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 …

Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …

Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …

With the development of deep representation learning, the domain of reinforcement learning
(RL) has become a powerful learning framework now capable of learning complex policies …

Deep learning with noisy labels is practically challenging, as the capacity of deep models is
so high that they can totally memorize these noisy labels sooner or later during training …

Artificial intelligence (AI) agents driven by machine learning algorithms are rapidly
transforming the business world, generating heightened interest from researchers. In this …

Even though active learning forms an important pillar of machine learning, deep learning
tools are not prevalent within it. Deep learning poses several difficulties when used in an …

The increasing scale of large language models (LLMs) brings emergent abilities to various
complex tasks requiring reasoning, such as arithmetic and commonsense reasoning. It is …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …