Bayesian Optimization

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Datasets archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 686 papers with code (1,900 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
  21 Mar 2016 17 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  Performance of machine learning algorithms depends critically on identifying a good set of hyperparameters.
• A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
  12 Dec 2010 15 repositories listed Syntology ran 0 of 16 samples · 16 unverified
  We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions.
• Auto-Keras: An Efficient Neural Architecture Search System
  27 Jun 2018 13 repositories listed Syntology ran 3 of 6 samples · 3 unverified
  In this paper, we propose a novel framework enabling Bayesian optimization to guide the network morphism for efficient neural architecture search.
• The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development
  22 May 2019 8 repositories listed
  To address these problems, we introduce the Machine Learning Bazaar, a new framework for developing machine learning and automated machine learning software systems.
• A Tutorial on Bayesian Optimization
  8 Jul 2018 7 repositories listed Syntology ran 2 of 10 samples · 8 unverified
  It builds a surrogate for the objective and quantifies the uncertainty in that surrogate using a Bayesian machine learning technique, Gaussian process regression, and then uses an acquisition function defined from this…
• MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements
  5 Dec 2020 5 repositories listed
  Instead of sampling configurations randomly in HB, BOHB samples configurations based on a BO surrogate model, which is constructed with the high-fidelity measurements only.
• Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization
  13 Oct 2021 4 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  We consider the problem of black-box multi-objective optimization (MOO) using expensive function evaluations (also referred to as experiments), where the goal is to approximate the true Pareto set of solutions by…
• Pre-trained Gaussian Processes for Bayesian Optimization
  16 Sep 2021 4 repositories listed Syntology ran 3 of 14 samples · 11 unverified · 2 pointer-only (licence)
  Contrary to a common expectation that BO is suited to optimizing black-box functions, it actually requires domain knowledge about those functions to deploy BO successfully.
• BOHB: Robust and Efficient Hyperparameter Optimization at Scale
  4 Jul 2018 4 repositories listed
  Modern deep learning methods are very sensitive to many hyperparameters, and, due to the long training times of state-of-the-art models, vanilla Bayesian hyperparameter optimization is typically computationally…
• Differentiable Compositional Kernel Learning for Gaussian Processes
  12 Jun 2018 4 repositories listed Syntology ran 1 of 15 samples · 14 unverified
  The NKN architecture is based on the composition rules for kernels, so that each unit of the network corresponds to a valid kernel.
• SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties
  6 Dec 2017 4 repositories listed
  Chemical databases store information in text representations, and the SMILES format is a universal standard used in many cheminformatics software.
• Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
  11 May 2017 4 repositories listed
  Computational models in fields such as computational neuroscience are often evaluated via stochastic simulation or numerical approximation.
• mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions
  9 Mar 2017 4 repositories listed
  We present mlrMBO, a flexible and comprehensive R toolbox for model-based optimization (MBO), also known as Bayesian optimization, which addresses the problem of expensive black-box optimization by approximating the…
• Max-value Entropy Search for Efficient Bayesian Optimization
  6 Mar 2017 4 repositories listed
  We propose a new criterion, Max-value Entropy Search (MES), that instead uses the information about the maximum function value.
• Grammar Variational Autoencoder
  6 Mar 2017 4 repositories listed Syntology ran 4 of 19 samples · 15 unverified · 3 pointer-only (licence)
  Crucially, state-of-the-art methods often produce outputs that are not valid.
• Scalable Bayesian Optimization Using Deep Neural Networks
  19 Feb 2015 4 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Bayesian optimization is an effective methodology for the global optimization of functions with expensive evaluations.
• Practical Bayesian Optimization of Machine Learning Algorithms
  13 Jun 2012 4 repositories listed
  In this work, we consider the automatic tuning problem within the framework of Bayesian optimization, in which a learning algorithm's generalization performance is modeled as a sample from a Gaussian process (GP).
• Bayesian Optimization with High-Dimensional Outputs
  24 Jun 2021 3 repositories listed Syntology ran 5 of 18 samples · 13 unverified · 1 pointer-only (licence)
  However, the Gaussian Process (GP) models typically used as probabilistic surrogates for multi-task Bayesian Optimization scale poorly with the number of outcomes, greatly limiting applicability.
• Local policy search with Bayesian optimization
  22 Jun 2021 3 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  We develop an algorithm utilizing a probabilistic model of the objective function and its gradient.
• IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
  8 Jul 2020 3 repositories listed
  An R programming interface is provided for users preferring to have a finer control over the implemented functionalities.
• Combinatorial 3D Shape Generation via Sequential Assembly
  16 Apr 2020 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  To alleviate this consequence induced by a huge number of feasible combinations, we propose a combinatorial 3D shape generation framework.
• Model-based Asynchronous Hyperparameter and Neural Architecture Search
  24 Mar 2020 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We introduce a model-based asynchronous multi-fidelity method for hyperparameter and neural architecture search that combines the strengths of asynchronous Hyperband and Gaussian process-based Bayesian optimization.
• BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
  25 Oct 2019 3 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  Bayesian optimization (BO), which has long had success in hyperparameter optimization, has recently emerged as a very promising strategy for NAS when it is coupled with a neural predictor.
• Scalable Global Optimization via Local Bayesian Optimization
  3 Oct 2019 3 repositories listed
  This motivates the design of a local probabilistic approach for global optimization of large-scale high-dimensional problems.
• pySOT and POAP: An event-driven asynchronous framework for surrogate optimization
  30 Jul 2019 3 repositories listed
  This paper describes Plumbing for Optimization with Asynchronous Parallelism (POAP) and the Python Surrogate Optimization Toolbox (pySOT).
• Deep Bayesian Optimization on Attributed Graphs
  31 May 2019 3 repositories listed Syntology ran 8 of 18 samples · 10 unverified
  Attributed graphs, which contain rich contextual features beyond just network structure, are ubiquitous and have been observed to benefit various network analytics applications.
• Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
  8 Feb 2019 3 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  In order to scale the method and keep its benefits, we propose an algorithm (LineBO) that restricts the problem to a sequence of iteratively chosen one-dimensional sub-problems that can be solved efficiently.
• Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search
  18 Jul 2018 3 repositories listed Syntology ran 2 of 10 samples · 8 unverified
  While existing work on neural architecture search (NAS) tunes hyperparameters in a separate post-processing step, we demonstrate that architectural choices and other hyperparameter settings interact in a way that can…
• Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics
  14 Feb 2016 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  While an initial guess for the parameters may be obtained from dynamic models of the robot, parameters are usually tuned manually on the real system to achieve the best performance.
• LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms
  27 May 2025 2 repositories listed
  Bayesian optimization (BO) is a powerful class of algorithms for optimizing expensive black-box functions, but designing effective BO algorithms remains a manual, expertise-driven task.

Syntology lines on 18 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.