Decoupled Weight Decay Regularization I Loshchilov, F Hutter International Conference on Learning Representations (ICLR 2019), 2018 | 23784* | 2018 |
SGDR: stochastic gradient descent with warm restarts I Loshchilov, F Hutter International Conference on Learning Representations (ICLR 2017), 2016 | 9141 | 2016 |
A downsampled variant of imagenet as an alternative to the cifar datasets P Chrabaszcz, I Loshchilov, F Hutter arXiv preprint arXiv:1707.08819, 2017 | 684 | 2017 |
CMA-ES for Hyperparameter Optimization of Deep Neural Networks I Loshchilov, F Hutter International Conference on Learning Representations (ICLR 2016). Workshop …, 2016 | 392 | 2016 |
Online batch selection for faster training of neural networks I Loshchilov, F Hutter International Conference on Learning Representations (ICLR 2016). Workshop …, 2015 | 330 | 2015 |
CMA-ES with restarts for solving CEC 2013 benchmark problems I Loshchilov 2013 IEEE Congress on Evolutionary Computation, 369-376, 2013 | 173 | 2013 |
Back to basics: Benchmarking canonical evolution strategies for playing atari P Chrabaszcz, I Loshchilov, F Hutter arXiv preprint arXiv:1802.08842, 2018 | 132 | 2018 |
Comparison-based optimizers need comparison-based surrogates I Loshchilov, M Schoenauer, M Sebag Parallel Problem Solving from Nature–PPSN XI, 364-373, 2011 | 129 | 2011 |
RoboGen: Robot Generation through Artificial Evolution JE Auerbach, D Aydin, A Maesani, PM Kornatowski, T Cieslewski, G Heitz, ... ALIFE 14: The Fourteenth Conference on the Synthesis and Simulation of …, 2014 | 127 | 2014 |
A mono surrogate for multiobjective optimization I Loshchilov, M Schoenauer, M Sebag Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 115 | 2010 |
Self-adaptive surrogate-assisted covariance matrix adaptation evolution strategy I Loshchilov, M Schoenauer, M Sebag Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 108 | 2012 |
A Computationally Efficient Limited Memory CMA-ES for Large Scale Optimization I Loshchilov Proceeding of the sixteenth annual conference on Genetic and Evolutionary …, 2014 | 105 | 2014 |
Large scale black-box optimization by limited-memory matrix adaptation I Loshchilov, T Glasmachers, HG Beyer IEEE Transactions on Evolutionary Computation 23 (2), 353-358, 2018 | 94* | 2018 |
BI-population CMA-ES Algorithms with Surrogate Models and Line Searches I Loshchilov, M Schoenauer, M Sebag BBOB workshop of Genetic and Evolutionary Computation Conference (GECCO 2013), 2013 | 84 | 2013 |
Evolutionary computation for wind farm layout optimization D Wilson, S Rodrigues, C Segura, I Loshchilov, F Hutter, GL Buenfil, ... Renewable energy 126, 681-691, 2018 | 83 | 2018 |
LM-CMA: an Alternative to L-BFGS for Large Scale Black-box Optimization I Loshchilov Evolutionary computation, MIT Press, 2015 | 72 | 2015 |
Adaptive coordinate descent I Loshchilov, M Schoenauer, M Sebag Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011 | 71 | 2011 |
Alternative restart strategies for CMA-ES I Loshchilov, M Schoenauer, M Sebag International Conference on Parallel Problem Solving from Nature, 296-305, 2012 | 52 | 2012 |
Intensive Surrogate Model Exploitation in Self-adaptive Surrogate-assisted CMA-ES (saACM-ES) I Loshchilov, M Schoenauer, M Sebag Proceeding of the fifteenth annual conference on Genetic and evolutionary …, 2013 | 51 | 2013 |
Dominance-based pareto-surrogate for multi-objective optimization I Loshchilov, M Schoenauer, M Sebag Simulated Evolution and Learning, 230-239, 2010 | 48 | 2010 |