Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural Networks

1 code implementation • 29 Nov 2021 • Yuren Sun, Tatiana Midori Maeda, Claudia Solis-Lemus, Daniel Pimentel-Alarcon, Zuzana Burivalova

Using soundscapes from a tropical forest in Borneo and a Convolutional Neural Network model (CNN) created with transfer learning, we investigate i) the minimum viable training data set size for accurate prediction of call types ('sonotypes'), and ii) the extent to which data augmentation can overcome the issue of small training data sets.

Data Augmentation Management +1

GLIMPS: A Greedy Mixed Integer Approach for Super Robust Matched Subspace Detection

no code implementations • 29 Oct 2019 • Md Mahfuzur Rahman, Daniel Pimentel-Alarcon

Due to diverse nature of data acquisition and modern applications, many contemporary problems involve high dimensional datum $\x \in \R^\d$ whose entries often lie in a union of subspaces and the goal is to find out which entries of $\x$ match with a particular subspace $\sU$, classically called \emph {matched subspace detection}.

Mixture Matrix Completion

no code implementations • NeurIPS 2018 • Daniel Pimentel-Alarcon

A more general model assumes that each column of X corresponds to one of several low-rank matrices.

Clustering Matrix Completion +1

Random Consensus Robust PCA

1 code implementation • AISTATS, Electronic Journal of Statistics 2017 • Daniel Pimentel-Alarcon, Robert Nowak

This paper presents r2pca, a random con- sensus method for robust principal compo- nent analysis.