Instance selection plays a pivotal role in enhancing machine learning by identifying and retaining those data instances that are most informative for the learning process, while discarding redundant ...
This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...
Machine learning (ML) is a complex domain that sits squarely at the convergence of mathematics, computer science, and statistics. Its mastery demands profound knowledge, practical expertise, and a ...
Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...
When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...
Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...
Artificial Intelligence (AI) has become an integral part of modern technology, transforming various industries by simulating human intelligence through computers. This guide delves into the world of ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results