« Back to top page

Real World Problem

Real World Problem

HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

Abstract Hyperparameter optimization benchmark introduced in the paper HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. The original benchmark is available here. Please note that this benchmark provides the results only at the last epoch of each configuration. APIs class Problem(dataset_id: int, seed: int | None = None, metric_names: list[str] | None = None) dataset_id: ID of the dataset to use. It must be in the range of [0, 7].

HPOLib: Tabular Benchmarks for Hyperparameter Optimization and Neural Architecture Search

Abstract Hyperparameter optimization benchmark introduced in the paper Tabular Benchmarks for Hyperparameter Optimization and Neural Architecture Search. The original benchmark is available here. Please note that this benchmark provides the results only at the last epoch of each configuration. APIs class Problem(dataset_id: int, seed: int | None = None, metric_names: list[str] | None = None) dataset_id: ID of the dataset to use. It must be in the range of [0, 3].

Multi-dimensional Knapsack Problem

Abstract The Multi-dimensional Knapsack Problem (MKP) is a fundamental combinatorial optimization problem that generalizes the classic knapsack problem to multiple dimensions. In this problem, each item has multiple attributes (e.g., weight, volume, size) and the goal is to maximize the total value of selected items while satisfying constraints on each attribute. Despite its conceptual simplicity, the MKP is NP-hard and appears frequently in real-world applications, such as resource allocation, capital budgeting, and project selection, as remarked in recent surveys e.

NATS-Bench (NAS-Bench-201): Benchmarking NAS Algorithms for Architecture Topology and Size

Abstract Neural architecture search benchmark introduced in the paper NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size. The original benchmark is available here. Please note that this benchmark provides the results only at the last epoch of each architecture. The preliminary version is the NAS-Bench-201, but since the widely used name is NAS-Bench-201, we stick to the name, NAS-Bench-201 APIs class Problem(dataset_id: int, seed: int | None = None, metric_names: list[str] | None = None) dataset_id: ID of the dataset to use.