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CS Technical Reports

The file that you are reading contains the list of our 2024 reports. Links from this list lead to pdf files. Lists of reports from the previous years can be found by clicking on:

  • What Is Optimal Granularity When Estimating Reliability of a Complex Engineering Systems

    Niklas Winnewisser, Michael Beer, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-58 in pdf
  • How Shapley Value and Its Generalizations Can Help in the Analysis of Complex Engineering Systems and What Next

    Niklas Winnewisser, Michael Beer, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-57 in pdf
  • Fair Economic Division: How to Modify Shapley Value to Take Into Account that Different People Have Different Productivity

    Christian Servin and Vladik Kreinovich

    link to abstract | UTEP-CS-24-56 in pdf | UTEP-CS-24-56b in pdf
  • Logarithmic Number System Is Optimal for AI Computations: Theoretical Explanation of an Empirical Success

    Olga Kosheleva, Vladik Kreinovich, Christoph Lauter, and Kristalys Ruiz-Rohena

    link to abstract | UTEP-CS-24-55 in pdf | UTEP-CS-24-55a in pdf
  • Why Linear Faults Have Fewer Earthquakes: A Geometric Explanation

    Julio C. Urenda, Aaron Velasco, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-54 in pdf
  • Why Geological Angular Unconformity Is Usually Horizontal: A Geometric Explanation

    Julio C. Urenda, Aaron Velasco, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-53 in pdf
  • Is Energy Local? Counterintuitive Non-Locality of Energy in General Relativity Can Be Naturally Explained on the Newtonian Level

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-52 in pdf | UTEP-CS-24-52a in pdf
  • Two Is Enough, but Three (or More) Is Better: in AI and Beyond

    Olga Kosheleva, Vladik Kreinovich, Victor Timchenko, and Yuriy Kondratenko

    link to abstract | UTEP-CS-24-51 in pdf | UTEP-CS-24-51a in pdf
  • Training Neural Networks on Interval Data: Unexpected Results and Their Explanation

    Edwin Tomy George, Luc Jaulin, Vladik Kreinovich, Christoph Lauter, and Martine Ceberio

    link to abstract | UTEP-CS-24-50 in pdf
  • Three Applications of Geometric Reasoning: Why Metastasis Is Mostly Caused by Elongated Cancer Cells? How Body Shape Affects Curiosity? Why Ring Fractures in Ice?

    Julio C. Urenda, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-49 in pdf
  • How to Check Continuity Based on Approximate Measurement Results

    Inese Bula and Vladik Kreinovich

    link to abstract | UTEP-CS-24-48 in pdf
  • Why Kolmolgorov-Arnold Networks (KAN) Work So Well: A Qualitative Explanation

    Hung T. Nguyen, Vladik Kreinovich, and Olga Kosheleva

    link to abstract | UTEP-CS-24-47 in pdf
  • A Full Description of All Commutative Associative Polynomial Operations on Probabilities

    Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, and Nguyen Hoang Phuong

    link to abstract | UTEP-CS-24-46 in pdf
  • To Which Interdisciplinary Research Collaborations Should We Pay More Attention?

    Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, and Nguyen Hoang Phuong

    link to abstract | UTEP-CS-24-45 in pdf
  • Why Decisions Based on the Results of Worst-Case, Most Realistic, and Best-Case Scenarios Work Well?

    Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich, and Chon Van Le

    link to abstract | UTEP-CS-24-44 in pdf
  • Why Green Wavelength Is Closer to Blue Than to Red and How It Is Related to Computations: Information-Based Explanation

    Victor L. Timchenko, Yuriy P. Kondratenko, Olga Kosheleva, Vladik Kreinovich, and Nguyen Hoang Phuong

    link to abstract | UTEP-CS-24-43 in pdf
  • What If the Resulting Interval Is Too Wide: From a Heuristic Fuzzy-Technique Idea to a Mathematically Justified Approach

    Marc Fina and Vladik Kreinovich

    link to abstract | UTEP-CS-24-42 in pdf
  • Shapley Value under Interval Uncertainty and Partial Information

    Kittawit Autchariyapanikul, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-41 in pdf
  • Why Seismicity in Ireland Is Low: A Possible Geometric Explanation

    Julio C. Urenda, Aaron Velasco, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-40 in pdf
  • Why Angles Between Galactic Center Filaments and Galactic Plane Follow a Bimodal Distribution: A Symmetry-Based Explanation

    Julio C. Urenda and Vladik Kreinovich

    link to abstract | UTEP-CS-24-39 in pdf
  • Stochastic Dominance: Cases of Interval and P-Box Uncertainty

    Kittawit Autchariyapanikul, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-38 in pdf
  • Is Alaska Negative-Tax Arrangement Fair? Almost: Mathematical Analysis

    Chon Van Le and Vladik Kreinovich

    link to abstract | UTEP-CS-24-37 in pdf
  • For 2 x n Cases, Proportional Fitting Problem Reduces to a Single Equation

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-36 in pdf
  • If Subsequent Results Are Too Easy to Obtain, the Proof Most Probably Has Errors: Explanation of the Empirical Observation

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-35 in pdf
  • Towards a More Subtle (and Hopefully More Adequate) Fuzzy "And"-Operation: Normalization-Invariant Multi-Input Aggregation Operators

    Yusuf Guven and Vladik Kreinovich

    link to abstract | UTEP-CS-24-34 in pdf
  • Why Fully Consistent Quantum Field Theories Require that the Space-Time Be at Least 10-Dimensional: A Commonsense Field-Based Explanation

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-33 in pdf
  • Why Empirical Membership Functions Are Well-Approximated by Piecewise Quadratic Functions: Theoretical Explanation for Empirical Formulas of Novak's Fuzzy Natural Logic

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-32 in pdf
  • How to Propagate Uncertainty via AI Algorithms

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-31 in pdf
  • Why Magenta Is Not a Real Color, and How It Is Related to Fuzzy Control and Quantum Computing

    Victor L. Timchenko, Yuriy P. Kondratenko, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-30 in pdf | UTEP-CS-24-30a in pdf
  • What to Do If an Inflexible Tolerance Problem Has No Solutions: Probabilistic Justification of Piegat's Semi-Heuristic Idea

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-29 in pdf
  • How to Make AI More Reliable

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-28 in pdf
  • For Discrete-Time Linear Dynamical Systems under Interval Uncertainty, Predicting Two Moments Ahead Is NP-Hard

    Luc Jaulin, Olga Kosheleva, Vladik Kreinovich

    link to abstract | UTEP-CS-24-27 in pdf
  • Why Is Grade Distribution Often Bimodal? Why Individualized Teaching Adds Two Sigmas to the Average Grade? And How Are These Facts Related?

    Christian Servin, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-26 in pdf | UTEP-CS-24-26a in pdf
  • How to Make a Neural Network Learn from a Small Number of Examples -- and Learn Fast: An Idea

    Chitta Baral and Vladik Kreinovich

    link to abstract | UTEP-CS-24-25 in pdf
  • How Can We Explain Empirical Formulas for Shrinkage Cracking of Cement-Stabilized Pavement Layers

    Edgar Daniel Rodriguez Velasquez and Vladik Kreinovich

    link to abstract | UTEP-CS-24-24 in pdf
  • Topics in the Study of the Pragmatic Functions of Phonetic Reduction in Dialog

    Nigel G. Ward and Carlos A. Ortega

    link to abstract | UTEP-CS-24-23 in pdf
  • Towards an Optimal Design: What Can We Recommend to Elon Musk?

    Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, and Hung T. Nguyen

    link to abstract | UTEP-CS-24-22 in pdf
  • Shall We Place More Advanced Students in a Separate Class?

    Shahnaz Shahbazova, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-21 in pdf
  • Using Known Relation Between Quantities to Make Measurements More Accurate and More Reliable

    Niklas R. Winnewisser, Felix Mett, Michael Beer, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-20 in pdf | UTEP-CS-24-20a in pdf
  • How to Fairly Allocate Safety Benefits of Self-Driving Cars

    Fernando Munoz, Christian Servin, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-19 in pdf
  • Data Fusion Is More Complex Than Data Processing: A Proof

    Robert Alvarez, Salvador Ruiz, Martine Ceberio, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-18 in pdf
  • Number Representation With Varying Number of Bits

    Anuradha Choudhury, Md Ahsanul Haque, Saeefa Rubaiyet Nowmi, Ahmed Ann Noor Ryen, Sabrina Saika, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-17 in pdf
  • Paradox of Causality and Paradoxes of Set Theory

    Alondra Baquier, Bradley Beltran, Gabriel Miki-Silva, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-16 in pdf
  • How to Make a Decision under Interval Uncertainty If We Do Not Know the Utility Function

    Jeffrey Escamilla and Vladik Kreinovich

    link to abstract | UTEP-CS-24-15 in pdf
  • Why Two Fish Follow Each Other but Three Fish Form a School: A Symmetry-Based Explanation

    Shahnaz Shahbazova, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-14 in pdf
  • From Aristotle to Newton, from Sets to Fuzzy Sets, and from Sigmoid to ReLU: What Do All These Transitions Have in Common?

    Christian Servin, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-13 in pdf | UTEP-CS-24-13a in pdf
  • How to Gauge Inequality and Fairness: A Complete Description of All Decomposable Versions of Theil Index

    Saeid Tizpaz-Niari, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-12 in pdf | UTEP-CS-24-12a in pdf
  • Somewhat Surprisingly, (Subjective) Fuzzy Technique Can Help to Better Combine Measurement Results and Expert Estimates into a Model with Guaranteed Accuracy: Digital Twins and Beyond

    Niklas Winnewisser, Michael Beer, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-11 in pdf | UTEP-CS-24-11a in pdf
  • Why Bernstein Polynomials: Yet Another Explanation

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-10 in pdf | UTEP-CS-24-10a in pdf
  • McFadden's Discrete Choice and Softmax under Interval (and Other) Uncertainty: Revisited

    Bartlomiej Jacek Kubica, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-09 in pdf | UTEP-CS-24-09a in pdf
  • Why Linear and Sigmoid Last Layers Work Better in Classification

    Lehel Denes-Fazakas, Laszlo Szilagyi, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-08 in pdf
  • How Difficult Is It to Comprehend a Program That Has Significant Repetitions: Fuzzy-Related Explanations of Empirical Results

    Christian Servin, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-07 in pdf | UTEP-CS-24-07a in pdf
  • Why Pavement Cracks Are Mostly Longitudinal, Sometimes Transversal, and Rarely of Other Directions: A Geometric Explanation

    Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, and Vladik Kreinovich

    link to abstract | UTEP-CS-24-06 in pdf
  • From Quantifying and Propagating Uncertainty to Quantifying and Propagating Both Uncertainty and Reliability: Practice-Motivated Approach to Measurement Planning and Data Processing

    Niklas R. Winnewisser, Michael Beer, Vladik Kreinovich, and Olga Kosheleva

    link to abstract | UTEP-CS-24-05 in pdf | UTEP-CS-24-05a in pdf
  • There Is Still Plenty of Room at the Bottom: Feynman's Vision of Quantum Computing 65 Years Later

    Alexis Lupo, Olga Kosheleva, Vladik Kreinovich, Victor Timchenko, and Yuriy Kondratenko

    link to abstract | UTEP-CS-24-04 in pdf
  • Fuzzy Ideas Explain Fechner Law and Help Detect Relation Between Objects in Video

    Olga Kosheleva, Vladik Kreinovich, and Ahnaf Farhan

    link to abstract | UTEP-CS-24-03 in pdf | UTEP-CS-24-03a in pdf
  • From Normal Distribution to What? How to Best Describe Distributions with Known Skewness

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-02 in pdf
  • Every Feasibly Computable Reals-to-Reals Function Is Feasibly Uniformly Continuous

    Olga Kosheleva and Vladik Kreinovich

    link to abstract | UTEP-CS-24-01 in pdf