A survey of reinforcement learning from human feedback
Reinforcement learning from human feedback (RLHF) is a variant of reinforcement learning
(RL) that learns from human feedback instead of relying on an engineered reward function …
(RL) that learns from human feedback instead of relying on an engineered reward function …
Preference-based online learning with dueling bandits: A survey
In machine learning, the notion of multi-armed bandits refers to a class of online learning
problems, in which an agent is supposed to simultaneously explore and exploit a given set …
problems, in which an agent is supposed to simultaneously explore and exploit a given set …
Classification and ranking of Fermi LAT gamma-ray sources from the 3FGL catalog using machine learning techniques
We apply a number of statistical and machine learning techniques to classify and rank
gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL) …
gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL) …
Analysis of ranking data
Ranking is one of the simple and efficient data collection techniques to understand
individuals' perception and preferences for some items such as products, people, and …
individuals' perception and preferences for some items such as products, people, and …
Critical success factor analysis for effective risk management at the execution stage of a construction project
Despite the importance of proper risk management during the construction execution stage,
the current studies mainly focus on risk management at the planning stage. In order to …
the current studies mainly focus on risk management at the planning stage. In order to …
Stakeholders perceptions to sustainable urban freight policies in emerging markets
The aim of this paper is to analyze the perceptions of key stakeholders to a set of policies
designed to address urban logistics issues in two cities in Colombia. A ranking survey was …
designed to address urban logistics issues in two cities in Colombia. A ranking survey was …
Model-based learning from preference data
Preference data occur when assessors express comparative opinions about a set of items,
by rating, ranking, pair comparing, liking, or clicking. The purpose of preference learning is …
by rating, ranking, pair comparing, liking, or clicking. The purpose of preference learning is …
Probabilistic preference learning with the Mallows rank model
Ranking and comparing items is crucial for collecting information about preferences in many
areas, from marketing to politics. The Mallows rank model is among the most successful …
areas, from marketing to politics. The Mallows rank model is among the most successful …
Quantitative research
Quantitative methods are often used when asking research questions that seek to explain,
describe, or evaluate a social phenomenon with the intent to generalize findings from a …
describe, or evaluate a social phenomenon with the intent to generalize findings from a …
Study of machine learning on the photocatalytic activity of a novel nanozeolite for the application in the Rhodamine B dye degradation
LR Oviedo, DM Druzian, LD Dalla Nora, WL da Silva - Catalysis Today, 2025 - Elsevier
Contamination of wastewater with organic dyes has caused a serious threat to humans and
aquatic life due to the hazardous effect of these contaminants. In this context, the present …
aquatic life due to the hazardous effect of these contaminants. In this context, the present …