Propostas Submetidas

DEI - FCTUC
Gerado a 2024-11-21 20:54:31 (Europe/Lisbon).
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Titulo Estágio

Reject Inference study

Áreas de especialidade

Engenharia de Software

Engenharia de Software

Local do Estágio

Coimbra

Enquadramento

Fraud is an adversarial problem where criminals routiney try to counteract defenses. Our typical approach is to train models on positive labels from e.g. chargebacks only, ignoring auto-declines. We'd like to diagnose how this affects our model performances, and explore mitigation strategies (e.g. using measures of model confidence to include some auto-declines as positives, ...).

Objetivo

Fraud is an adversarial problem where criminals routiney try to counteract defenses. Our typical approach is to train models on positive labels from e.g. chargebacks only, ignoring auto-declines. We'd like to diagnose how this affects our model performances, and explore mitigation strategies (e.g. using measures of model confidence to include some auto-declines as positives, ...).

Plano de Trabalhos - Semestre 1

"1. Onboarding
2. Literature review: label noise / incomplete labels / model confidence / conformal prediction / etc.
3. Data exploration
4. Define the experimental design
5. Data preparation"

Plano de Trabalhos - Semestre 2

"6. Implementation of selected methods
7. Execution of experiments
8. Reporting"

Condições

Remunerated

Orientador

João Costa
joao.viriato@feedzai.com 📩