Abstract: Data clustering is a fundamental machine learning task that seeks to categorize a dataset into homogeneous groups. However, real data usually contain noise, which poses significant ...

Abstract: In this article, we propose a novel algorithm to obtain a solution to the clustering problem with an additional constraint of connectivity. This is achieved by suitably modifying K-Means ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

In addition to single-nucleotide variations and small insertions-deletions (indels), larger-sized structural variations (for example, insertions, deletions, inversions, segmental duplications and copy ...

This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Kiev outpaces Russia in the technological race. Its advancements allow it to train AI drones and spy on Moscow with real-time ...

Protecting creators themselves was another recurring theme.

Tefi Pessoa is a mentor, a walking pop-culture encyclopedia, and now — along with Ciara Miller — one of the hosts of Love ...

For the last two to three years, the world has been told that support for Israel is collapsing across the West. Social media ...

Bing accounts for 26.5% of all desktop searches in the U.S., according to Comscore (April 2021). With the recent prevalence of working from home, people are spending more time on their desktop ...

In his first interview since switching teams from Netflix, Tony Zameczkowski shares Disney's strategy across the Asia-Pacific ...