Josif Grabocka

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 59

Top Topics

Multivariate Time Series

Top Venues

Publications

Gresa Shala, André Biedenkapp, Josif Grabocka
Hierarchical Transformers are Efficient Meta-Reinforcement Learners. CoRR (2024)
Guri Zabërgja, Arlind Kadra, Josif Grabocka
Tabular Data: Is Attention All You Need? CoRR (2024)
Rhea Sanjay Sukthanker, Arber Zela, Benedikt Staffler, Samuel Dooley, Josif Grabocka, Frank Hutter
Multi-objective Differentiable Neural Architecture Search. CoRR (2024)
Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How. ICLR (2024)
Sebastian Pineda-Arango, Josif Grabocka
Deep Pipeline Embeddings for AutoML. CoRR (2023)
Sebastian Pineda-Arango, Josif Grabocka
Deep Pipeline Embeddings for AutoML. KDD (2023)
Arlind Kadra, Sebastian Pineda-Arango, Josif Grabocka
Breaking the Paradox of Explainable Deep Learning. CoRR (2023)
Abdus Salam Khazi, Sebastian Pineda-Arango, Josif Grabocka
Deep Ranking Ensembles for Hyperparameter Optimization. ICLR (2023)
Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka
Scaling Laws for Hyperparameter Optimization. NeurIPS (2023)
Sebastian Pineda-Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How. CoRR (2023)
Gresa Shala, Thomas Elsken, Frank Hutter, Josif Grabocka
Transfer NAS with Meta-learned Bayesian Surrogates. ICLR (2023)
Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka
Gray-Box Gaussian Processes for Automated Reinforcement Learning. ICLR (2023)
Arlind Kadra, Maciej Janowski, Martin Wistuba, Josif Grabocka
Deep Power Laws for Hyperparameter Optimization. CoRR (2023)
Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
Phantom Embeddings: Using Embedding Space for Model Regularization in Deep Neural Networks. CoRR (2023)
Abdus Salam Khazi, Sebastian Pineda-Arango, Josif Grabocka
Deep Ranking Ensembles for Hyperparameter Optimization. CoRR (2023)
Martin Wistuba, Arlind Kadra, Josif Grabocka
Dynamic and Efficient Gray-Box Hyperparameter Optimization for Deep Learning. CoRR (2022)
Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
Zero-Shot AutoML with Pretrained Models. CoRR (2022)
Martin Wistuba, Arlind Kadra, Josif Grabocka
Supervising the Multi-Fidelity Race of Hyperparameter Configurations. NeurIPS (2022)
Ekrem Öztürk, Fabio Ferreira, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka, Frank Hutter
Zero-shot AutoML with Pretrained Models. ICML (2022)
Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter
Transformers Can Do Bayesian Inference. ICLR (2022)
Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Dataset2Vec: learning dataset meta-features. Data Min. Knowl. Discov. 35 (3) (2021)
Michael Ruchte, Josif Grabocka
Scalable Pareto Front Approximation for Deep Multi-Objective Learning. ICDM (2021)
Sebastian Pineda-Arango, Hadi S. Jomaa, Martin Wistuba, Josif Grabocka
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML. NeurIPS Datasets and Benchmarks (2021)
Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka
Well-tuned Simple Nets Excel on Tabular Datasets. NeurIPS (2021)
Arlind Kadra, Marius Lindauer, Frank Hutter, Josif Grabocka
Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data. CoRR (2021)
Shayan Jawed, Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Multi-task Learning Curve Forecasting Across Hyperparameter Configurations and Datasets. ECML/PKDD (1) (2021)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
A Guided Learning Approach for Item Recommendation via Surrogate Loss Learning. SIGIR (2021)
Michael Ruchte, Josif Grabocka
Multi-task problems are not multi-objective. CoRR (2021)
Hadi S. Jomaa, Lars Schmidt-Thieme, Josif Grabocka
Hyperparameter Optimization with Differentiable Metafeatures. CoRR (2021)
Martin Wistuba, Josif Grabocka
Few-Shot Bayesian Optimization with Deep Kernel Surrogates. CoRR (2021)
Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter
Transformers Can Do Bayesian Inference. CoRR (2021)
Michael Ruchte, Josif Grabocka
Efficient Multi-Objective Optimization for Deep Learning. CoRR (2021)
Sebastian Pineda-Arango, Hadi S. Jomaa, Martin Wistuba, Josif Grabocka
HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML. CoRR (2021)
Martin Wistuba, Josif Grabocka
Few-Shot Bayesian Optimization with Deep Kernel Surrogates. ICLR (2021)
Shayan Jawed, Josif Grabocka, Lars Schmidt-Thieme
Self-supervised Learning for Semi-supervised Time Series Classification. PAKDD (1) (2020)
Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
HIDRA: Head Initialization across Dynamic targets for Robust Architectures. SDM (2020)
Mofassir ul Islam Arif, Mohsan Jameel, Josif Grabocka, Lars Schmidt-Thieme
Phantom Embeddings: Using Embeddings Space for Model Regularization in Deep Neural Networks. LWDA (2020)
Ahmed Rashed, Shayan Jawed, Jens Rehberg, Josif Grabocka, Lars Schmidt-Thieme, Andre Hintsches
A Deep Multi-task Approach for Residual Value Forecasting. ECML/PKDD (3) (2019)
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
Dataset2Vec: Learning Dataset Meta-Features. CoRR (2019)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
Attribute-aware non-linear co-embeddings of graph features. RecSys (2019)
Vijaya Krishna Yalavarthi, Josif Grabocka, Hareesh Mandalapu, Lars Schmidt-Thieme
Gait Verification using Deep Learning with a Pairwise Loss. BIOSIG (2019)
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
Hyp-RL : Hyperparameter Optimization by Reinforcement Learning. CoRR (2019)
Lukas Brinkmeyer, Rafael Rêgo Drumond, Randolf Scholz, Josif Grabocka, Lars Schmidt-Thieme
Chameleon: Learning Model Initializations Across Tasks With Different Schemas. CoRR (2019)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
Weighted Personalized Factorizations for Network Classification with Approximated Relation Weights. ICAART (Revised Selected Papers) (2019)
Hadi Samer Jomaa, Josif Grabocka, Lars Schmidt-Thieme, Alexander Borek
A Hybrid Convolutional Approach for Parking Availability Prediction. IJCNN (2019)
Hadi S. Jomaa, Josif Grabocka, Lars Schmidt-Thieme
In Hindsight: A Smooth Reward for Steady Exploration. CoRR (2019)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings. KDD (2019)
Shayan Jawed, Eya Boumaiza, Josif Grabocka, Lars Schmidt-Thieme
Data-Driven Vehicle Trajectory Forecasting. CoRR (2019)
Josif Grabocka, Randolf Scholz, Lars Schmidt-Thieme
Learning Surrogate Losses. CoRR (2019)
Rafael Rêgo Drumond, Lukas Brinkmeyer, Josif Grabocka, Lars Schmidt-Thieme
HIDRA: Head Initialization across Dynamic targets for Robust Architectures. CoRR (2019)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
Multi-Label Network Classification via Weighted Personalized Factorizations. CoRR (2019)
Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme
Multi-Label Network Classification via Weighted Personalized Factorizations. ICAART (2) (2019)
Mohsan Jameel, Josif Grabocka, Mofassir ul Islam Arif, Lars Schmidt-Thieme
Ring-Star: A Sparse Topology for Faster Model Averaging in Decentralized Parallel SGD. PKDD/ECML Workshops (1) (2019)
Josif Grabocka, Lars Schmidt-Thieme
NeuralWarp: Time-Series Similarity with Warping Networks. CoRR (2018)
Hanh T. H. Nguyen, Martin Wistuba, Josif Grabocka, Lucas Rêgo Drumond, Lars Schmidt-Thieme
Personalized Deep Learning for Tag Recommendation. PAKDD (1) (2017)
Dripta S. Raychaudhuri, Josif Grabocka, Lars Schmidt-Thieme
Channel masking for multivariate time series shapelets. CoRR (2017)
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
Fast classification of univariate and multivariate time series through shapelet discovery. Knowl. Inf. Syst. 49 (2) (2016)
Mit Shah, Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
Learning DTW-Shapelets for Time-Series Classification. CODS (2016)
Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme
Latent Time-Series Motifs. ACM Trans. Knowl. Discov. Data 11 (1) (2016)
Martin Wistuba, Josif Grabocka, Lars Schmidt-Thieme
Ultra-Fast Shapelets for Time Series Classification. CoRR (2015)
Josif Grabocka, Lars Schmidt-Thieme
Learning Through Non-linearly Supervised Dimensionality Reduction. Trans. Large Scale Data Knowl. Centered Syst. 17 (2015)
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials. IEEE Trans. Knowl. Data Eng. 27 (6) (2015)
Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme
Optimal Time-Series Motifs. CoRR (2015)
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
Scalable Discovery of Time-Series Shapelets. CoRR (2015)
Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme
Supervised Nonlinear Factorizations Excel In Semi-supervised Regression. PAKDD (1) (2014)
Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme
Learning time-series shapelets. KDD (2014)
Josif Grabocka, Lars Schmidt-Thieme
Invariant time-series factorization. Data Min. Knowl. Discov. 28 (5-6) (2014)
Josif Grabocka, Alexandros Dalkalitsis, Athanasios Lois, Evangelos Katsaros, Lars Schmidt-Thieme
Realistic optimal policies for energy-efficient train driving. ITSC (2014)
Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme
Time-Series Classification Through Histograms of Symbolic Polynomials. CoRR (2013)
Josif Grabocka, Lars Schmidt-Thieme
Invariant Factorization Of Time-Series. CoRR (2013)
Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme
Supervised Dimensionality Reduction via Nonlinear Target Estimation. DaWaK (2013)
Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme
Classification of Sparse Time Series via Supervised Matrix Factorization. AAAI (2012)
Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme
Efficient Classification of Long Time-Series. ICT Innovations (2012)
Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme
Invariant Time-Series Classification. ECML/PKDD (2) (2012)