Challenges in benchmarking stream learning algorithms with real-world data
VMA Souza, DM dos Reis, AG Maletzke… - Data Mining and …, 2020 - Springer
Streaming data are increasingly present in real-world applications such as sensor
measurements, satellite data feed, stock market, and financial data. The main characteristics …
measurements, satellite data feed, stock market, and financial data. The main characteristics …
Machine learning techniques to characterize functional traits of plankton from image data
Plankton imaging systems supported by automated classification and analysis have
improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of …
improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of …
The augmented social scientist: Using sequential transfer learning to annotate millions of texts with human-level accuracy
The last decade witnessed a spectacular rise in the volume of available textual data. With
this new abundance came the question of how to analyze it. In the social sciences, scholars …
this new abundance came the question of how to analyze it. In the social sciences, scholars …
Automatic plankton quantification using deep features
P González, A Castaño, EE Peacock… - Journal of Plankton …, 2019 - academic.oup.com
The study of marine plankton data is vital to monitor the health of the world's oceans. In
recent decades, automatic plankton recognition systems have proved useful to address the …
recent decades, automatic plankton recognition systems have proved useful to address the …
Political discussion is abundant in non-political subreddits (and less toxic)
Research on online political communication has primarily focused on content in explicitly
political spaces. In this work, we set out to determine the amount of political talk missed …
political spaces. In this work, we set out to determine the amount of political talk missed …
MorphoCluster: efficient annotation of plankton images by clustering
In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate
annotation of large image data sets. While already having surpassed the annotation rate of …
annotation of large image data sets. While already having surpassed the annotation rate of …
QuaPy: A Python-based framework for quantification
QuaPy is an open-source framework for performing quantification (aka supervised
prevalence estimation), written in Python. Quantification is the task of training quantifiers via …
prevalence estimation), written in Python. Quantification is the task of training quantifiers via …
Measuring fairness under unawareness of sensitive attributes: A quantification-based approach
Algorithms and models are increasingly deployed to inform decisions about people,
inevitably affecting their lives. As a consequence, those in charge of developing these …
inevitably affecting their lives. As a consequence, those in charge of developing these …
Plankton classification with high-throughput submersible holographic microscopy and transfer learning
Background Plankton are foundational to marine food webs and an important feature for
characterizing ocean health. Recent developments in quantitative imaging devices provide …
characterizing ocean health. Recent developments in quantitative imaging devices provide …
An improved differential evolution algorithm for quantifying fraudulent transactions
Identification of fraudulent credit card transactions is a complex problem mainly due to the
following factors: 1) The relative behavior of customers and fraudsters may alter over time. 2) …
following factors: 1) The relative behavior of customers and fraudsters may alter over time. 2) …