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Olga Kosheleva
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Publications
- 2023
- [c128]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Günter Mayer:
Complex-Valued Interval Computations are NP-Hard Even for Single Use Expressions. NAFIPS 2023: 246-257 - [c126]Martine Ceberio, Vladik Kreinovich, Olga Kosheleva, Lev Ginzburg:
Faster Algorithms for Estimating the Mean of a Quadratic Expression Under Uncertainty. NAFIPS 2023: 290-300 - [c125]Palvi Aggarwal, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How People Make Decisions Based on Prior Experience: Formulas of Instance-Based Learning Theory (IBLT) Follow from Scale Invariance. NAFIPS 2023: 312-319 - [c124]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Integrity First, Service Before Self, and Excellence: Core Values of US Air Force Naturally Follow from Decision Theory. NAFIPS 2023: 320-324 - [c120]Lehel Dénes-Fazakas, László Szilágyi, György Eigner, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Which Activation Function Works Best for Training Artificial Pancreas: Empirical Fact and Its Theoretical Explanation. SSCI 2023: 496-500 - [c119]Orsolya Csiszár, Gábor Csiszár, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Fuzzy Control Is Often More Robust (and Smoother): A Theoretical Explanation. SSCI 2023: 501-505 - [p65]Martine Ceberio, Christian Servin, Olga Kosheleva, Vladik Kreinovich:
How to Best Write Research Papers: Basic English? Sophisticated English? Decision Making Under Uncertainty and Constraints 2023: 75-80 - [p62]Julio C. Urenda, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why Homogeneous Membranes Lead to Optimal Water Desalination: A Possible Explanation. Decision Making Under Uncertainty and Constraints 2023: 89-92 - [p36]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
How to Describe Relative Approximation Error? A New Justification for Gustafson's Logarithmic Expression. Uncertainty, Constraints, and Decision Making 2023: 323-327 - [p34]Juan Carlos Figueroa García, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Estimating Skewness and Higher Central Moments of an Interval-Valued Fuzzy Set. Uncertainty, Constraints, and Decision Making 2023: 345-352 - [p31]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
An Argument in Favor of Piecewise-Constant Membership Functions. Uncertainty, Constraints, and Decision Making 2023: 377-386 - [p30]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Data Processing Under Fuzzy Uncertainty: Towards More Accurate Algorithms. Uncertainty, Constraints, and Decision Making 2023: 387-399 - [p29]Marina Tuyako Mizukoshi, Weldon A. Lodwick, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Epistemic Versus Aleatory: Case of Interval Uncertainty. Uncertainty, Constraints, and Decision Making 2023: 401-421 - 2022
- [j53]Jonatan M. Contreras, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Why neural networks in the first place: a theoretical explanation. J. Intell. Fuzzy Syst. 43(6): 6947-6951 (2022) - 2021
- [c108]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 - 2020
- [c99]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 - [c94]Jonatan M. Contreras, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich, Martine Ceberio:
Let Us Use Negative Examples in Regression-Type Problems Too. IV 2020: 296-300 - [c89]Leobardo Valera, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Equations for Which Newton's Method Never Works: Pedagogical Examples. NAFIPS 2020: 413-419 - [c88]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Optimal Search Under Constraints. NAFIPS 2020: 421-426 - [c87]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 - [p27]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Italian Folk Multiplication Algorithm Is Indeed Better: It Is More Parallelizable. Decision Making under Constraints 2020: 59-64 - [p26]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Reverse Mathematics Is Computable for Interval Computations. Decision Making under Constraints 2020: 65-70 - [p25]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 - [p24]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 - 2019
- [c81]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 - [c80]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 - [c75]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 - 2015
- [c39]Martine Ceberio, Leobardo Valera, Olga Kosheleva, Rodrigo Romero:
Model reduction: Why it is possible and how it can potentially help to control swarms of Unmanned Arial Vehicles (UAVs). NAFIPS/WConSC 2015: 1-6 - 2014
- [p7]Martine Ceberio, Olga Kosheleva, Vladik Kreinovich:
Simplicity Is Worse Than Theft: A Constraint-Based Explanation of a Seemingly Counter-Intuitive Russian Saying. Constraint Programming and Decision Making 2014: 9-13 - [p6]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Why Tensors? Constraint Programming and Decision Making 2014: 75-78 - [p5]Olga Kosheleva, Martine Ceberio, Vladik Kreinovich:
Adding Constraints - A (Seemingly Counterintuitive but) Useful Heuristic in Solving Difficult Problems. Constraint Programming and Decision Making 2014: 79-83 - [p4]Karen Villaverde, Olga Kosheleva, Martine Ceberio:
Why Ellipsoid Constraints, Ellipsoid Clusters, and Riemannian Space-Time: Dvoretzky's Theorem Revisited. Constraint Programming and Decision Making 2014: 203-207 - 2010
- [c19]Olga Kosheleva, Martine Ceberio:
Why polynomial formulas in soft computing, decision making, etc.? FUZZ-IEEE 2010: 1-5
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