Search Results for author:
Found 11 papers, 3 papers with code
AIRCADE: an Anechoic and IR Convolution-based Auralization Data-compilation Ensemble
In this paper, we introduce a data-compilation ensemble, primarily intended to serve as a resource for researchers in the field of dereverberation, particularly for data-driven approaches.
ESSYS* Sharing #UC: An Emotion-driven Audiovisual Installation
We present ESSYS* Sharing #UC, an audiovisual installation artwork that reflects upon the emotional context related to the university and the city of Coimbra, based on the data shared about them on Twitter.
Optimal Decision Diagrams for Classification
Decision diagrams for classification have some notable advantages over decision trees, as their internal connections can be determined at training time and their width is not bound to grow exponentially with their depth.
Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm
We also compared our results with a control method based on the standard machine learning pipeline (pre-processing, feature extraction, classifier training, and post-processing), where the control marginally outperformed our approach by validating 35% of the patients.
Launchers and Targets in Social Networks
On a different direction, using the second index, the strong target members should characterize relevant consumers of information in the network, which may include fake news' regular collectors.
Social and Information Networks 68R10, 90B18
A Pig, an Angel and a Cactus Walk Into a Blender: A Descriptive Approach to Visual Blending
A descriptive approach for automatic generation of visual blends is presented.
Beyond the Shortest Path : Unsupervised Domain Adaptation by Sampling Subspaces Along the Spline Flow
In this case, the source/target domains are represented in the form of subspaces, which are treated as points on the Grassmann manifold.
Fast Training of Pose Detectors in the Fourier Domain
In many datasets, the samples are related by a known image transformation, such as rotation, or a repeatable non-rigid deformation.
Non-Parametric Bayesian Constrained Local Models
This work presents a novel non-parametric Bayesian formulation for aligning faces in unseen images.
High-Speed Tracking with Kernelized Correlation Filters
Interestingly, for linear regression our formulation is equivalent to a correlation filter, used by some of the fastest competitive trackers.
Rolling Riemannian Manifolds to Solve the Multi-class Classification Problem
In the past few years there has been a growing interest on geometric frameworks to learn supervised classification models on Riemannian manifolds [31, 27].
