70 citations · 293 across the 70 of their papers we have counts for
7 papers · 1 filter
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values
Haewon Jeong, Hao Wang, Flavio P. Calmon
We investigate the fairness concerns of training a machine learning model using data with missing values. Even though there are a number of fairness intervention methods in the lit…
Measuring Information from Moments
Wael Alghamdi, Flavio P. Calmon
We investigate the problem of representing information measures in terms of the moments of the underlying random variables. First, we derive polynomial approximations of the condit…
-Approximate Coded Matrix Multiplication is Nearly Twice as Efficient as Exact Multiplication
Haewon Jeong, Ateet Devulapalli, Viveck R. Cadambe +1
We study coded distributed matrix multiplication from an approximate recovery viewpoint. We consider a system of computation nodes where each node stores of each multipli…
Polynomial Approximations of Conditional Expectations in Scalar Gaussian Channels
Wael Alghamdi, Flavio P. Calmon
We consider a channel where is a random variable satisfying and is an independent standard normal random variable. We show that the minimum…
Privacy-Preserving Near Neighbor Search via Sparse Coding with Ambiguation
Behrooz Razeghi, Sohrab Ferdowsi, Dimche Kostadinov +2
In this paper, we propose a framework for privacy-preserving approximate near neighbor search via stochastic sparsifying encoding. The core of the framework relies on sparse coding…
Local Differential Privacy Is Equivalent to Contraction of -Divergence
Shahab Asoodeh, Maryam Aliakbarpour, Flavio P. Calmon
We investigate the local differential privacy (LDP) guarantees of a randomized privacy mechanism via its contraction properties. We first show that LDP constraints can be equivalen…
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels
Hao Wang, Rui Gao, Flavio P. Calmon
Machine learning models trained by different optimization algorithms under different data distributions can exhibit distinct generalization behaviors. In this paper, we analyze the…