Latest Articles for Computer Science

The SEBQ scheme offers advanced security in symmetric encryption using quasigroups.

A new method merges AI techniques for improved learning from data.

Researchers present a faster way to solve complex differential equations using random walks.

Learn how model pruning enhances AI performance and reduces resource needs.

Learn how to craft specifications for programs with complex behaviors.

Discover how deep learning mimics brain function to enhance machine learning.

A new approach to assess language models with varied instructions and tasks.

A study of labeling techniques in null and 1-regular graphs.

Exploring the study of surfaces in geometry and topology.

New methods improve accuracy and speed in studying the universe's structure.

This article discusses data augmentation methods for improving continual reinforcement learning agents.

New methods improve efficiency in solving complex computational problems.

This article focuses on the challenges of correlated errors in quantum memory systems.

Learn about edge geodetic graphs and their significance in network connections.

A new approach enhances gradient calculations, improving transformer efficiency in machine learning.

Exploring random walks on the associahedron and their mixing times.

Innovative methods enhance quantum circuit simulations, overcoming hardware limitations.

Research focuses on efficient algorithms for dominating sets in complex networks.

Learn about subfactors and how they relate within group theory.

A simplified look at CSPs and the impact of additional constraints.

An overview of digraphs, their cycles, and the concept of period.

A look into Woodall's conjecture and its significance in planar graphs.

Learn how to determine fair meeting spots using graph centers and centroids.

Introducing character complexity to improve quantum circuit analysis and algorithm design.

Exploring the complexity of dividing graphs into two connected groups.

A look into the complexities of identifying candidate keys in database design.

A study of random hypergraphs, focusing on subgraph counts and statistical behavior.

Explore the structure and properties of directed graphs and their applications.

A method to enhance how machine learning models handle new data.

Exploring the impact of positive equality-free logic on model-checking methods.

A look at recent findings in machine translation evaluation methods.

Learn to create efficient data structures for concurrent programming environments.

A look into reflection-symmetric graphs and their possible flexible arrangements.

This paper presents a method to automatically create formal semantics using interpreters.

A look into additive spanners and their role in simplifying network connections.

Exploring the behavior and structure of random graphs in various contexts.

Study examines how group formation and discussions affect programming education outcomes.

A new method for finding shortest paths in changing directed graphs.

Ultrahomogeneous graphs showcase symmetry, impacting various fields like computer science.

This article discusses a method to improve SMT solving by using machine learning for quantifier selection.