375 citations · 783 across the 14 of their papers we have counts for
16 papers
COCO Denoiser: Using Co-Coercivity for Variance Reduction in Stochastic Convex Optimization
Manuel Madeira, Renato Negrinho, João Xavier +1
First-order methods for stochastic optimization have undeniable relevance, in part due to their pivotal role in machine learning. Variance reduction for these algorithms has become…
Sparse Continuous Distributions and Fenchel-Young Losses
André F. T. Martins, Marcos Treviso, António Farinhas +4
Exponential families are widely used in machine learning, including many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical distr…
Multimodal Continuous Visual Attention Mechanisms
António Farinhas, André F. T. Martins, Pedro M. Q. Aguiar
Visual attention mechanisms are a key component of neural network models for computer vision. By focusing on a discrete set of objects or image regions, these mechanisms identify t…
Sparse and Continuous Attention Mechanisms
André F. T. Martins, António Farinhas, Marcos Treviso +3
Exponential families are widely used in machine learning; they include many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical di…
Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization
Lourenço V. Pato, Renato Negrinho, Pedro M. Q. Aguiar
The majority of current object detectors lack context: class predictions are made independently from other detections. We propose to incorporate context in object detection by post…
Maximizing compression efficiency through block rotation
Rui F. C. Guerreiro, Pedro M. Q. Aguiar
The Discrete Cosine Transform (DCT) is widely used in lossy image and video compression schemes, e.g., JPEG and MPEG. In this paper, we show that the compression efficiency of the…