Volume 16 Number 2 - 4th International Conference on Computer Science and Machine Learning (CSML 2026)

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Volume 16, Number 2, January 2026

4^th International Conference on Computer Science and Machine Learning (CSML 2026), January 24 ~ 25, 2026, Copenhagen, Denmark

Volume Editors : David C. Wyld, Dhinaharan Nagamalai (Eds)
ISBN : 978-1-923107-82-3

Parallel Approximation Algorithms for Rainbow Matching in Bipartite Graphs with Applications to Machine Learning Systems

Saeed Bakhshan and Maedeh Yahaghi , Wayne State University ,USA

A Parallel Graph Coloring Algorithm with Applications in Machine Learning

Maedeh Yahaghi and Saeed Bakhshan , Wayne State University ,USA

Vectorcube: Multi-Granular Neuro-Symbolic Data Cubes For Semantic OLAP

Siddhesh Ramesh Surve ,USA

From Worst Case to Conditional Frontiers in Reinforcement Learning

Amar Ahmad , Yvonne Valles , and Youssef Idaghdour , New York University, UAE

Enhancing Architectural Safety Design Through a 3D NPC-Driven Emergency Evacuation Simulation

Malcolm Qiu ¹ and Moddwyn Andaya ², ¹ USA , ² California State Polytechnic University, USA

Design and Evaluation of a Low-Cost Computer Vision System for Real-Time Automated Chess Move Notation

William Huang Wang ¹ and Andrew Park ² , ¹ USA, ² California State Polytechnic University, USA

A Comprehensive Comparison of Text Summarization Performance: A Multi-Faceted Evaluation of Large Language Models with Practical Considerations

Anantharaman Janakiraman and Behnaz Ghoraani , Florida Atlantic University

Failure Semantics: Why Systems Fail Despite Correct Diagnostics

Anand Wanjari , Independent Researcher, USA

Risk-Based Test Framework for LLM Features in Regulated Software

Zhiyin Zhou , New York, USA

Dynamic Optimization-Based Clustering in Hexagonal Topology for Enhancing Network Lifetime of WSNs

S. Ceca Mijatovic , Shahram Sarkani and Thomas Mazzuchi , The George Washington University, Washington D.C., USA

Performance Impact Factors for the Knapsack Algorithm Based on Dynamic Programming

David Kuhlen and Andreas Speck, Germany

The Fractime Framework: A Unified Toolkit for Fractal Geometry and Probability-Weighted Time Series Forecasting

Rick Galbo , Wayy Research, USA