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Laxman Bokati
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2020 – today
- 2023
- [j6]Woraphon Yamaka, Laxman Bokati:
Why Markov Switching Models Work Well: An Explanation. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 31(Supplement-2): 265-271 (2023) - [p3]Laxman Bokati, Vladik Kreinovich, Joseph Baca, Natasha Rovelli:
Why Rectified Power (RePU) Activation Functions are Efficient in Deep Learning: A Theoretical Explanation. Uncertainty, Constraints, and Decision Making 2023: 7-13 - [p2]Laxman Bokati, Olga Kosheleva, Vladik Kreinovich:
Why Rarity Score Is a Good Evaluation of a Non-Fungible Token. Uncertainty, Constraints, and Decision Making 2023: 69-74 - [p1]Laxman Bokati, Vladik Kreinovich:
Why Time Seems to Pass Slowly for Unpleasant Experiences and Quickly for Pleasant Experiences: An Explanation Based on Decision Theory. Uncertainty, Constraints, and Decision Making 2023: 257-261 - 2022
- [j5]Solymar Ayala Cortez, Laxman Bokati, Aaron Velasco, Vladik Kreinovich:
Why Daubechies wavelets are so successful. J. Intell. Fuzzy Syst. 43(6): 6933-6938 (2022) - [c9]Laxman Bokati, Vladik Kreinovich:
Why Smaller-Size Objects Affect the Flow Much More than Larger Ones: A Geometric Explanation with Applications Ranging from Volcanoes and Tornadoes to Blood, Fish, and Buildings Preservation. IS 2022: 1-4 - [c8]Laxman Bokati, Vladik Kreinovich:
Why Exponential Almon Lag Works Well in Econometrics: An Invariance-Based Explanation. IS 2022: 1-4 - [c7]Laxman Bokati, Olga Kosheleva, Vladik Kreinovich:
How to Elicit Complex-Valued Fuzzy Degrees. NAFIPS 2022: 1-11 - 2021
- [j4]Supanika Leurcharusmee, Laxman Bokati, Olga Kosheleva:
Why linear expressions in discounting and in empathy: a symmetry-based explanation. Soft Comput. 25(12): 7753-7759 (2021) - [c6]Laxman Bokati, Olga Kosheleva, Vladik Kreinovich:
How Much for a Set: General Case of Decision Making Under Set-Valued Uncertainty. NAFIPS 2021: 52-61 - [c5]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
- [j3]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) - [j2]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) - [c4]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 - [c3]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
2010 – 2019
- 2019
- [j1]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) - [c2]Oscar Galindo, Laxman Bokati, Vladik Kreinovich:
Towards a More Efficient Representation of Functions in Quantum and Reversible Computing. EUSFLAT Conf. 2019 - [c1]Bartlomiej Jacek Kubica, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich:
Softmax and McFadden's Discrete Choice Under Interval (and Other) Uncertainty. PPAM (2) 2019: 364-373
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