9.4k citations · 11.7k across the 21 of their papers we have counts for
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Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari
Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter
Evolution Strategies (ES) have recently been demonstrated to be a viable alternative to reinforcement learning (RL) algorithms on a set of challenging deep RL problems, including A…
Limited-Memory Matrix Adaptation for Large Scale Black-box Optimization
Ilya Loshchilov, Tobias Glasmachers, Hans-Georg Beyer
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a popular method to deal with nonconvex and/or stochastic optimization problems when the gradient information is not…
Anytime Bi-Objective Optimization with a Hybrid Multi-Objective CMA-ES (HMO-CMA-ES)
Ilya Loshchilov, Tobias Glasmachers
We propose a multi-objective optimization algorithm aimed at achieving good anytime performance over a wide range of problems. Performance is assessed in terms of the hypervolume m…
LM-CMA: an Alternative to L-BFGS for Large Scale Black-box Optimization
Ilya Loshchilov
The limited memory BFGS method (L-BFGS) of Liu and Nocedal (1989) is often considered to be the method of choice for continuous optimization when first- and/or second- order inform…
Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag +1
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimiza…
A Computationally Efficient Limited Memory CMA-ES for Large Scale Optimization
Ilya Loshchilov
We propose a computationally efficient limited memory Covariance Matrix Adaptation Evolution Strategy for large scale optimization, which we call the LM-CMA-ES. The LM-CMA-ES is a…
Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
In this paper, we study the performance of IPOP-saACM-ES and BIPOP-saACM-ES, recently proposed self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution Strategies. B…
Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
In this paper, we study the performance of IPOP-saACM-ES, recently proposed self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution Strategy. The algorithm was test…
Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy
Ilya Loshchilov, Marc Schoenauer, Michèle Sebag
This paper presents a novel mechanism to adapt surrogate-assisted population-based algorithms. This mechanism is applied to ACM-ES, a recently proposed surrogate-assisted variant o…