Latest Articles for Algorithms

Examining how algorithms perform in the presence of noise during multi-objective optimization.

A new method leverages Johnson-Lindenstrauss matrices for extreme multiclass classification.

A new framework tackles challenges of Byzantine agents in distributed optimization.

New algorithms enhance efficiency in solving complex optimization problems.

Using quantum computing to tackle the maximum cut issue in graph theory.

This study combines classical and quantum methods for improved image segmentation.

This article examines methods to show certain number sequences are positive.

Exploring the types and properties of graphs and their applications.

Introducing an innovative modular approach to improve reinforcement learning efficiency and performance.

Examining how algorithms can adapt to strategic behavior in lending and hiring.

This article discusses the advantages and challenges of hypothesis transfer learning in machine learning.

Research on algorithms for finding shortest paths in distributed graph models.

New methods improve sampling efficiency for large datasets in machine learning.

This article discusses improving sketching algorithms through innovative machine learning techniques.

Exploring methods to count unique items while protecting individual privacy.

New methods simplify complex calculations in many-body quantum systems using quantum computers.

Exploring challenges and solutions in creating multi-input Toffoli gates for quantum computing.

A closer look at local antimagic labeling and its impact on bridge graphs.

This article presents a novel variational method for studying non-Hermitian systems using quantum computing.

New methods improve graph-based semi-supervised learning efficiency and speed.

Learn about clustering and its importance in analyzing data effectively.

This article explores improvements to Angluin's algorithm for learning automata with noisy data.

Learn how multiplication transducers simplify calculations in various bases.

Introducing a reliable method for managing dynamic trees without randomness.

This article discusses methods for optimizing smooth, non-convex functions with noise.

A look into Roman Domination and its applications in graph theory.

Explore how trigger selection impacts SMT solver efficiency and accuracy.

A new algorithm to enhance training speed for reversible deep learning models.

New algorithm improves choices in uncertain situations within multi-armed bandit problems.

Permutation graphs play a crucial role in graph isomorphism testing and algorithm development.

This study reveals new strategies for minimizing regret in online learning.

MementoHash offers efficient data distribution across nodes in cloud environments.

This paper presents two new algorithms for clustering graphs with clear structures.

Examining the role of quantum algorithms in modern chemistry calculations.

Explore how BDD-based methods improve SAT problem-solving efficiency.

This article discusses analyzing treatment actions for better patient outcomes.

A new approach to actor-critic algorithms using two-layer neural networks.

A new method to encourage patient actions for effective treatment.

This article discusses methods to find missing subgraphs in larger graphs.

Examining how natural processes influence machine learning training methods.