In this blog post, we discuss Abacus.AI’s NeurIPS 2022 paper on recommender systems.Paper: https://arxiv.org/abs/2206.11886Code: https://github.com/naszilla/reczilla1 min video: https://www.youtube.com/watch?v=Eu8G3oNzcvU5 min video…
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…
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…
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…
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…
Like many other Machine Learning concepts, meta-learning is an approach akin to what human beings are already used to doing. Meta-learning simply means “learning to learn.” Whenever we learn any new skill there is some prior experience we can relate to, which makes the…
Pattern recognition is a crucial aspect of modern data analytics. These patterns can be studied to better understand the underlying structure of data and monitor behavior over time. However, there are often rare items or observations that seem to differ significantly from…