72 citations · 77 across the 3 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2020
Oblivious Data for Fairness with Kernels
Steffen Grünewälder, Azadeh Khaleghi
We investigate the problem of algorithmic fairness in the case where sensitive and non-sensitive features are available and one aims to generate new, `oblivious', features that clo…
stat.ML2019
Clustering piecewise stationary processes
Azadeh Khaleghi, Daniil Ryabko
The problem of time-series clustering is considered in the case where each data-point is a sample generated by a piecewise stationary ergodic process. Stationary processes are perh…
stat.ML2013
A consistent clustering-based approach to estimating the number of change-points in highly dependent time-series
Azaden Khaleghi, Daniil Ryabko
The problem of change-point estimation is considered under a general framework where the data are generated by unknown stationary ergodic process distributions. In this context, th…