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Adversarial Causal Bayesian Optimization

A principled algorithm for causal bayesian optimization in non-stationary systems.

Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause

Safe Risk-averse Bayesian Optimization for Controller Tuning

Real-world application of risk-averse BO in safe controller tuning.

Christopher Konig, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan

Model-based Causal Bayesian Optimization

A principled algorithm for causal bayesian optimization.

Scott Sussex, Anastasiia Makarova, Andreas Krause

Automatic Termination for Hyperparameter Optimization

Bayesian optimization (BO) is a widely popular approach for the hyperparameter optimization (HPO) in machine learning. At its core, BO …

Anastasiia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias Seeger, Cedric Archambeau

Risk-averse Heteroscedastic Bayesian Optimization

Many black-box optimization tasks arising in high-stakes applications require risk-averse decisions. The standard Bayesian optimization …

Anastasiia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause

Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation

An end-to-end trainable framework that processes large-scale visual data tensors by looking at a fraction of their entries only

Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim Rakhuba, Andreas Krause, Konrad Schindler

Mixed-Variable Bayesian Optimization

Erik Daxberger, Anastasiia Makarova, Matteo Turchetta, Andreas Krause

Hierarchical Image Classification Using Entailment Cone Embeddings

Image classification has been studied extensively, but there has been limited work in using unconventional, external guidance other …

Ankit Dhall, Anastasiia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause