Search Results for author: Juan Lavista Ferres

Found 14 papers, 4 papers with code

BankNote-Net: Open dataset for assistive universal currency recognition

1 code implementation7 Apr 2022 Felipe Oviedo, Srinivas Vinnakota, Eugene Seleznev, Hemant Malhotra, Saqib Shaikh, Juan Lavista Ferres

This last task, the recognition of banknotes from different denominations, has been addressed by the use of computer vision models for image recognition.

Contrastive Learning Few-Shot Learning +1

An Artificial Intelligence Dataset for Solar Energy Locations in India

1 code implementation31 Jan 2022 Anthony Ortiz, Dhaval Negandhi, Sagar R Mysorekar, Joseph Kiesecker, Shivaprakash K Nagaraju, Caleb Robinson, Priyal Bhatia, Aditi Khurana, Jane Wang, Felipe Oviedo, Juan Lavista Ferres

Using this dataset, we measure the solar footprint across India and quantified the degree of landcover modification associated with the development of PV infrastructure.

Interpretable and Explainable Machine Learning for Materials Science and Chemistry

no code implementations1 Nov 2021 Felipe Oviedo, Juan Lavista Ferres, Tonio Buonassisi, Keith Butler

While the uptake of data-driven approaches for materials science and chemistry is at an exciting, early stage, to realise the true potential of machine learning models for successful scientific discovery, they must have qualities beyond purely predictive power.

BIG-bench Machine Learning Interpretable Machine Learning

An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises

no code implementations15 Jun 2021 Mayana Pereira, Meghana Kshirsagar, Sumit Mukherjee, Rahul Dodhia, Juan Lavista Ferres

Diferentially private (DP) synthetic datasets are a powerful approach for training machine learning models while respecting the privacy of individual data providers.

Fairness Synthetic Data Generation

Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary

no code implementations18 Jan 2021 Jean-Francois Rajotte, Sumit Mukherjee, Caleb Robinson, Anthony Ortiz, Christopher West, Juan Lavista Ferres, Raymond T Ng

We show that by using the FELICIA mechanism, a data owner with limited image samples can generate high-quality synthetic images with high utility while neither data owners has to provide access to its data.

Federated Learning Lesion Classification +1

MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models

no code implementations11 Sep 2020 Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan Lavista Ferres

In this work, we propose the first formal framework for membership privacy estimation in generative models.

privGAN: Protecting GANs from membership inference attacks at low cost

1 code implementation31 Dec 2019 Sumit Mukherjee, Yixi Xu, Anusua Trivedi, Juan Lavista Ferres

It has been shown that such synthetic data can be used for a variety of downstream tasks such as training classifiers that would otherwise require the original dataset to be shared.

Privacy Preserving

NonSTOP: A NonSTationary Online Prediction Method for Time Series

no code implementations8 Nov 2016 Christopher Xie, Avleen Bijral, Juan Lavista Ferres

Moreover, since these transformations are usually unknown, we employ the learning with experts setting to develop a fully online method (NonSTOP-NonSTationary Online Prediction) for predicting nonstationary time series.

Time Series

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