Sebastian Pineda-Arango

According to our database, Sebastian Pineda-Arango authored at least 11 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Ensembling Finetuned Language Models for Text Classification.

Sebastian Pineda-Arango, Maciej Janowski, Lennart Purucker, Arber Zela, Frank Hutter, Josif Grabocka

CoRR, 2024

Dynamic Post-Hoc Neural Ensemblers.

Sebastian Pineda-Arango, Maciej Janowski, Lennart Purucker, Arber Zela, Frank Hutter, Josif Grabocka

CoRR, 2024

Chronos: Learning the Language of Time Series.

Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Türkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda-Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang

CoRR, 2024

Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How.

Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Breaking the Paradox of Explainable Deep Learning.

Arlind Kadra, Sebastian Pineda-Arango, Josif Grabocka

CoRR, 2023

Deep Pipeline Embeddings for AutoML.

Sebastian Pineda-Arango, Josif Grabocka

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Deep Ranking Ensembles for Hyperparameter Optimization.

Abdus Salam Khazi, Sebastian Pineda-Arango, Josif Grabocka

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Transformers Can Do Bayesian Inference.

Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML.

Sebastian Pineda-Arango, Hadi S. Jomaa, Martin Wistuba, Josif Grabocka

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Multimodal Meta-Learning for Time Series Regression.

Sebastian Pineda-Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2021

2020

Improving Sample Efficiency with Normalized RBF Kernels.

Sebastian Pineda-Arango, David Obando-Paniagua, Alperen Dedeoglu, Philip Kurzendörfer, Friedemann Schestag, Randolf Scholz

CoRR, 2020