activity
20182022
most citedScalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ML2022

Probabilistic Model Incorporating Auxiliary Covariates to Control FDR

Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva +2

Controlling False Discovery Rate (FDR) while leveraging the side information of multiple hypothesis testing is an emerging research topic in modern data science. Existing methods r…

cs.CV2022

Leveraging Unlabeled Data for Sketch-based Understanding

Javier Morales, Nils Murrugarra-Llerena, Jose M. Saavedra

Sketch-based understanding is a critical component of human cognitive learning and is a primitive communication means between humans. This topic has recently attracted the interest…

cs.CV2021★ 1 cited

Scalable Visual Attribute Extraction through Hidden Layers of a Residual ConvNet

Andres Baloian, Nils Murrugarra-Llerena, Jose M. Saavedra

Visual attributes play an essential role in real applications based on image retrieval. For instance, the extraction of attributes from images allows an eCommerce search engine to…

stat.ML2021

NeurT-FDR: Controlling FDR by Incorporating Feature Hierarchy

Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva +2

Controlling false discovery rate (FDR) while leveraging the side information of multiple hypothesis testing is an emerging research topic in modern data science. Existing methods r…

cs.CV2018

Image Retrieval with Mixed Initiative and Multimodal Feedback

Nils Murrugarra-Llerena, Adriana Kovashka

How would you search for a unique, fashionable shoe that a friend wore and you want to buy, but you didn't take a picture? Existing approaches propose interactive image search as a…