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black-box optimization

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Test Development Learning Exchange
Test Development Learning Exchange
Apr 4, 2024 · Artificial Intelligence

Scikit‑Optimize (skopt): Features, Use Cases, and Code Examples

Scikit‑Optimize is a Python library for black‑box optimization that offers adaptable, efficient algorithms, hyper‑parameter tuning, interactive monitoring, and seamless Scikit‑Learn integration, illustrated with five comprehensive code examples covering basic usage, constrained and interactive optimization, and visualization.

Bayesian Optimizationblack-box optimizationhyperparameter tuning
0 likes · 7 min read
Scikit‑Optimize (skopt): Features, Use Cases, and Code Examples
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Nov 11, 2022 · Artificial Intelligence

Language Model as a Service and Black‑Box Optimization: Insights from Prof. Qiu Xipeng’s Talk

Prof. Qiu Xipeng’s talk highlighted how large language models can be offered as a service and efficiently adapted via in‑context learning, lightweight label‑tuning, and gradient‑free black‑box optimization, showcasing a unified asymmetric Transformer (CPT) that handles understanding, generation, ABSA and NER tasks while reducing resource demands.

LLMNLPY‑Tuning
0 likes · 15 min read
Language Model as a Service and Black‑Box Optimization: Insights from Prof. Qiu Xipeng’s Talk
Dada Group Technology
Dada Group Technology
Jun 9, 2017 · Artificial Intelligence

Deep Reinforcement Learning: Concepts, Black‑Box Optimization, and the Cross‑Entropy Method

This article introduces reinforcement learning and deep reinforcement learning, explains key algorithms such as DQN and policy gradients, discusses black‑box optimization and the cross‑entropy method, and provides resources and code examples for further study.

Artificial IntelligenceDQNblack-box optimization
0 likes · 7 min read
Deep Reinforcement Learning: Concepts, Black‑Box Optimization, and the Cross‑Entropy Method