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Found 10 papers, 4 papers with code
Introducing a Family of Synthetic Datasets for Research on Bias in Machine Learning
A significant impediment to progress in research on bias in machine learning (ML) is the availability of relevant datasets.
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis
While state-of-the-art NLP models have been achieving the excellent performance of a wide range of tasks in recent years, important questions are being raised about their robustness and their underlying sensitivity to systematic biases that may exist in their training and test data.
Using Pareto Simulated Annealing to Address Algorithmic Bias in Machine Learning
Algorithmic Bias can be due to bias in the training data or issues with the algorithm itself.
Algorithmic Factors Influencing Bias in Machine Learning
It is fair to say that many of the prominent examples of bias in Machine Learning (ML) arise from bias that is there in the training data.
A Case-Study on the Impact of Dynamic Time Warping in Time Series Regression
It is well understood that Dynamic Time Warping (DTW) is effective in revealing similarities between time series that do not align perfectly.
Indicators of Good Student Performance in Moodle Activity Data
In this paper we conduct an analysis of Moodle activity data focused on identifying early predictors of good student performance.
A Latent Space Analysis of Editor Lifecycles in Wikipedia
Collaborations such as Wikipedia are a key part of the value of the modern Internet.
How Many Topics? Stability Analysis for Topic Models
Topic modeling refers to the task of discovering the underlying thematic structure in a text corpus, where the output is commonly presented as a report of the top terms appearing in each topic.
Adaptive Representations for Tracking Breaking News on Twitter
In this paper we examine the effectiveness of adaptive mechanisms for tracking and summarizing breaking news stories.
Link Prediction with Social Vector Clocks
State-of-the-art link prediction utilizes combinations of complex features derived from network panel data.
