#bayesian-optimization News & Analysis

3 articles tagged with #bayesian-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · 6d ago7/10

🧠

AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent

AgentOpt v0.1, a new Python framework, addresses client-side optimization for AI agents by intelligently allocating models, tools, and API budgets across pipeline stages. Using search algorithms like Arm Elimination and Bayesian Optimization, the tool reduces evaluation costs by 24-67% while achieving near-optimal accuracy, with cost differences between model combinations reaching up to 32x at matched performance levels.

AIBullisharXiv – CS AI · 6d ago6/10

🧠

EmoMAS: Emotion-Aware Multi-Agent System for High-Stakes Edge-Deployable Negotiation with Bayesian Orchestration

Researchers introduce EmoMAS, a Bayesian multi-agent framework that enables small language models to perform sophisticated negotiation by treating emotional intelligence as a strategic variable. The system coordinates game-theoretic, reinforcement learning, and psychological agents to optimize negotiation outcomes while maintaining privacy through edge deployment, demonstrating performance comparable to larger models across high-stakes domains.

AIBullisharXiv – CS AI · Mar 27/1019

🧠

Thompson Sampling via Fine-Tuning of LLMs

Researchers developed ToSFiT (Thompson Sampling via Fine-Tuning), a new Bayesian optimization method that uses fine-tuned large language models to improve search efficiency in complex discrete spaces. The approach eliminates computational bottlenecks by directly parameterizing reward probabilities and demonstrates superior performance across diverse applications including protein search and quantum circuit design.