90 citations · 135 across the 24 of their papers we have counts for
5 papers · 1 filter
ISEE.U: Distributed online active target localization with unpredictable targets
Miguel Vasques, Claudia Soares, João Gomes
This paper addresses target localization with an online active learning algorithm defined by distributed, simple and fast computations at each node, with no parameters to tune and…
Ranking with Confidence for Large Scale Comparison Data
Filipa Valdeira, Cláudia Soares
In this work, we leverage a generative data model considering comparison noise to develop a fast, precise, and informative ranking algorithm from pairwise comparisons that produces…
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…
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…