Accepted Papers
Poster Session 1
Contributed Talk: Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
Jack Parker-Holder, Vu Nguyen and Stephen Roberts.
MTL2L: A Context Aware Neural Optimiser
Nicholas Kuo, Mehrtash Harandi, Nicolas Fourrier, Christian Walder, Gabriela Ferraro and Hanna Suominen.
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data
Nick Erickson, Jonas Mueller, Alexander Shirkov, Pedro Larroy, Mu Li and Alex Smola.
Cost-aware Bayesian Optimization
Eric Lee, Valerio Perrone, Cedric Archambeau and Matthias Seeger.
Multi-Source Unsupervised Hyperparameter Optimization
Masahiro Nomura and Yuta Saito.
Regression Networks for Meta-Learning Few-Shot Classification
Arnout Devos and Matthias Grossglauser.
Mining Documentation to Extract Hyperparameter Schemas
Guillaume Baudart, Peter Kirchner, Martin Hirzel and Kiran Kate.
Tiny Video Networks: Architecture Search for Efficient Video Models
Aj Piergiovanni, Anelia Angelova and Michael Ryoo.
Solving Heterogeneous AutoML Problems with AutoGOAL
Suilan Estevez-Velarde, Alejandro Piad-Morffis, Yoan Gutierrez, Andrés Montoyo, Rafael Muñoz and Yudivian Almeida-Cruz.
Bayesian Optimization for Iterative Learning
Vu Nguyen, Sebastian Schulze and Michael Osborne.
Weighted Meta-Learning
Diana Cai, Rishit Sheth, Lester Mackey and Nicolo Fusi.
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization
Sauptik Dhar, Unmesh Kurup and Mohak Shah.
Solving Constrained CASH Problems with ADMM
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz and Alexander Gray.
A Study on Encodings for Neural Architecture Search
Colin White, Willie Neiswanger, Sam Nolen and Yash Savani.
Multi-fidelity zero-shot HPO
Fela Winkelmolen, Nikita Ivkin, H. Furkan Bozkurt and Zohar Karnin.
Analysis of Imbalance Strategies Recommendation using a Meta-Learning Approach
Afonso José Costa, Miriam Seoane Santos, Carlos Soares and Pedro Henriques Abreu.
Learning to Prune Deep Neural Networks via Reinforcement Learning
Manas Gupta, Siddharth Aravindan, Aleksandra Kalisz, Vijay Chandrasekhar and Lin Jie.
W-EDGE: Weight Updating in Directed Graph Ensembles to improve Classification
Xavier Fontes, Daniel Castro Silva and Pedro Henriques Abreu.
Toward Synergism in Macro Action Ensembles
Yu-Ming Chen, Kuan-Yu Chang, Chien Liu, Tsu-Ching Hsiao, Zhang-Wei Hong and Chun-Yi Lee.
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
Carlos Medina, Arnout Devos and Matthias Grossglauser.
Poster Session 2
Contributed Talk: Bayesian Optimization with Fairness Constraints
Valerio Perrone, Michele Donini, Krishnaram Kenthapadi and Cédric Archambeau.
Contributed Talk: How far are we from true AutoML: reflection from winning solutions and results of AutoDL challenge
Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Isabelle Guyon, Julio C. S. Jacques Junior, Meysam Madadi and Sebastien Treguer.
Federated Meta-Learning: Democratizing Algorithm Selection Across Disciplines and Software Libraries
Mukesh Arambakam and Joeran Beel.
Towards Algorithm-Agnostic Uncertainty Estimation: Predicting Classification Error in an Automated Machine Learning Setting
Matthias König, Holger Hoos and Jan N. van Rijn.
Local Search is State of the Art for NAS Benchmarks
Colin White, Sam Nolen and Yash Savani.
Geometric Dataset Distances via Optimal Transport
David Alvarez Melis and Nicolo Fusi.
Collecting Empirical Data About Hyperparameters for Data Driven AutoML
Martin Binder, Florian Pfisterer and Bernd Bischl.
Meta-Learning for Recalibration of EMG-Based Upper Limb Prostheses
Krsto Proroković, Michael Wand and Jürgen Schmidhuber.
A Simple Setting for Understanding Neural Architecture Search with Weight-Sharing
Mikhail Khodak, Liam Li, Nicholas Roberts, Maria-Florina Balcan and Ameet Talwalkar.
Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient
Yufei Wang and Tianwei Ni.
‘Algorithm-Performance Personas’ for Siamese Meta-Learning and Automated Algorithm Selection
Bryan Tyrrell, Edward Bergman, Gareth Jones and Joeran Beel.
Uncertainty aware Search framework for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria, Aryan Deshwal and Janardhan Rao Doppa.
Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters
Sulin Liu, Xingyuan Sun, Peter Ramadge and Ryan Adams.
Bayesian Optimization for real-time, automatic design of face-stimuli in human-centred research
Pedro F da Costa, Romy Lorenz, Ricardo Pio Monti, Emily Jones and Robert Leech.
On Evaluation of AutoML Systems
Mitar Milutinovic, Brandon Schoenfeld, Diego Martinez-Garcia, Saswati Ray, Sujen Shah and David Yan.
H2O AutoML: Scalable Automatic Machine Learning
Erin Ledell and Sebastien Poirier.
RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow
Samuel Glass, Simeon Spasov and Pietro Lio.