The Abacus.AI team has published two papers to appear at the Conference on Neural Information Processing Systems (NeurIPS) 2022. NeurIPS is a top machine learning conference held every December. Abacus.AI is also planning a social event during NeurIPS – stay tuned for…
In our previous post, we presented an introduction to Seq2Seq models – models that take a sequence as an input and produce a sequence for their output. Back in 2014, they revolutionized the field of Natural Language Processing (NLP), especially in translation…
When reading about Machine Learning, the majority of the material you’ve encountered is likely concerned with classification problems. You have a certain input, and the ML model tries to figure out the features of that input. For example, a classification model can decide…
Anyone who’s worked in a manufacturing space can tell you that one of the most significant challenges they face is managing supply chains of the materials and speciality items used to fabricate products. Without clear foresight into demand, how, when and from where…
E-commerce is the new normal for many consumers, never more so than in these times of quarantine and social distancing. As an alternative for the traditional brick-and-mortar storefront, online purchasing has spent the last couple decades transforming the retail…
We open-sourced our debiasing module a few weeks ago.
In this post, we give an introduction to bias in computer vision models, we discuss our new research on debiasing models, and we show how you can debias your own model with our open-source code.
The use of facial…
Most of the machine learning applications you’ve likely heard about are concerned with processing data such as images or databases – their key characteristic being that they can be “taken in” by a learning model all at once. They don’t have any temporal…
Neural architecture search (NAS) is a popular area of machine learning, with the goal of automating the development of the best neural network for a given dataset. Since 2017, hundreds of NAS algorithms have been proposed, and with the recent release of two NAS benchmark…
In this post, we give an introduction to bias in machine learning, and we discuss our new research for debiasing pretrained neural networks (i.e., post-hoc debiasing). ArXiv paper: https://arxiv.org/abs/2006.08564 Source code…