Martin Wistuba

According to our database1, Martin Wistuba authored at least 69 papers between 2011 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Continual Learning with Low Rank Adaptation.
CoRR, 2023

Renate: A Library for Real-World Continual Learning.
CoRR, 2023

Deep Power Laws for Hyperparameter Optimization.
CoRR, 2023

Scaling Laws for Hyperparameter Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PASHA: Efficient HPO and NAS with Progressive Resource Allocation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Variational Boosted Soft Trees.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Memory Efficient Continual Learning for Neural Text Classification.
CoRR, 2022

Dynamic and Efficient Gray-Box Hyperparameter Optimization for Deep Learning.
CoRR, 2022

Supervising the Multi-Fidelity Race of Hyperparameter Configurations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Memory Efficient Continual Learning with Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Continual Learning with Transformers for Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research.
Proceedings of the International Conference on Automated Machine Learning, 2022

Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Comprehensive Survey on Hardware-Aware Neural Architecture Search.
CoRR, 2021

HPO-B: A Large-Scale Reproducible Benchmark for Black-Box HPO based on OpenML.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Hardware-Aware Neural Architecture Search: Survey and Taxonomy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Few-Shot Bayesian Optimization with Deep Kernel Surrogates.
Proceedings of the 9th International Conference on Learning Representations, 2021

Automated Data Science for Relational Data.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

AutoText: An End-to-End AutoAI Framework for Text.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Searching for Machine Learning Pipelines Using a Context-Free Grammar.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
XferNAS: Transfer Neural Architecture Search.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Automation of Deep Learning - Theory and Practice.
Proceedings of the 2020 on International Conference on Multimedia Retrieval, 2020

Survey on Automated End-to-End Data Science?
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Learning to Rank Learning Curves.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
How can AI Automate End-to-End Data Science?
CoRR, 2019

A Survey on Neural Architecture Search.
CoRR, 2019

Inductive Transfer for Neural Architecture Optimization.
CoRR, 2019

NeuNetS: An Automated Synthesis Engine for Neural Network Design.
CoRR, 2019

Scalable Large Margin Gaussian Process Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Optimal Exploitation of Clustering and History Information in Multi-armed Bandit.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Automated Machine Learning - Bayesian Optimization, Meta-Learning & Applications.
PhD thesis, 2018

Scalable Gaussian process-based transfer surrogates for hyperparameter optimization.
Mach. Learn., 2018

Adversarial Robustness Toolbox v0.2.2.
CoRR, 2018

Automated Image Data Preprocessing with Deep Reinforcement Learning.
CoRR, 2018

Scalable Multi-Class Bayesian Support Vector Machines for Structured and Unstructured Data.
CoRR, 2018

Learning Features For Relational Data.
CoRR, 2018

Deep Learning Architecture Search by Neuro-Cell-Based Evolution with Function-Preserving Mutations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Practical Deep Learning Architecture Optimization.
Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

2017
Finding Competitive Network Architectures Within a Day Using UCT.
CoRR, 2017

Adversarial Phenomenon in the Eyes of Bayesian Deep Learning.
CoRR, 2017

Automatic Frankensteining: Creating Complex Ensembles Autonomously.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Bayesian Optimization Combined with Successive Halving for Neural Network Architecture Optimization.
Proceedings of the International Workshop on Automatic Selection, 2017

Personalized Tag Recommendation for Images Using Deep Transfer Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Multi-Plant Photovoltaic Energy Forecasting Challenge with Regression Tree Ensembles and Hourly Average Forecasts.
Proceedings of the ECML/PKDD Discovery Challenges co-located with European Conference on Machine Learning, 2017

Personalized Deep Learning for Tag Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

2016
Fast classification of univariate and multivariate time series through shapelet discovery.
Knowl. Inf. Syst., 2016

Bank Card Usage Prediction Exploiting Geolocation Information.
CoRR, 2016

Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Scalable Hyperparameter Optimization with Products of Gaussian Process Experts.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Hyperparameter Optimization Machines.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Learning DTW-Shapelets for Time-Series Classification.
Proceedings of the 3rd IKDD Conference on Data Science, 2016

2015
Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials.
IEEE Trans. Knowl. Data Eng., 2015

Ultra-Fast Shapelets for Time Series Classification.
CoRR, 2015

Scalable Discovery of Time-Series Shapelets.
CoRR, 2015

Learning Data Set Similarities for Hyperparameter Optimization Initializations.
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015

Hyperparameter Search Space Pruning - A New Component for Sequential Model-Based Hyperparameter Optimization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Hyperparameter Optimization with Factorized Multilayer Perceptrons.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Geo_ML @ MediaEval Placing Task 2015.
Proceedings of the Working Notes Proceedings of the MediaEval 2015 Workshop, 2015

Joint Model Choice and Hyperparameter Optimization with Factorized Multilayer Perceptrons.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

Sequential Model-Free Hyperparameter Tuning.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Learning hyperparameter optimization initializations.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

2014
Learning time-series shapelets.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Minimal Invasive Integration of Learning Analytics Services in Intelligent Tutoring Systems.
Proceedings of the IEEE 14th International Conference on Advanced Learning Technologies, 2014

2013
Time-Series Classification Through Histograms of Symbolic Polynomials.
CoRR, 2013

Supervised Clustering of Social Media Streams.
Proceedings of the MediaEval 2013 Multimedia Benchmark Workshop, 2013

Move Prediction in Go - Modelling Feature Interactions Using Latent Factors.
Proceedings of the KI 2013: Advances in Artificial Intelligence, 2013

Factorized Decision Trees for Active Learning in Recommender Systems.
Proceedings of the 25th IEEE International Conference on Tools with Artificial Intelligence, 2013

2012
Comparison of Bayesian move prediction systems for Computer Go.
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

2011


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