Semi-supervised learning (SSL) has tremendous value in practice due to the utilization of
both labeled and unlabelled data. An essential class of SSL methods, referred to as graph …

Incremental learning, online learning, and data stream learning are terms commonly
associated with learning algorithms that update their models given a continuous influx of …

In the past decade the mathematical theory of machine learning has lagged far behind the
triumphs of deep neural networks on practical challenges. However, the gap between theory …

Multi-view clustering has attracted increasing attention in multimedia, machine learning and
data mining communities. As one kind of the essential multi-view clustering algorithm, multi …

Abstract We present Deep Neural Decision Forests-a novel approach that unifies
classification trees with the representation learning functionality known from deep …

Multi-view clustering, which seeks a partition of the data inmultiple views that often provide
complementary information to eachother, has received considerable attention in recent …

Extreme learning machines (ELMs) have proven to be efficient and effective learning
mechanisms for pattern classification and regression. However, ELMs are primarily applied …

Supervised learning with large scale labelled datasets and deep layered models has
caused a paradigm shift in diverse areas in learning and recognition. However, this …

Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …

Semi-supervised learning is a learning paradigm concerned with the study of how
computers and natural systems such as humans learn in the presence of both labeled and …