global-optimization

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 158 papers with code (658 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.

• Tree Search vs Optimization Approaches for Map Generation
  27 Mar 2019 5 repositories listed
  We compare them on three different game level generation problems: Binary, Zelda, and Sokoban.
• 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.
• 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.
• A Literature Survey of Benchmark Functions For Global Optimization Problems
  19 Aug 2013 4 repositories listed
  Test functions are important to validate and compare the performance of optimization algorithms.
• FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations
  2 Feb 2023 3 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  Our formulation involves clients synthesizing a small set of samples that approximate local loss landscapes by simulating the gradients of real images within a local region.
• 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).
• Global optimization of Lipschitz functions
  7 Mar 2017 3 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  The goal of the paper is to design sequential strategies which lead to efficient optimization of an unknown function under the only assumption that it has a finite Lipschitz constant.
• Learning Geometric Transformation for Point Cloud Completion
  8 Jun 2023 2 repositories listed
  It exploits the repetitive geometric structures in common 3D objects to recover the complete shapes, which contains three sub-networks: geometric patch network, structure transformation network, and detail refinement…
• Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
  31 May 2023 2 repositories listed
  However, many of the methods used rely on general-purpose solvers for which scalability remains an issue.
• TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack
  14 Sep 2022 2 repositories listed
  Recent years have witnessed the success of recurrent neural network (RNN) models in time series classification (TSC).
• Certifiably Optimal Outlier-Robust Geometric Perception: Semidefinite Relaxations and Scalable Global Optimization
  7 Sep 2021 2 repositories listed
  Our third contribution is to solve the SDP relaxations at an unprecedented scale and accuracy by presenting STRIDE, a solver that blends global descent on the convex SDP with fast local search on the nonconvex POP.
• Document-level Event Extraction via Parallel Prediction Networks
  1 Aug 2021 2 repositories listed
  We argue that sentence-level extractors are ill-suited to the DEE task where event arguments always scatter across sentences and multiple events may co-exist in a document.
• Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure
  23 Apr 2021 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  Bayesian optimization (BO) is a popular paradigm for global optimization of expensive black-box functions, but there are many domains where the function is not completely a black-box.
• Pathwise Conditioning of Gaussian Processes
  8 Nov 2020 2 repositories listed
  As Gaussian processes are used to answer increasingly complex questions, analytic solutions become scarcer and scarcer.
• Hyperparameter Optimization via Sequential Uniform Designs
  8 Sep 2020 2 repositories listed
  Hyperparameter optimization (HPO) plays a central role in the automated machine learning (AutoML).
• Efficient Rollout Strategies for Bayesian Optimization
  24 Feb 2020 2 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Non-myopic acquisition functions consider the impact of the next h function evaluations and are typically computed through rollout, in which h steps of BO are simulated.
• BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
  14 Oct 2019 2 repositories listed
  Bayesian optimization provides sample-efficient global optimization for a broad range of applications, including automatic machine learning, engineering, physics, and experimental design.
• Slot-Gated Modeling for Joint Slot Filling and Intent Prediction
  1 Jun 2018 2 repositories listed
  Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.
• NeRF-based CBCT Reconstruction needs Normalization and Initialization
  24 Jun 2025 1 repository listed
  However, they suffer from a local-global training mismatch between their two key components: the hash encoder and the neural network.
• Focusing on Tracks for Online Multi-Object Tracking
  15 Jun 2025 1 repository listed
  Multi-object tracking (MOT) is a critical task in computer vision, requiring the accurate identification and continuous tracking of multiple objects across video frames.
• A Hybrid GA LLM Framework for Structured Task Optimization
  9 Jun 2025 1 repository listed
  GA LLM is a hybrid framework that combines Genetic Algorithms with Large Language Models to handle structured generation tasks under strict constraints.
• A Divide-and-Conquer Approach for Global Orientation of Non-Watertight Scene-Level Point Clouds Using 0-1 Integer Optimization
  29 May 2025 1 repository listed
  To reliably evaluate orientation consistency between adjacent blocks, we introduce the concept of the visible connected region, which defines the region over which visibility-based assessments are performed.
• Improving LLM-based Global Optimization with Search Space Partitioning
  27 May 2025 1 repository listed
  Large Language Models (LLMs) have recently emerged as effective surrogate models and candidate generators within global optimization frameworks for expensive blackbox functions.
• Physics-guided and fabrication-aware inverse design of photonic devices using diffusion models
  23 Apr 2025 1 repository listed
  Designing free-form photonic devices is fundamentally challenging due to the vast number of possible geometries and the complex requirements of fabrication constraints.
• SUDO: Enhancing Text-to-Image Diffusion Models with Self-Supervised Direct Preference Optimization
  20 Apr 2025 1 repository listed
  In this paper, we introduce Self-sUpervised Direct preference Optimization (SUDO), a novel paradigm that optimizes both fine-grained details at the pixel level and global image quality.
• Probability Estimation and Scheduling Optimization for Battery Swap Stations via LRU-Enhanced Genetic Algorithm and Dual-Factor Decision System
  10 Apr 2025 1 repository listed
  To address the challenges of limited Battery Swap Stations datasets, high operational costs, and fluctuating user charging demand, this research proposes a probability estimation model based on charging pile data and…
• Riemannian Optimization on Relaxed Indicator Matrix Manifold
  26 Mar 2025 1 repository listed
  The indicator matrix plays an important role in machine learning, but optimizing it is an NP-hard problem.
• FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
  20 Mar 2025 1 repository listed
  However, adaptively adjusting aggregation weights while ensuring data security-without requiring additional proxy data-remains a significant challenge.
• Island-Based Evolutionary Computation with Diverse Surrogates and Adaptive Knowledge Transfer for High-Dimensional Data-Driven Optimization
  17 Mar 2025 1 repository listed
  In the intra-island optimization phase, a semi-supervised learning method is devised to fine-tune the surrogates.

Syntology lines on 6 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.