning Certifiably Optimal Rule Lists for Categorical Data.

Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin

J. Mach. Learn. Res., 2017

Learning Certifiably Optimal Rule Lists.

Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin

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.

Daniel Alabi, Eugene Wu

Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2016