Human-in-the-loop machine learning: a state of the art

E Mosqueira-Rey, E Hernández-Pereira… - Artificial Intelligence …, 2023 - Springer
Researchers are defining new types of interactions between humans and machine learning
algorithms generically called human-in-the-loop machine learning. Depending on who is in …

The use of machine learning algorithms in recommender systems: A systematic review

I Portugal, P Alencar, D Cowan - Expert Systems with Applications, 2018 - Elsevier
Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …

Active learning of uniformly accurate interatomic potentials for materials simulation

L Zhang, DY Lin, H Wang, R Car, WE - Physical Review Materials, 2019 - APS
An active learning procedure called deep potential generator (DP-GEN) is proposed for the
construction of accurate and transferable machine learning-based models of the potential …

[图书][B] Recommender systems

CC Aggarwal - 2016 - Springer
“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Current challenges and visions in music recommender systems research

M Schedl, H Zamani, CW Chen, Y Deldjoo… - International Journal of …, 2018 - Springer
Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

Towards conversational recommender systems

K Christakopoulou, F Radlinski… - Proceedings of the 22nd …, 2016 - dl.acm.org
People often ask others for restaurant recommendations as a way to discover new dining
experiences. This makes restaurant recommendation an exciting scenario for recommender …

A survey of active learning in collaborative filtering recommender systems

M Elahi, F Ricci, N Rubens - Computer Science Review, 2016 - Elsevier
In collaborative filtering recommender systems user's preferences are expressed as ratings
for items, and each additional rating extends the knowledge of the system and affects the …

Content-based video recommendation system based on stylistic visual features

Y Deldjoo, M Elahi, P Cremonesi, F Garzotto… - Journal on Data …, 2016 - Springer
This paper investigates the use of automatically extracted visual features of videos in the
context of recommender systems and brings some novel contributions in the domain of …

An introduction to recommender systems

CC Aggarwal, CC Aggarwal - Recommender systems: The textbook, 2016 - Springer
The increasing importance of the Web as a medium for electronic and business transactions
has served as a driving force for the development of recommender systems technology. An …

Sampling from Gaussian process posteriors using stochastic gradient descent

JA Lin, J Antorán, S Padhy, D Janz… - Advances in …, 2023 - proceedings.neurips.cc
Gaussian processes are a powerful framework for quantifying uncertainty and for sequential
decision-making but are limited by the requirement of solving linear systems. In general, this …