14 citations · 25 across the 7 of their papers we have counts for
8 papers
Decentralized EM to Learn Gaussian Mixtures from Datasets Distributed by Features
Pedro Valdeira, Cláudia Soares, João Xavier
Expectation Maximization (EM) is the standard method to learn Gaussian mixtures. Yet its classic, centralized form is often infeasible, due to privacy concerns and computational an…
Decision Support Models for Predicting and Explaining Airport Passenger Connectivity from Data
Marta Guimaraes, Claudia Soares, Rodrigo Ventura
Predicting if passengers in a connecting flight will lose their connection is paramount for airline profitability. We present novel machine learning-based decision support models f…
Clustering of the Blendshape Facial Model
Stevo Racković, Cláudia Soares, Dušan Jakovetić +2
Digital human animation relies on high-quality 3D models of the human face -- rigs. A face rig must be accurate and, at the same time, fast to compute. One of the most common riggi…
Range and Bearing Data Fusion for Precise Convex Network Localization
Claudia Soares, Filipa Valdeira, Joao Gomes
Hybrid localization in GNSS-challenged environments using measured ranges and angles is becoming increasingly popular, in particular with the advent of multimodal communication sys…
STRONG: Synchronous and asynchronous RObust Network localization, under Non-Gaussian noise
Claudia Soares, João Gomes
Real-world network applications must cope with failing nodes, malicious attacks, or nodes facing corrupted data - data classified as outliers. Our work addresses these concerns in…
Accurate, Interpretable, and Fast Animation: An Iterative, Sparse, and Nonconvex Approach
Stevo Rackovic, Claudia Soares, Dusan Jakovetic +1
Digital human animation relies on high-quality 3D models of the human face: rigs. A face rig must be accurate and, at the same time, fast to compute. One of the most common rigging…