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Roman Vainshtein
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2020 – today
- 2024
- [j2]Itai Dagan, Roman Vainshtein
, Gilad Katz, Lior Rokach:
Automated algorithm selection using meta-learning and pre-trained deep convolution neural networks. Inf. Fusion 105: 102210 (2024) - [c5]Jonathan Brokman, Omer Hofman, Roman Vainshtein, Amit Giloni, Toshiya Shimizu, Inderjeet Singh, Oren Rachmil, Alon Zolfi, Asaf Shabtai, Yuki Unno, Hisashi Kojima:
MONTRAGE: Monitoring Training for Attribution of Generative Diffusion Models. ECCV (75) 2024: 1-17 - [i6]Shai Meital, Lior Rokach, Roman Vainshtein, Nir Grinberg:
The Branch Not Taken: Predicting Branching in Online Conversations. CoRR abs/2404.13613 (2024) - 2023
- [j1]Adva Hadrian
DeepCAN: Hybrid Method for Road Type Classification Using Vehicle Sensor Data for Smart Autonomous Mobility. IEEE Trans. Intell. Transp. Syst. 24(11): 11756-11772 (2023) - 2020
- [c4]Doron Laadan, Roman Vainshtein, Yarden Curiel, Gilad Katz, Lior Rokach:
MetaTPOT: Enhancing A Tree-based Pipeline Optimization Tool Using Meta-Learning. CIKM 2020: 2097-2100 - [c3]Yuval Heffetz, Roman Vainshtein, Gilad Katz, Lior Rokach:
DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering. KDD 2020: 2103-2113 - [i5]Sigal Shaked, Amos Zamir, Roman Vainshtein, Moshe Unger, Lior Rokach, Rami Puzis, Bracha Shapira:
Sequence Preserving Network Traffic Generation. CoRR abs/2002.09832 (2020) - [i4]Asnat Greenstein-Messica, Roman Vainshtein, Gilad Katz, Bracha Shapira, Lior Rokach:
Automatic Machine Learning Derived from Scholarly Big Data. CoRR abs/2003.03470 (2020)
2010 – 2019
- 2019
- [c2]Noy Cohen-Shapira, Lior Rokach, Bracha Shapira
AutoGRD: Model Recommendation Through Graphical Dataset Representation. CIKM 2019: 821-830 - [i3]Roman Vainshtein
Assessing the Quality of Scientific Papers. CoRR abs/1908.04200 (2019) - [i2]Yuval Heffetz, Roman Vainshtein
DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering. CoRR abs/1911.00061 (2019) - [i1]Doron Laadan, Roman Vainshtein
RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines. CoRR abs/1911.00108 (2019) - 2018
- [c1]Roman Vainshtein
A Hybrid Approach for Automatic Model Recommendation. CIKM 2018: 1623-1626
Coauthor Index
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last updated on 2024-11-11 21:31 CET by the dblp team
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