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Maxim Buzdalov 0001
Maxim V. Buzdalov
Person information
- affiliation: Aberystwyth University, UK
- affiliation: ITMO University, St. Petersburg, Russia
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2020 – today
- 2024
- [j5]Denis Antipov
, Maxim Buzdalov
Lazy Parameter Tuning and Control: Choosing All Parameters Randomly from a Power-Law Distribution. Algorithmica 86(2): 442-484 (2024) - [c81]Aidan Walden, Maxim Buzdalov:
A Simple Statistical Test Against Origin-Biased Metaheuristics. EvoApplications@EvoStar 2024: 322-337 - [i18]Maxim Buzdalov, Pavel Martynov, Sergey Pankratov, Vitaly Aksenov, Stefan Schmid
In the Search of Optimal Tree Networks: Hardness and Heuristics. CoRR abs/2403.03724 (2024) - 2023
- [c80]Deyao Chen
Using Automated Algorithm Configuration for Parameter Control. FOGA 2023: 38-49 - [c79]Maxim Buzdalov
Improving Time and Memory Efficiency of Genetic Algorithms by Storing Populations as Minimum Spanning Trees of Patches. GECCO Companion 2023: 1873-1881 - [i17]Deyao Chen, Maxim Buzdalov, Carola Doerr, Nguyen Dang
Using Automated Algorithm Configuration for Parameter Control. CoRR abs/2302.12334 (2023) - [i16]Maxim Buzdalov:
Improving Time and Memory Efficiency of Genetic Algorithms by Storing Populations as Minimum Spanning Trees of Patches. CoRR abs/2306.16686 (2023) - 2022
- [j4]Denis Antipov
Fast Mutation in Crossover-Based Algorithms. Algorithmica 84(6): 1724-1761 (2022) - [j3]Maxim Buzdalov
Fixed-Target Runtime Analysis. Algorithmica 84(6): 1762-1793 (2022) - [c78]Maxim Buzdalov
The $(1+(\lambda, \lambda))$ Genetic Algorithm on the Vertex Cover Problem: Crossover Helps Leaving Plateaus. CEC 2022: 1-10 - [c77]Dmitry Vinokurov, Maxim Buzdalov
On optimal static and dynamic parameter choices for fixed-target optimization. GECCO 2022: 876-883 - [c76]Dmitry Vinokurov
Towards Fixed-Target Black-Box Complexity Analysis. PPSN (2) 2022: 600-611 - 2021
- [j2]Anton O. Bassin
The "One-Fifth Rule" with Rollbacks for Self-Adjustment of the Population Size in the (1 + (λ, λ)) Genetic Algorithm. Autom. Control. Comput. Sci. 55(7): 885-902 (2021) - [c75]Kirill Antonov, Maxim Buzdalov
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CEC 2021: 878-885 - [c74]Sumit Mishra
Labeling-oriented non-dominated sorting is Θ(MN3). GECCO Companion 2021: 189-190 - [c73]Maxim Buzdalov, Carola Doerr:
Optimal static mutation strength distributions for the (1 + λ) evolutionary algorithm on OneMax. GECCO 2021: 660-668 - [c72]Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
Lazy parameter tuning and control: choosing all parameters randomly from a power-law distribution. GECCO 2021: 1115-1123 - [i15]Maxim Buzdalov, Carola Doerr:
Optimal Static Mutation Strength Distributions for the (1+λ) Evolutionary Algorithm on OneMax. CoRR abs/2102.04944 (2021) - [i14]Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr:
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CoRR abs/2102.11461 (2021) - [i13]Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
Lazy Parameter Tuning and Control: Choosing All Parameters Randomly From a Power-Law Distribution. CoRR abs/2104.06714 (2021) - 2020
- [c71]Maxim Buzdalov, Sergey A. Kolyubin
Optimizing Robotic Cheetah Leg Parameters Using Evolutionary Algorithms. BIOMA 2020: 214-227 - [c70]Sumit Mishra
Time complexity analysis of the dominance degree approach for non-dominated sorting. GECCO Companion 2020: 169-170 - [c69]Sumit Mishra
If unsure, shuffle: deductive sort is Θ(MN3), but O(MN2) in expectation over input permutations. GECCO 2020: 516-523 - [c68]Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
Fast mutation in crossover-based algorithms. GECCO 2020: 1268-1276 - [c67]Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-target runtime analysis. GECCO 2020: 1295-1303 - [c66]Anton O. Bassin, Maxim Buzdalov:
The (1 + (λ, λ)) genetic algorithm for permutations. GECCO Companion 2020: 1669-1677 - [c65]Denis Antipov, Maxim Buzdalov
First Steps Towards a Runtime Analysis When Starting with a Good Solution. PPSN (2) 2020: 560-573 - [c64]Maxim Buzdalov
Optimal Mutation Rates for the (1+λ ) EA on OneMax. PPSN (2) 2020: 574-587 - [c63]Sumit Mishra
Filter Sort Is $\varOmega (N^3)$ in the Worst Case. PPSN (2) 2020: 675-685 - [i12]Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
Fast Mutation in Crossover-based Algorithms. CoRR abs/2004.06538 (2020) - [i11]Anton O. Bassin, Maxim Buzdalov:
The $(1+(λ, λ))$ Genetic Algorithm for Permutations. CoRR abs/2004.08664 (2020) - [i10]Maxim Buzdalov, Benjamin Doerr, Carola Doerr, Dmitry Vinokurov:
Fixed-Target Runtime Analysis. CoRR abs/2004.09613 (2020) - [i9]Maxim Buzdalov, Carola Doerr:
Optimal Mutation Rates for the (1+λ) EA on OneMax. CoRR abs/2006.11457 (2020) - [i8]Denis Antipov, Maxim Buzdalov, Benjamin Doerr:
First Steps Towards a Runtime Analysis When Starting With a Good Solution. CoRR abs/2006.12161 (2020)
2010 – 2019
- 2019
- [c62]Maxim Buzdalov:
Make Evolutionary Multiobjective Algorithms Scale Better with Advanced Data Structures: Van Emde Boas Tree for Non-dominated Sorting. EMO 2019: 66-77 - [c61]Vladimir Mironovich
Permutation Encoding for Automatic Reconstruction of Connections in Closed-Loop Control System using Evolutionary Algorithm. ETFA 2019: 1265-1268 - [c60]Anton O. Bassin, Maxim Buzdalov:
The 1/5-th rule with rollbacks: on self-adjustment of the population size in the (1 + (λ, λ)) GA. GECCO (Companion) 2019: 277-278 - [c59]Artem Pavlenko
Fitness comparison by statistical testing in construction of SAT-based guess-and-determine cryptographic attacks. GECCO 2019: 312-320 - [c58]Nina Bulanova, Maxim Buzdalov:
Black-box complexity of the binary value function. GECCO (Companion) 2019: 423-424 - [c57]Maxim Buzdalov:
Generalized incremental orthant search: towards efficient steady-state evolutionary multiobjective algorithms. GECCO (Companion) 2019: 1357-1365 - [c56]Maxim Buzdalov:
Towards better estimation of statistical significance when comparing evolutionary algorithms. GECCO (Companion) 2019: 1782-1788 - [c55]Ivan Ignashov, Arina Buzdalova
Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper. GECCO (Companion) 2019: 1807-1812 - [c54]Nina Bulanova, Maxim Buzdalov:
Limited memory, limited arity unbiased black-box complexity: first insights. GECCO (Companion) 2019: 2020-2023 - [c53]Dmitry Vinokurov
Fixed-target runtime analysis of the (1 + 1) EA with resampling. GECCO (Companion) 2019: 2068-2071 - [i7]Nina Bulanova, Maxim Buzdalov:
Black-Box Complexity of the Binary Value Function. CoRR abs/1904.04867 (2019) - [i6]Anton O. Bassin, Maxim Buzdalov:
The 1/5-th Rule with Rollbacks: On Self-Adjustment of the Population Size in the (1+(λ, λ)) GA. CoRR abs/1904.07284 (2019) - 2018
- [c52]Vladimir Mironovich
Automatic Plant-Controller Input/Output Matching using Evolutionary Algorithms. ETFA 2018: 1043-1046 - [c51]Ilya Yakupov, Maxim Buzdalov:
On asynchronous non-dominated sorting for steady-state multiobjective evolutionary algorithms. GECCO (Companion) 2018: 205-206 - [c50]Nina Bulanova, Maxim Buzdalov:
Better fixed-arity unbiased black-box algorithms. GECCO (Companion) 2018: 322-323 - [c49]Maxim Buzdalov:
Generalized offline orthant search: one code for many problems in multiobjective optimization. GECCO 2018: 593-600 - [c48]Vladimir Mironovich
From fitness landscape analysis to designing evolutionary algorithms: the case study in automatic generation of function block applications. GECCO (Companion) 2018: 1902-1905 - [c47]Margarita Markina, Maxim Buzdalov:
Towards Large-Scale Multiobjective Optimisation with a Hybrid Algorithm for Non-dominated Sorting. PPSN (1) 2018: 347-358 - [i5]Ilya Yakupov, Maxim Buzdalov:
On Asynchronous Non-Dominated Sorting for Steady-State Multiobjective Evolutionary Algorithms. CoRR abs/1804.05208 (2018) - [i4]Nina Bulanova, Maxim Buzdalov:
Better Fixed-Arity Unbiased Black-Box Algorithms. CoRR abs/1804.05443 (2018) - 2017
- [c46]Maxim Buzdalov, Benjamin Doerr, Mikhail Kever:
The unrestricted black-box complexity of jump functions. GECCO (Companion) 2017: 1-2 - [c45]Margarita Markina, Maxim Buzdalov:
Hybridizing non-dominated sorting algorithms: divide-and-conquer meets best order sort. GECCO (Companion) 2017: 153-154 - [c44]Ilya Yakupov, Maxim Buzdalov:
Improved incremental non-dominated sorting for steady-state evolutionary multiobjective optimization. GECCO 2017: 649-656 - [c43]Maxim Buzdalov, Benjamin Doerr:
Runtime analysis of the (1 + (λ, λ)) genetic algorithm on random satisfiable 3-CNF formulas. GECCO 2017: 1343-1350 - [c42]Nina Bulanova, Maxim Buzdalov:
On binary unbiased operators returning multiple offspring. GECCO (Companion) 2017: 1395-1398 - [c41]Vladimir Mironovich
Evaluation of heavy-tailed mutation operator on maximum flow test generation problem. GECCO (Companion) 2017: 1423-1426 - [c40]Vladimir Mironovich
Automatic generation of function block applications using evolutionary algorithms: Initial explorations. INDIN 2017: 700-705 - [i3]Margarita Markina, Maxim Buzdalov:
Hybridizing Non-dominated Sorting Algorithms: Divide-and-Conquer Meets Best Order Sort. CoRR abs/1704.04205 (2017) - [i2]Maxim Buzdalov, Benjamin Doerr:
Runtime Analysis of the (1+(λ, λ)) Genetic Algorithm on Random Satisfiable 3-CNF Formulas. CoRR abs/1704.04366 (2017) - 2016
- [j1]Maxim Buzdalov, Benjamin Doerr, Mikhail Kever:
The Unrestricted Black-Box Complexity of Jump Functions. Evol. Comput. 24(4): 719-744 (2016) - [c39]Nina Bulanova, Arina Buzdalova
Fitness-Dependent Hybridization of Clonal Selection Algorithm and Random Local Search. GECCO (Companion) 2016: 5-6 - [c38]Maxim Buzdalov:
An Algorithm for Computing Lower Bounds for Unrestricted Black-Box Complexities. GECCO (Companion) 2016: 147-148 - [c37]Andrey Vasin, Maxim Buzdalov:
A Faster Algorithm for the Binary Epsilon Indicator Based on Orthant Minimum Search. GECCO 2016: 613-620 - [c36]Maxim Buzdalov:
GECCO'16 Workshop on Algorithms and Data Structures for Evolutionary Computation Chairs' Welcome. GECCO (Companion) 2016: 1111 - [c35]Niyaz Nigmatullin, Maxim Buzdalov, Andrey Stankevich:
Efficient Removal of Points with Smallest Crowding Distance in Two-dimensional Incremental Non-dominated Sorting. GECCO (Companion) 2016: 1121-1128 - [c34]Arina Buzdalova
Runtime analysis of different Approaches to select conflicting auxiliary objectives in the generalized OneMax problem. SSCI 2016: 1-7 - [c33]Tatyana Polevaya
Preserving diversity in auxiliary objectives provably speeds up crossing plateaus. SSCI 2016: 1-8 - 2015
- [c32]Maxim Buzdalov
Can OneMax help optimizing LeadingOnes using the EA+RL method? CEC 2015: 1762-1768 - [c31]Maxim Buzdalov
Analysis of Q-learning with random exploration for selection of auxiliary objectives in random local search. CEC 2015: 1776-1783 - [c30]Ilya Yakupov
Incremental non-dominated sorting with O(N) insertion for the two-dimensional case. CEC 2015: 1853-1860 - [c29]Maxim Buzdalov
Hard test generation for augmenting path maximum flow algorithms using genetic algorithms: Revisited. CEC 2015: 2121-2128 - [c28]Denis Antipov
Runtime Analysis of (1+1) Evolutionary Algorithm Controlled with Q-learning Using Greedy Exploration Strategy on OneMax+ZeroMax Problem. EvoCOP 2015: 160-172 - [c27]Maxim Buzdalov
Upper and Lower Bounds on Unrestricted Black-Box Complexity of Jump _n, ℓ. EvoCOP 2015: 209-221 - [c26]Maxim Buzdalov
Fast Implementation of the Steady-State NSGA-II Algorithm for Two Dimensions Based on Incremental Non-Dominated Sorting. GECCO 2015: 647-654 - [c25]Maxim Buzdalov
Various Degrees of Steadiness in NSGA-II and Their Influence on the Quality of Results. GECCO (Companion) 2015: 749-750 - [c24]Vladimir Mironovich
Hard Test Generation for Maximum Flow Algorithms with the Fast Crossover-Based Evolutionary Algorithm. GECCO (Companion) 2015: 1229-1232 - [c23]Viktor Arkhipov, Maxim Buzdalov
An Asynchronous Implementation of the Limited Memory CMA-ES. ICMLA 2015: 707-712 - [i1]Viktor Arkhipov, Maxim Buzdalov, Anatoly Shalyto:
An Asynchronous Implementation of the Limited Memory CMA-ES. CoRR abs/1510.00419 (2015) - 2014
- [c22]Maxim Buzdalov, Anatoly Shalyto:
Worst-Case Execution Time Test Generation for Solutions of the Knapsack Problem Using a Genetic Algorithm. BIC-TA 2014: 1-10 - [c21]Maxim Buzdalov
Onemax helps optimizing XdivK: : theoretical runtime analysis for RLS and EA+RL. GECCO (Companion) 2014: 201-202 - [c20]Arina Buzdalova
Selecting evolutionary operators using reinforcement learning: initial explorations. GECCO (Companion) 2014: 1033-1036 - [c19]Maxim Buzdalov
NSGA-II implementation details may influence quality of solutions for the job-shop scheduling problem. GECCO (Companion) 2014: 1445-1446 - [c18]Mikhail Lukin, Maxim Buzdalov, Anatoly Shalyto:
Formal Verification of 800 Genetically Constructed Automata Programs: A Case Study. Haifa Verification Conference 2014: 165-170 - [c17]Maxim Buzdalov
Protein Conformation Motion Modeling Using Sep-CMA-ES. ICMLA 2014: 35-40 - [c16]Maxim Buzdalov
A Switch-and-Restart Algorithm with Exponential Restart Strategy for Objective Selection and its Runtime Analysis. ICMLA 2014: 141-146 - [c15]Irina Petrova
Improved Selection of Auxiliary Objectives Using Reinforcement Learning in Non-stationary Environment. ICMLA 2014: 580-583 - [c14]Arina Buzdalova
A New Algorithm for Adaptive Online Selection of Auxiliary Objectives. ICMLA 2014: 584-587 - [c13]Maxim Buzdalov, Anatoly Shalyto:
A Provably Asymptotically Fast Version of the Generalized Jensen Algorithm for Non-dominated Sorting. PPSN 2014: 528-537 - 2013
- [c12]Maxim Buzdalov
Adaptive selection of helper-objectives for test case generation. IEEE Congress on Evolutionary Computation 2013: 2245-2250 - [c11]Maxim Buzdalov
Generation of tests for programming challenge tasks using multi-objective optimization. GECCO (Companion) 2013: 1655-1658 - [c10]Viktor Arkhipov, Maxim Buzdalov
Worst-Case Execution Time Test Generation for Augmenting Path Maximum Flow Algorithms Using Genetic Algorithms. ICMLA (2) 2013: 108-111 - [c9]Maxim Buzdalov
A First Step towards the Runtime Analysis of Evolutionary Algorithm Adjusted with Reinforcement Learning. ICMLA (1) 2013: 203-208 - [c8]Irina Petrova
Improved Helper-Objective Optimization Strategy for Job-Shop Scheduling Problem. ICMLA (2) 2013: 374-377 - [c7]Arina Buzdalova
Generation of Tests for Programming Challenge Tasks Using Helper-Objectives. SSBSE 2013: 300-305 - 2012
- [c6]Maxim Buzdalov
Evolving EFSMs solving a path-planning problem by genetic programming. GECCO (Companion) 2012: 591-594 - [c5]Maxim Buzdalov
Generation of Tests for Programming Challenge Tasks on Graph Theory Using Evolution Strategy. ICMLA (2) 2012: 62-65 - [c4]Arina Buzdalova
Adaptive Selection of Helper-Objectives with Reinforcement Learning. ICMLA (2) 2012: 66-67 - [c3]Arina Buzdalova
Increasing Efficiency of Evolutionary Algorithms by Choosing between Auxiliary Fitness Functions with Reinforcement Learning. ICMLA (1) 2012: 150-155 - 2011
- [c2]Maxim Buzdalov
Generation of tests for programming challenge tasks using evolution algorithms. GECCO (Companion) 2011: 763-766 - [c1]Arina Afanasyeva
Choosing Best Fitness Function with Reinforcement Learning. ICMLA (2) 2011: 354-357
Coauthor Index
Arina Buzdalova
aka: Arina Afanasyeva
aka: Arina Afanasyeva
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last updated on 2024-08-05 20:21 CEST by the dblp team
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