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1 code implementation • 7 Sep 2021 • Manuel Madeira, Renato Negrinho, João Xavier, Pedro M. Q. Aguiar

First-order methods for stochastic optimization have undeniable relevance, in part due to their pivotal role in machine learning.

1 code implementation • 4 Aug 2021 • André F. T. Martins, Marcos Treviso, António Farinhas, Pedro M. Q. Aguiar, Mário A. T. Figueiredo, Mathieu Blondel, Vlad Niculae

When $\Omega$ is a Tsallis negentropy with parameter $\alpha$, we obtain "deformed exponential families," which include $\alpha$-entmax and sparsemax ($\alpha$ = 2) as particular cases.

no code implementations • 7 Apr 2021 • António Farinhas, André F. T. Martins, Pedro M. Q. Aguiar

Visual attention mechanisms are a key component of neural network models for computer vision.

2 code implementations • NeurIPS 2020 • André F. T. Martins, António Farinhas, Marcos Treviso, Vlad Niculae, Pedro M. Q. Aguiar, Mário A. T. Figueiredo

Exponential families are widely used in machine learning; they include many distributions in continuous and discrete domains (e. g., Gaussian, Dirichlet, Poisson, and categorical distributions via the softmax transformation).

Ranked #20 on Visual Question Answering on VQA v2 test-dev

1 code implementation • 27 Dec 2019 • Lourenço V. Pato, Renato Negrinho, Pedro M. Q. Aguiar

In this setting, we use a bidirectional RNN with attention for contextual rescoring and introduce a training target that uses the IoU with ground truth to maximize AP for the given set of detections.

1 code implementation • 8 May 2013 • João F. C. Mota, João M. F. Xavier, Pedro M. Q. Aguiar, Markus Püschel

Our contribution is a communication-efficient distributed algorithm that finds a vector $x^\star$ minimizing the sum of all the functions.

Optimization and Control Information Theory Information Theory

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