Denis Antipov

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 42

Top Topics

Theoretical And Empirical Study

Evolutionary Algorithm

Population Size

Top Venues

Publications

Denis Antipov, Benjamin Doerr, Alexandra Ivanova
Already Moderate Population Sizes Provably Yield Strong Robustness to Noise. GECCO (2024)
Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann
Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem. GECCO (2024)
Denis Antipov, Aneta Neumann, Frank Neumann
A Detailed Experimental Analysis of Evolutionary Diversity Optimization for OneMinMax. GECCO (2024)
Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann
Effective 2- and 3-Objective MOEA/D Approaches for the Chance Constrained Knapsack Problem. GECCO (2024)
Denis Antipov, Aneta Neumann, Frank Neumann, Andrew M. Sutton
Runtime Analysis of Evolutionary Diversity Optimization on the Multi-objective (LeadingOnes, TrailingZeros) Problem. CoRR (2024)
Denis Antipov, Benjamin Doerr, Alexandra Ivanova
Already Moderate Population Sizes Provably Yield Strong Robustness to Noise. CoRR (2024)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Lazy Parameter Tuning and Control: Choosing All Parameters Randomly from a Power-Law Distribution. Algorithmica 86 (2) (2024)
Denis Antipov, Aneta Neumann, Frank Neumann
Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential. CoRR (2024)
Ishara Hewa Pathiranage, Frank Neumann, Denis Antipov, Aneta Neumann
Using 3-Objective Evolutionary Algorithms for the Dynamic Chance Constrained Knapsack Problem. CoRR (2024)
Denis Antipov, Aneta Neumann, Frank Neumann
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax. CoRR (2023)
Denis Antipov, Aneta Neumann, Frank Neumann
Rigorous Runtime Analysis of Diversity Optimization with GSEMO on OneMinMax. FOGA (2023)
Alexandra Ivanova, Denis Antipov, Benjamin Doerr
Larger Offspring Populations Help the (1 + (λ, λlambda)) Genetic Algorithm to Overcome the Noise. GECCO (2023)
Alexandra Ivanova, Denis Antipov, Benjamin Doerr
Larger Offspring Populations Help the (1 + (λ, λ)) Genetic Algorithm to Overcome the Noise. CoRR (2023)
Aneta Neumann, Denis Antipov, Frank Neumann
Coevolutionary Pareto diversity optimization. GECCO (2022)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Fast Mutation in Crossover-Based Algorithms. Algorithmica 84 (6) (2022)
Denis Antipov, Benjamin Doerr
Precise runtime analysis for plateau functions: (hot-off-the-press track at GECCO 2022). GECCO Companion (2022)
Aneta Neumann, Denis Antipov, Frank Neumann
Coevolutionary Pareto Diversity Optimization. CoRR (2022)
Denis Antipov, Benjamin Doerr, Vitalii Karavaev
A Rigorous Runtime Analysis of the (1 + (λ , λ )) GA on Jump Functions. Algorithmica 84 (6) (2022)
Denis Antipov, Benjamin Doerr
A Tight Runtime Analysis for the (μ + λ ) EA. Algorithmica 83 (4) (2021)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Lazy Parameter Tuning and Control: Choosing All Parameters Randomly From a Power-Law Distribution. CoRR (2021)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Lazy parameter tuning and control: choosing all parameters randomly from a power-law distribution. GECCO (2021)
Denis Antipov, Benjamin Doerr
Precise Runtime Analysis for Plateau Functions. ACM Trans. Evol. Learn. Optim. 1 (4) (2021)
Matvey Shnytkin, Denis Antipov
The lower bounds on the runtime of the (1 + (λ, λ)) GA on the minimum spanning tree problem. GECCO Companion (2021)
Denis Antipov, Semen Naumov
The effect of non-symmetric fitness: the analysis of crossover-based algorithms on RealJump functions. FOGA (2021)
Denis Antipov, Benjamin Doerr
Runtime Analysis of a Heavy-Tailed (1+(λ, λ)) Genetic Algorithm on Jump Functions. CoRR (2020)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Fast Mutation in Crossover-based Algorithms. CoRR (2020)
Denis Antipov, Benjamin Doerr, Vitalii Karavaev
The (1 + (λ, λ)) GA Is Even Faster on Multimodal Problems. CoRR (2020)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
First Steps Towards a Runtime Analysis When Starting With a Good Solution. CoRR (2020)
Denis Antipov, Benjamin Doerr, Vitalii Karavaev
)) GA is even faster on multimodal problems. GECCO (2020)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Fast mutation in crossover-based algorithms. GECCO (2020)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
First Steps Towards a Runtime Analysis When Starting with a Good Solution. PPSN (2) (2020)
Denis Antipov, Benjamin Doerr
Runtime Analysis of a Heavy-Tailed (1+(λ , λ )) Genetic Algorithm on Jump Functions. PPSN (2) (2020)
Vitalii Karavaev, Denis Antipov, Benjamin Doerr
Theoretical and empirical study of the (1 + (λ, λ)) EA on the leadingones problem. GECCO (Companion) (2019)
Denis Antipov, Benjamin Doerr, Quentin Yang
) EA. GECCO (2019)
Denis Antipov, Benjamin Doerr, Vitalii Karavaev
A tight runtime analysis for the (1 + (λ, λ)) GA on leadingones. FOGA (2019)
Denis Antipov, Benjamin Doerr, Quentin Yang
The Efficiency Threshold for the Offspring Population Size of the (μ, λ) EA. CoRR (2019)
Denis Antipov, Benjamin Doerr, Jiefeng Fang, Tangi Hetet
A tight runtime analysis for the (μ + λ) EA. GECCO (2018)
Denis Antipov, Benjamin Doerr
Precise Runtime Analysis for Plateaus. CoRR (2018)
Denis Antipov, Arina Buzdalova, Andrew Stankevich
Runtime analysis of a population-based evolutionary algorithm with auxiliary objectives selected by reinforcement learning. GECCO (Companion) (2018)
Denis Antipov, Benjamin Doerr
Precise Runtime Analysis for Plateaus. PPSN (2) (2018)
Denis Antipov, Benjamin Doerr
A Tight Runtime Analysis for the (μ+ λ) EA. CoRR (2018)
Denis Antipov, Arina Buzdalova
Runtime Analysis of Random Local Search on JUMP function with Reinforcement Based Selection of Auxiliary Objectives. CEC (2017)
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
Runtime Analysis of (1+1) Evolutionary Algorithm Controlled with Q-learning Using Greedy Exploration Strategy on OneMax+ZeroMax Problem. EvoCOP (2015)