Utility-Fairness Trade-Offs and How to Find Them

no code implementations • 15 Apr 2024 • Sepehr Dehdashtian, Bashir Sadeghi, Vishnu Naresh Boddeti

and 2) How can we numerically quantify these trade-offs from data for a desired prediction task and demographic attribute of interest?

Attribute Fairness +1

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs

no code implementations • 22 Mar 2024 • Sepehr Dehdashtian, Lan Wang, Vishnu Naresh Boddeti

However, owing to the nature of their training process, these models have the potential to 1) propagate or amplify societal biases in the training data and 2) learn to rely on spurious features.

Fairness

On Characterizing the Trade-off in Invariant Representation Learning

1 code implementation • NeurIPS 2021 • Bashir Sadeghi, Sepehr Dehdashtian, Vishnu Boddeti

Solutions to invariant representation learning (IRepL) problems lead to a trade-off between utility and invariance when they are competing.

Attribute Domain Adaptation +2

Deep-Learning Based Blind Recognition of Channel Code Parameters over Candidate Sets under AWGN and Multi-Path Fading Conditions

no code implementations • 16 Sep 2020 • Sepehr Dehdashtian, Matin Hashemi, Saber Salehkaleybar

We consider the problem of recovering channel code parameters over a candidate set by merely analyzing the received encoded signals.