Online learning: A comprehensive survey
Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …
to tackle some predictive (or any type of decision-making) task by learning from a sequence …
Large scale online multiple kernel regression with application to time-series prediction
Kernel-based regression represents an important family of learning techniques for solving
challenging regression tasks with non-linear patterns. Despite being studied extensively …
challenging regression tasks with non-linear patterns. Despite being studied extensively …
Passive-aggressive online learning with nonlinear embeddings
Nowadays, there is an increasing demand for machine learning techniques which can deal
with problems where the instances are produced as a stream or in real time. In these …
with problems where the instances are produced as a stream or in real time. In these …
Relational intelligence recognition in online social networks—A survey
Abstract Information networks today play an important, fundamental role in regulating real
life activities. However, many methods developed on this framework lack the capacity to …
life activities. However, many methods developed on this framework lack the capacity to …
Learning with incremental instances and features
In many real-world applications, data may dynamically expand over time in both volume and
feature dimensions. Besides, they are often collected in batches (also called blocks). We …
feature dimensions. Besides, they are often collected in batches (also called blocks). We …
Evaluation and Interpretation of Tourist Satisfaction for Local Korean Festivals Using Explainable AI
In this paper, we propose using explainable artificial intelligence (XAI) techniques to predict
and interpret the effects of local festival components on tourist satisfaction. We use data …
and interpret the effects of local festival components on tourist satisfaction. We use data …
An online passive-aggressive algorithm for difference-of-squares classification
We investigate a low-rank model of quadratic classification inspired by previous work on
factorization machines, polynomial networks, and capsule-based architectures for visual …
factorization machines, polynomial networks, and capsule-based architectures for visual …
Sparse passive-aggressive learning for bounded online kernel methods
One critical deficiency of traditional online kernel learning methods is their unbounded and
growing number of support vectors in the online learning process, making them inefficient …
growing number of support vectors in the online learning process, making them inefficient …
Online kernel learning with adaptive bandwidth by optimal control approach
Online learning methods are designed to establish timely predictive models for machine
learning problems. The methods for online learning of nonlinear systems are usually …
learning problems. The methods for online learning of nonlinear systems are usually …
Budgeted passive-aggressive learning for online multiclass classification
Online multiclass classification is a specific problem of online learning that performs a
sequence of multiclass classification tasks given the knowledge of previous tasks. The goal …
sequence of multiclass classification tasks given the knowledge of previous tasks. The goal …