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Sebastian Pineda Arango
Sebastian Pineda Arango
在 cs.uni-freiburg.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
Transformers Can Do Bayesian Inference
S Müller, N Hollmann, SP Arango, J Grabocka, F Hutter
International Conference on Learning Representations, 2021
1072021
Chronos: Learning the language of time series
AF Ansari, L Stella, C Turkmen, X Zhang, P Mercado, H Shen, O Shchur, ...
arXiv preprint arXiv:2403.07815, 2024
392024
HPO-B: A large-scale reproducible benchmark for black-box HPO based on openml
S Pineda Arango, HS Jomaa, M Wistuba, J Grabocka
NeurIPS Datasets and Benchmarks, 2021
39*2021
Multimodal meta-learning for time series regression
SP Arango, F Heinrich, K Madhusudhanan, L Schmidt-Thieme
Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop …, 2021
162021
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
SP Arango, F Ferreira, A Kadra, F Hutter, J Grabocka
International Conference on Learning Representations, 2024
7*2024
HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning
G Shala, SP Arango, A Biedenkapp, F Hutter, J Grabocka
AutoML Conference 2024 (ABCD Track), 2024
5*2024
Deep Ranking Ensembles for Hyperparameter Optimization
AS Khazi*, S Pineda-Arango*, J Grabocka
International Conference on Learning Representations, 2023
52023
Transfer learning for bayesian hpo with end-to-end landmark meta-features
HS Jomaa, SP Arango, L Schmidt-Thieme, J Grabocka
Fifth Workshop on Meta-Learning at the Conference on Neural Information …, 2021
52021
Improving sample efficiency with normalized rbf kernels
S Pineda-Arango, D Obando-Paniagua, A Dedeoglu, P Kurzendörfer, ...
arXiv preprint arXiv:2007.15397, 2020
52020
Breaking the Paradox of Explainable Deep Learning
A Kadra, SP Arango, J Grabocka
arXiv preprint arXiv:2305.13072, 2023
22023
Deep Pipeline Embeddings for AutoML
S Pineda Arango, J Grabocka
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining …, 2023
22023
Quick-Tune-Tool: A Practical Tool and its User Guide for Automatically Finetuning Pretrained Models
I Rapant, L Purucker, F Ferreira, SP Arango, A Kadra, J Grabocka, ...
AutoML Conference 2024 (Workshop Track), 0
Bayesian Optimization with a Neural Network Meta-learned on Synthetic Data Only
S Müller, SP Arango, M Feurer, J Grabocka, F Hutter
Sixth Workshop on Meta-Learning at the Conference on Neural Information …, 0
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