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ORCIDVladik Kreinovich
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- affiliation: University of Texas at El Paso, Department of Computer Science
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2020 – today
- 2022
[j417]Ander Gray
, Scott Ferson, Vladik Kreinovich, Edoardo Patelli:
Distribution-free risk analysis. Int. J. Approx. Reason. 146: 133-156 (2022)- [j416]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 30(2): 335-336 (2022) - [j415]Vladik Kreinovich:
Ordered Weighted Averaging (OWA), Decision Making under Uncertainty, and Deep Learning: How Is This All Related? Inf. 13(2): 82 (2022) - [j414]Nancy Solis García, José Guadalupe Flores Muñiz, Vladik Kreinovich, Nataliya I. Kalashnykova, Viacheslav Kalashnikov:
Consistent Conjectural Variations Equilibrium for a Financial Model. J. Optim. Theory Appl. 194(3): 966-987 (2022) - [c263]Olga Kosheleva, Vladik Kreinovich:
Why People Tend to Overestimate Joint Probabilities. IPMU (1) 2022: 485-493 - [e17]Julia Rayz, Victor Raskin, Scott Dick, Vladik Kreinovich:
Explainable AI and Other Applications of Fuzzy Techniques - Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2021, Virtual Event / West Lafayette, IN, USA, June 7-9, 2021. Lecture Notes in Networks and Systems 258, Springer 2022, ISBN 978-3-030-82098-5 [contents] - [e16]Barnabás Bede, Martine Ceberio, Martine De Cock, Vladik Kreinovich:
Fuzzy Information Processing 2020 - Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020, Redmond, WA, USA, 20-22 August 2020. Advances in Intelligent Systems and Computing 1337, Springer 2022, ISBN 978-3-030-81560-8 [contents] - [i5]Orsolya Csiszár, Luca Sára Pusztaházi, Lehel Dénes-Fazakas, Michael S. Gashler, Vladik Kreinovich, Gábor Csiszár:
Uninorm-like parametric activation functions for human-understandable neural models. CoRR abs/2205.06547 (2022) - [i4]Evgeny Dantsin, Vladik Kreinovich, Alexander Wolpert:
An AlphaZero-Inspired Approach to Solving Search Problems. CoRR abs/2207.00919 (2022) - 2021
- [j413]Juan Carlos Figueroa García, Vladik Kreinovich:
How Accurate Are Fuzzy Control Recommendations: Interval-Valued Case. Adv. Artif. Intell. Mach. Learn. 1(1): 12-25 (2021) - [j412]Javier Viaña, Stephan Ralescu, Kelly Cohen, Vladik Kreinovich, Anca L. Ralescu:
Why Cauchy Membership Functions: Efficiency. Adv. Artif. Intell. Mach. Learn. 1(1): 82-89 (2021) - [j411]Vladik Kreinovich, Olga Kosheleva:
Limit Theorems as Blessing of Dimensionality: Neural-Oriented Overview. Entropy 23(5): 501 (2021) - [j410]Jonatan M. Contreras, Martine Ceberio, Vladik Kreinovich:
Why Dilated Convolutional Neural Networks: A Proof of Their Optimality. Entropy 23(6): 767 (2021) - [j409]Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich, Olga Kosheleva:
Invariance-based approach: general methods and pavement engineering case study. Int. J. Gen. Syst. 50(6): 672-702 (2021) - [j408]Olga Kosheleva, Vladik Kreinovich:
Joseph Henrich, The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, Farrar, Straus, and Giroux, New York, 2020. J. Intell. Fuzzy Syst. 40(1): 1713-1714 (2021) - [j407]Olga Kosheleva, Vladik Kreinovich:
Hung T. Nguyen, Carol L. Walker, and Elbert A. Walker A First Course in Fuzzy Logic (4th edition) CRC Press, Taylor & Francis Book, Boca Raton, Florida, 2019. J. Intell. Fuzzy Syst. 40(1): 1715-1716 (2021) - [j406]Vladik Kreinovich:
Witold Pedrycz An Introduction to Computing with Fuzzy Sets: Analysis, Design, and Applications Springer, Cham, Switzerland, 2021. J. Intell. Fuzzy Syst. 40(1): 1717-1719 (2021) - [j405]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Amanda Jansen, Rough Draft Math: Revising to Learn, Stenhouse Publishers, Portsmouth, New Hampshire, 2020. J. Intell. Fuzzy Syst. 40(2): 3813-3814 (2021) - [j404]Vladik Kreinovich:
Jozo Dujmović, Soft Computing Evaluation Logic: The LSP Decision Method, and Its Applications, IEEE Press and Wiley, Hoboken, New Jersey, 2018. J. Intell. Fuzzy Syst. 40(2): 3815-3817 (2021) - [j403]Vladik Kreinovich:
Boris Kovalerchuk, Visual Knowledge Discovery and Machine Learning Springer, Cham, Switzerland, 2018. J. Intell. Fuzzy Syst. 40(3): 5753-5755 (2021) - [j402]Vladik Kreinovich:
Fabio Cuzzolin, The Geometry of Uncertainty: The Geometry of Imprecise Probabilities Springer, Cham, Switzerland, 2021. J. Intell. Fuzzy Syst. 40(3): 5757-5758 (2021) - [j401]Vladik Kreinovich:
Olga Kosheleva and Karen Villaverde How Interval and Fuzzy Techniques Can Improve Teaching Springer, Cham, Switzerland, 2018. J. Intell. Fuzzy Syst. 40(5): 10323-10324 (2021) - [j400]Olga Kosheleva, Vladik Kreinovich:
Wolfram Eilenberger Time of the Magicians: Wittgenstein, Benjamin, Cassirer, Heidegger, and The Decade that Reinvented Philosophy Penguin Press, New York, 2020. J. Intell. Fuzzy Syst. 40(5): 10325-10327 (2021) - [j399]Olga Kosheleva, Vladik Kreinovich:
Djuro G. Zrilic Functional Processing of Delta-Sigma Bit-Stream, Springer, Cham, Switzerland, 2020. J. Intell. Fuzzy Syst. 40(5): 10329-10330 (2021) - [j398]Vladik Kreinovich:
Concha Bielza and Pedro Larrañaga, Data-Driven Computational Neuroscience: Machine Learning and Statistical Models, Cambridge University Press, Cambridge, UK, 2021. J. Intell. Fuzzy Syst. 41(1): 2513-2514 (2021) - [j397]Vladik Kreinovich:
Chiara Marletto, The Science of Can and Can't: A Physicist's Journey Through the Land of Counterfactuals, Viking, New York, 2021. J. Intell. Fuzzy Syst. 41(1): 2515-2517 (2021) - [j396]Vladik Kreinovich:
Jose Maria Alonso Moral, Ciro Castiello, Luis Magdalena, and Corrado Mencar, Explainable Fuzzy Systems: Paving the Way from Interpretable Fuzzy Systems to Explainable AI Systems, Springer, Cha... J. Intell. Fuzzy Syst. 41(1): 2519-2520 (2021) - [j395]Hung T. Nguyen, Vladik Kreinovich:
Special issue on soft computing in economic application. Soft Comput. 25(12): 7693-7694 (2021) - [c262]Laxman Bokati, Olga Kosheleva, Vladik Kreinovich:
How Much for a Set: General Case of Decision Making Under Set-Valued Uncertainty. NAFIPS 2021: 52-61 - [c261]Kelly Cohen, Laxman Bokati, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Fuzzy Techniques in Explainable AI? Which Fuzzy Techniques in Explainable AI? NAFIPS 2021: 74-78 - [c260]Olga Kosheleva, Vladik Kreinovich:
A Natural Formalization of Changing-One's-Mind Leads to Square Root of "Not" and to Complex-Valued Fuzzy Logic. NAFIPS 2021: 190-195 - [c259]Olga Kosheleva, Vladik Kreinovich:
Each Realistic Continuous Functional Dependence Implies a Relation Between Some Variables: A Theoretical Explanation of a Fuzzy-Related Empirical Phenomenon. NAFIPS 2021: 196-202 - [c258]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
What Teachers Can Learn from Machine Learning. NAFIPS 2021: 400-405 - [c257]Julio C. Urenda, Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Mexican Folk Arithmetic Algorithm Makes Perfect Sense. NAFIPS 2021: 453-460 - [c256]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich:
Fuzzy Logic Leads to a More Adequate Way of Processing Likert-Scale Values: Case Study of Burnout. NAFIPS 2021: 499-504 - [c255]Michael Beer, Olga Kosheleva, Vladik Kreinovich:
Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL- Decomposition and Interval Fields. SSCI 2021: 1-7 - [c254]Ander Gray, Scott Ferson, Olga Kosheleva, Vladik Kreinovich:
While, In General, Uncertainty Quantification (UQ) Is NP-Hard, Many Practical UQ Problems Can Be Made Feasible. SSCI 2021: 1-6 - [p63]Vladik Kreinovich, Olga Kosheleva, Michael Zakharevich:
Z-Numbers: How They Describe Student Confidence and How They Can Explain (and Improve) Laplacian and Schroedinger Eigenmap Dimension Reduction in Data Analysis. Fuzzy Approaches for Soft Computing and Approximate Reasoning 2021: 285-297 - 2020
- [b3]Griselda Acosta, Eric Smith, Vladik Kreinovich:
Towards Analytical Techniques for Systems Engineering Applications. Springer 2020, ISBN 978-3-030-46412-7, pp. 1-95 - [j394]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
If Space-Time Is Discrete, It Could Be Possible to Solve NP-Complete Problems in Polynomial Time. Int. J. Unconv. Comput. 15(3): 193-218 (2020) - [j393]Hung T. Nguyen, Vladik Kreinovich:
Uncertainty Analysis in Economics and Finance: Preface to the Special Issue. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 28(Supplement-1) (2020) - [j392]Hoang Phuong Nguyen, Vladik Kreinovich:
Towards Making Fuzzy Techniques More Adequate for Combining Knowledge of Several Experts. J. Adv. Comput. Intell. Intell. Informatics 24(5): 583-588 (2020) - [j391]Hoang Phuong Nguyen, Laxman Bokati, Vladik Kreinovich:
A New (Simplified) Derivation of Nash's Bargaining Solution. J. Adv. Comput. Intell. Intell. Informatics 24(5): 589-592 (2020) - [j390]Olga Kosheleva, Vladik Kreinovich, Hoang Phuong Nguyen:
How to Describe Conditions Like 2-out-of-5 in Fuzzy Logic: A Neural Approach. J. Adv. Comput. Intell. Intell. Informatics 24(5): 593-598 (2020) - [j389]Laxman Bokati, Hoang Phuong Nguyen, Olga Kosheleva, Vladik Kreinovich:
How to Combine (Dis)Utilities of Different Aspects into a Single (Dis)Utility Value, and How This Is Related to Geometric Images of Happiness. J. Adv. Comput. Intell. Intell. Informatics 24(5): 599-603 (2020) - [j388]Vladik Kreinovich, Omar Masmali, Hoang Phuong Nguyen, Omar Badreddin:
Theoretical Explanation of Recent Empirically Successful Code Quality Metrics. J. Adv. Comput. Intell. Intell. Informatics 24(5): 604-608 (2020) - [j387]Vladik Kreinovich:
Review of the book John Kay and Mervyn King, Radical Uncertainty: Decision Making Beyond the Numbers, W. W. Norton and Co., New York, 2020. J. Intell. Fuzzy Syst. 39(3): 4803-4805 (2020) - [j386]Vladik Kreinovich:
Review of the Book "Mind in Motion: How Action Shapes Thought" by Barbara Tversky, Basic Books, New York, 2019. J. Intell. Fuzzy Syst. 39(3): 4807-4810 (2020) - [c253]Olga Kosheleva, Vladik Kreinovich:
Relativistic Effects Can Be Used to Achieve a Universal Square-Root (Or Even Faster) Computation Speedup. Fields of Logic and Computation III 2020: 179-189 - [c252]Vladik Kreinovich:
Formal Concept Analysis Techniques Can Help in Intelligent Control, Deep Learning, etc. CLA 2020: 9-17 - [c251]Vladik Kreinovich, Martine Ceberio, Olga Kosheleva:
White- and Black-Box Computing and Measurements Under Limited Resources: Cloud, High Performance, and Quantum Computing, and Two Case Studies - Robotic Boat and Hierarchical Covid Testing. ICTES 2020: 1-18 - [c250]Michael Beer, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Why Spiking Neural Networks Are Efficient: A Theorem. IPMU (1) 2020: 59-69 - [c249]Michael Beer, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich:
Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. IPMU (1) 2020: 70-79 - [c248]Laxman Bokati, Olga Kosheleva, Vladik Kreinovich, Uram Anibal Sosa Aguirre:
Why Deep Learning Is More Efficient than Support Vector Machines, and How it is Related to Sparsity Techniques in Signal Processing. ISMSI 2020: 8-12 - [c247]Vladik Kreinovich, Olga Kosheleva:
Deep Learning (Partly) Demystified. ISMSI 2020: 30-35 - [c246]Jonatan Contretas, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio:
Let Us Use Negative Examples in Regression-Type Problems Too. IV 2020: 296-300 - [c245]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
Adversarial Teaching Approach to Cybersecurity: A Mathematical Model Explains Why It Works Well. IV 2020: 313-316 - [c244]Oscar Galindo, Olga Kosheleva, Vladik Kreinovich:
Why Majority Rule Does Not Work in Quantum Computing: A Pedagogical Explanation. MICAI (1) 2020: 396-401 - [c243]Edgar Daniel Rodriguez Velasquez, Olga Kosheleva, Vladik Kreinovich:
How to Decide Which Cracks Should Be Repaired First: Theoretical Explanation of Empirical Formulas. MICAI (1) 2020: 402-410 - [c242]Ricardo Alvarez, Nick Sims, Christian Servin, Martine Ceberio, Vladik Kreinovich:
How to Reconcile Randomness with Physicists' Belief that Every Theory Is Approximate: Informal Knowledge Is Needed. NAFIPS 2020: 373-378 - [c241]Laxman Bokati, Aaron Velasco, Vladik Kreinovich:
Scale-Invariance and Fuzzy Techniques Explain the Empirical Success of Inverse Distance Weighting and of Dual Inverse Distance Weighting in Geosciences. NAFIPS 2020: 379-390 - [c240]Christian Servin, Vladik Kreinovich:
Is There a Contradiction Between Statistics and Fairness: From Intelligent Control to Explainable AI. NAFIPS 2020: 391-400 - [c239]Olga Kosheleva, Vladik Kreinovich:
Which Algorithms Are Feasible and Which Are Not: Fuzzy Techniques Can Help in Formalizing the Notion of Feasibility. NAFIPS 2020: 401-406 - [c238]Juan Carlos Figueroa García, Christian Servin, Vladik Kreinovich:
Centroids Beyond Defuzzification. NAFIPS 2020: 407-412 - [c237]Leobardo Valera, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Equations for Which Newton's Method Never Works: Pedagogical Examples. NAFIPS 2020: 413-419 - [c236]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Optimal Search Under Constraints. NAFIPS 2020: 421-426 - [c235]Julio C. Urenda, Manuel Hernandez, Natalia Villanueva-Rosales, Vladik Kreinovich:
How User Ratings Change with Time: Theoretical Explanation of an Empirical Formula. NAFIPS 2020: 427-432 - [c234]Julio C. Urenda, Vladik Kreinovich:
Why a Classification Based on Linear Approximation to Dynamical Systems Often Works Well in Nonlinear Cases. NAFIPS 2020: 433-437 - [c233]Julio C. Urenda, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
How Mathematics and Computing Can Help Fight the Pandemic: Two Pedagogical Examples. NAFIPS 2020: 439-442 - [c232]Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Vladik Kreinovich:
Natural Invariance Explains Empirical Success of Specific Membership Functions, Hedge Operations, and Negation Operations. NAFIPS 2020: 443-456 - [c231]Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, Olga Kosheleva, Vladik Kreinovich, György Eigner:
Why Squashing Functions in Multi-Layer Neural Networks. SMC 2020: 1705-1711 - [c230]Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich:
Scale-Invariance Ideas Explain the Empirical Soil-Water Characteristic Curve. SSCI 2020: 958-962 - [c229]Oscar Galindo, Vladik Kreinovich:
What Is the Optimal Annealing Schedule in Quantum Annealing. SSCI 2020: 963-967 - [c228]Deepak K. Tosh, Oscar Galindo, Vladik Kreinovich, Olga Kosheleva:
Towards Security of Cyber-Physical Systems using Quantum Computing Algorithms. SoSE 2020: 313-320 - [p62]Mahdokht Afravi, Vladik Kreinovich:
Fuzzy Systems Are Universal Approximators for Random Dependencies: A Simplified Proof. Decision Making under Constraints 2020: 1-5 - [p61]Christian Ayub, Martine Ceberio, Vladik Kreinovich:
How Quantum Computing Can Help with (Continuous) Optimization. Decision Making under Constraints 2020: 7-14 - [p60]Chitta Baral, Martine Ceberio, Vladik Kreinovich:
How Neural Networks (NN) Can (Hopefully) Learn Faster by Taking into Account Known Constraints. Decision Making under Constraints 2020: 15-20 - [p59]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Italian Folk Multiplication Algorithm Is Indeed Better: It Is More Parallelizable. Decision Making under Constraints 2020: 59-64 - [p58]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Reverse Mathematics Is Computable for Interval Computations. Decision Making under Constraints 2020: 65-70 - [p57]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Plans Are Worthless but Planning Is Everything: A Theoretical Explanation of Eisenhower's Observation. Decision Making under Constraints 2020: 93-98 - [p56]Angel F. Garcia Contreras, Martine Ceberio, Vladik Kreinovich:
Why Convex Optimization Is Ubiquitous and Why Pessimism Is Widely Spread. Decision Making under Constraints 2020: 99-104 - [p55]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Attraction-Repulsion Forces Between Biological Cells: A Theoretical Explanation of Empirical Formulas. Decision Making under Constraints 2020: 139-144 - [p54]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
When We Know the Number of Local Maxima, Then We Can Compute All of Them. Decision Making under Constraints 2020: 145-151 - [p53]Andrzej Pownuk, Vladik Kreinovich:
Which Value $\widetilde{x}$ Best Represents a Sample x1, ... , xn: Utility-Based Approach Under Interval Uncertainty. Decision Making under Constraints 2020: 169-174 - [p52]Andrzej Pownuk, Vladik Kreinovich:
Why Unexpectedly Positive Experiences Make Decision Makers More Optimistic: An Explanation. Decision Making under Constraints 2020: 175-179 - [p51]Leobardo Valera, Martine Ceberio, Vladik Kreinovich:
Why Burgers Equation: Symmetry-Based Approach. Decision Making under Constraints 2020: 211-216 - [p50]Francisco Zapata, Maliheh Zargaran, Vladik Kreinovich:
Working on One Part at a Time Is the Best Strategy for Software Production: A Proof. Decision Making under Constraints 2020: 217-221 - [e15]Martine Ceberio, Vladik Kreinovich:
Decision Making under Constraints. Springer 2020, ISBN 978-3-030-40813-8 [contents] - [e14]Yuriy P. Kondratenko, Vladik Kreinovich, Dan Simon, Yaroslav M. Krainyk:
Proceedings of the 2nd International Workshop on Information-Communication Technologies & Embedded Systems (ICTES 2020) Mykolaiv, Ukraine (online), November 12, 2020., Mykolaiv, Ukraine (online), November 12, 2020. CEUR Workshop Proceedings 2762, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [j385]Vladik Kreinovich, Olga Kosheleva, Songsak Sriboonchitta:
Why Use a Fuzzy Partition in F-Transform? Axioms 8(3): 94 (2019) - [j384]Olga Kosheleva, Vladik Kreinovich, Thach Ngoc Nguyen:
Why Triangular Membership Functions Are Successfully Used in F-Transform Applications: A Global Explanation to Supplement the Existing Local Ones. Axioms 8(3): 95 (2019) - [j383]Ildar Z. Batyrshin, Olga Kosheleva, Vladik Kreinovich, Nailya Kubysheva, Raouf Akhtiamov:
Contrast Similarity Measures of Fuzzy Sets. Computación y Sistemas 23(4) (2019) - [j382]Vladik Kreinovich:
Acknowledgements to the Referees (2018). Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(1): 171-173 (2019) - [j381]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(2): 351-352 (2019) - [j380]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(3): 513-514 (2019) - [j379]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(4): 691-692 (2019) - [j378]Vladik Kreinovich:
Interval Methods in Knowledge Representation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 27(5): 879-880 (2019) - [j377]Ildar Z. Batyrshin, Valerie Cross, Vladik Kreinovich, Maria Rifqi:
Special issue on Similarity, Correlation and Association Measures. J. Intell. Fuzzy Syst. 36(4): 2975-2976 (2019) - [j376]Olga Kosheleva, Vladik Kreinovich:
How to Assign Points for Chores. Russ. Digit. Libr. J. 22(6): 759-762 (2019) - [j375]Olga Kosheleva, Vladik Kreinovich, Francisco Zapata:
Egyptian Fractions Re-Revisited. Russ. Digit. Libr. J. 22(6): 763-768 (2019) - [j374]Mourat Tchoshanov, Olga Kosheleva, Vladik Kreinovich:
Anatole France's Statement on Education Transformed into a Theorem. Russ. Digit. Libr. J. 22(6): 769-772 (2019) - [j373]Laxman Bokati, Vyacheslav Kalashnikov, Nataliya I. Kalashnykova, Olga Kosheleva, Vladik Kreinovich:
How to Assign Grades to Tasks so as to Maximize Student Efforts. Russ. Digit. Libr. J. 22(6): 773-779 (2019) - [c227]Thongchai Dumrongpokaphan, Afshin Gholamy, Vladik Kreinovich, Hoang Phuong Nguyen:
Why Hammerstein-Type Block Models Are so Efficient: Case Study of Financial Econometrics. ECONVN 2019: 129-136 - [c226]Thongchai Dumrongpokaphan, Vladik Kreinovich, Songsak Sriboonchitta:
Why Threshold Models: A Theoretical Explanation. ECONVN 2019: 137-145 - [c225]Thach Ngoc Nguyen, Olga Kosheleva, Vladik Kreinovich, Hoang Phuong Nguyen:
Blockchains Beyond Bitcoin: Towards Optimal Level of Decentralization in Storing Financial Data. ECONVN 2019: 163-167 - [c224]Miroslav Svítek, Olga Kosheleva, Vladik Kreinovich, Thach Ngoc Nguyen:
Why Quantum (Wave Probability) Models Are a Good Description of Many Non-quantum Complex Systems, and How to Go Beyond Quantum Models. ECONVN 2019: 168-175 - [c223]Tran Anh Tuan, Vladik Kreinovich, Thach Ngoc Nguyen:
Decision Making Under Interval Uncertainty: Beyond Hurwicz Pessimism-Optimism Criterion. ECONVN 2019: 176-184 - [c222]Oscar Galindo, Laxman Bokati, Vladik Kreinovich:
Towards a More Efficient Representation of Functions in Quantum and Reversible Computing. EUSFLAT Conf. 2019 - [c221]Oscar Galindo, Vladik Kreinovich:
For Quantum and Reversible Computing, Intervals Are More Appropriate Than General Sets, And Fuzzy Numbers Than General Fuzzy Sets. EUSFLAT Conf. 2019 - [c220]Olga Kosheleva, Vladik Kreinovich:
Physics's Need for Interval Uncertainty and How It Explains Why Physical Space Is (at Least) 3-Dimensional. EUSFLAT Conf. 2019 - [c219]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
Between Dog and Wolf: A Continuous Transition from Fuzzy to Probabilistic Estimates. FUZZ-IEEE 2019: 1-5 - [c218]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich, Luc Longpré:
In Its Usual Formulation, Fuzzy Computation Is, In General, NP-Hard, But a More Realistic Formulation Can Make It Feasible. FUZZ-IEEE 2019: 1-6 - [c217]Oscar Galindo, Olga Kosheleva, Vladik Kreinovich:
High Concentrations Naturally Lead to Fuzzy-Type Interactions and to Gravitational Wave Bursts. FUZZ-IEEE 2019: 1-5 - [c216]Olga Kosheleva, Christian Servin, Vladik Kreinovich:
Why Grade Distribution Is Often Multi-modal: An Uncertainty-Based Explanation. IFSA/NAFIPS 2019: 106-112 - [c215]Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Fuse Expert Knowledge: Not Always "And" but a Fuzzy Combination of "And" and "Or". IFSA/NAFIPS 2019: 113-120 - [c214]Francisco Zapata, Olga Kosheleva, Vladik Kreinovich:
Logarithms Are Not Infinity: A Rational Physics-Related Explanation of the Mysterious Statement by Lev Landau. IFSA/NAFIPS 2019: 746-751 - [c213]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Can We Improve the Standard Algorithm of Interval Computation by Taking Almost Monotonicity into Account? IFSA/NAFIPS 2019: 767-778