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Pawel Liskowski
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2020 – today
- 2024
- [i4]Lukasz Borchmann, Michal Pietruszka, Wojciech Jaskowski, Dawid Jurkiewicz, Piotr Halama, Pawel Józiak, Lukasz Garncarek, Pawel Liskowski, Karolina Szyndler, Andrzej Gretkowski, Julita Oltusek, Gabriela Nowakowska, Artur Zawlocki, Lukasz Duhr, Pawel Dyda, Michal Turski:
Arctic-TILT. Business Document Understanding at Sub-Billion Scale. CoRR abs/2408.04632 (2024) - 2023
- [i3]Nihat Engin Toklu, Timothy Atkinson, Vojtech Micka, Pawel Liskowski, Rupesh Kumar Srivastava:
EvoTorch: Scalable Evolutionary Computation in Python. CoRR abs/2302.12600 (2023) - 2020
- [c19]Pawel Liskowski, Krzysztof Krawiec
, Nihat Engin Toklu, Jerry Swan:
Program synthesis as latent continuous optimization: evolutionary search in neural embeddings. GECCO 2020: 359-367 - [c18]Nihat Engin Toklu, Pawel Liskowski
ClipUp: A Simple and Powerful Optimizer for Distribution-Based Policy Evolution. PPSN (2) 2020: 515-527 - [c17]Pawel Liskowski, Krzysztof Krawiec
Neuromemetic Evolutionary Optimization. PPSN (1) 2020: 623-636 - [i2]Nihat Engin Toklu, Pawel Liskowski, Rupesh Kumar Srivastava:
ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolution. CoRR abs/2008.02387 (2020)
2010 – 2019
- 2018
- [j4]Pawel Liskowski
Learning to Play Othello With Deep Neural Networks. IEEE Trans. Games 10(4): 354-364 (2018) - [c16]Pawel Liskowski, Bartosz Wieloch
Neural estimation of interaction outcomes. GECCO 2018: 1055-1062 - [c15]Pawel Liskowski, Iwo Bladek
Neuro-guided genetic programming: prioritizing evolutionary search with neural networks. GECCO 2018: 1143-1150 - 2017
- [j3]Pawel Liskowski, Krzysztof Krawiec
Online Discovery of Search Objectives for Test-Based Problems. Evol. Comput. 25(3): 375-406 (2017) - [c14]Pawel Liskowski, Wojciech Jaskowski
Accelerating coevolution with adaptive matrix factorization. GECCO 2017: 457-464 - [c13]Pawel Liskowski, Krzysztof Krawiec
Discovery of search objectives in continuous domains. GECCO 2017: 969-976 - [i1]Pawel Liskowski, Wojciech Jaskowski, Krzysztof Krawiec:
Learning to Play Othello with Deep Neural Networks. CoRR abs/1711.06583 (2017) - 2016
- [j2]Wojciech Jaskowski, Pawel Liskowski, Marcin Grzegorz Szubert, Krzysztof Krawiec
The performance profile: A multi-criteria performance evaluation method for test-based problems. Int. J. Appl. Math. Comput. Sci. 26(1): 215 (2016) - [j1]Pawel Liskowski
Segmenting Retinal Blood Vessels With Deep Neural Networks. IEEE Trans. Medical Imaging 35(11): 2369-2380 (2016) - [c12]Pawel Liskowski, Krzysztof Krawiec
Surrogate Fitness via Factorization of Interaction Matrix. EuroGP 2016: 68-82 - [c11]Pawel Liskowski, Krzysztof Krawiec
Online Discovery of Search Objectives for Test-based Problems. GECCO (Companion) 2016: 163-164 - [c10]Pawel Liskowski, Krzysztof Krawiec
Non-negative Matrix Factorization for Unsupervised Derivation of Search Objectives in Genetic Programming. GECCO 2016: 749-756 - 2015
- [c9]Krzysztof Krawiec
Automatic Derivation of Search Objectives for Test-Based Genetic Programming. EuroGP 2015: 53-65 - [c8]Marcin Grzegorz Szubert, Wojciech Jaskowski, Pawel Liskowski, Krzysztof Krawiec
The Role of Behavioral Diversity and Difficulty of Opponents in Coevolving Game-Playing Agents. EvoApplications 2015: 394-405 - [c7]Wojciech Jaskowski, Marcin Grzegorz Szubert, Pawel Liskowski, Krzysztof Krawiec
High-Dimensional Function Approximation for Knowledge-Free Reinforcement Learning: a Case Study in SZ-Tetris. GECCO 2015: 567-573 - [c6]Pawel Liskowski, Krzysztof Krawiec
Comparison of Semantic-aware Selection Methods in Genetic Programming. GECCO (Companion) 2015: 1301-1307 - 2014
- [c5]Wojciech Jaskowski
Multi-Criteria Comparison of Coevolution and Temporal Difference Learning on Othello. EvoApplications 2014: 301-312 - [c4]Pawel Liskowski, Krzysztof Krawiec
Discovery of Implicit Objectives by Compression of Interaction Matrix in Test-Based Problems. PPSN 2014: 611-620 - 2013
- [c3]Wojciech Jaskowski
Improving coevolution by random sampling. GECCO 2013: 1141-1148 - [c2]Marcin Grzegorz Szubert, Wojciech Jaskowski
Shaping fitness function for evolutionary learning of game strategies. GECCO 2013: 1149-1156 - [c1]Pawel Liskowski:
Quantitative analysis of the hall of fame coevolutionary archives. GECCO (Companion) 2013: 1683-1686
Coauthor Index
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last updated on 2024-09-14 23:51 CEST by the dblp team
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