[HTML][HTML] A/B testing: A systematic literature review
A/B testing, also referred to as online controlled experimentation or continuous
experimentation, is a form of hypothesis testing where two variants of a piece of software are …
experimentation, is a form of hypothesis testing where two variants of a piece of software are …
Statistical challenges in online controlled experiments: A review of a/b testing methodology
The rise of internet-based services and products in the late 1990s brought about an
unprecedented opportunity for online businesses to engage in large scale data-driven …
unprecedented opportunity for online businesses to engage in large scale data-driven …
Top challenges from the first practical online controlled experiments summit
Online controlled experiments (OCEs), also known as A/B tests, have become ubiquitous in
evaluating the impact of changes made to software products and services. While the concept …
evaluating the impact of changes made to software products and services. While the concept …
[HTML][HTML] Controlled experimentation in continuous experimentation: Knowledge and challenges
Context: Continuous experimentation and A/B testing is an established industry practice that
has been researched for more than 10 years. Our aim is to synthesize the conducted …
has been researched for more than 10 years. Our aim is to synthesize the conducted …
Optimal Baseline Corrections for Off-Policy Contextual Bandits
The off-policy learning paradigm allows for recommender systems and general ranking
applications to be framed as decision-making problems, where we aim to learn decision …
applications to be framed as decision-making problems, where we aim to learn decision …
[HTML][HTML] Heat dissipation analysis and multi-objective optimization of a permanent magnet synchronous motor using surrogate assisted method
Permanent magnet synchronous motors (PMSM) have been substantially used in electric
vehicles (EVs) due to their advantages such as low loss, large torque, and high power …
vehicles (EVs) due to their advantages such as low loss, large torque, and high power …
Learning Metrics that Maximise Power for Accelerated A/B-Tests
Online controlled experiments are a crucial tool to allow for confident decision-making in
technology companies. A North Star metric is defined (such as long-term revenue or user …
technology companies. A North Star metric is defined (such as long-term revenue or user …
Using machine learning for efficient flexible regression adjustment in economic experiments
This study investigates the optimal use of covariates in reducing variance when analyzing
experimental data. We show that finding the variance-minimizing strategy for making use of …
experimental data. We show that finding the variance-minimizing strategy for making use of …
Multi-Objective Recommendation via Multivariate Policy Learning
Real-world recommender systems often need to balance multiple objectives when deciding
which recommendations to present to users. These include behavioural signals (eg clicks …
which recommendations to present to users. These include behavioural signals (eg clicks …
Systematic look at machine learning algorithms–advantages, disadvantages and practical applications
Abstract Machine Learning (ML) is the study and the usage of the mathematical algorithms
which can improve their performance without the need for human interaction. These …
which can improve their performance without the need for human interaction. These …