CMA-ES
PulseAugur coverage of CMA-ES — every cluster mentioning CMA-ES across labs, papers, and developer communities, ranked by signal.
7 day(s) with sentiment data
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Refined CMA-ES algorithm simplifies and enhances optimization for competition
Researchers have developed a simplified version of the CMA-ES algorithm, named Refined CMA-ES, specifically for the CEC 2026 Bound-Constrained Single-Objective Optimization competition. This variant focuses on removing …
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New FLAT method improves sample-efficient traffic calibration for digital twins
Researchers have developed FLAT, a novel method for sample-efficient traffic calibration in digital twins. This approach smooths the parameter-error landscape, making the objective learnable from a limited number of sam…
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Language Models Aid Formal Verification of Robotic Controllers
Researchers have explored the use of language models in designing formally verifiable controllers for robotic systems. The 'Proof-Carrying Evolution' (PCE) method involves a search process that proposes controllers alon…
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New DGO Optimizer Analyzes Local Search, Population, and Solver Performance
This paper introduces the Da Gou Gun Optimization (DGO) method, a population optimizer designed to analyze the impact of evaluated candidates on local search steps, population dynamics, and overall solver performance. T…
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LLM Agent Speeds Up Analog Chip Design with AnalogScout
Researchers have developed AnalogScout, a new framework designed to improve the efficiency of analog device sizing for chip design. This framework utilizes a large language model (LLM) agent to guide the sizing process,…
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New forward-only learning method for wavelet neural networks bypasses backpropagation
Researchers have developed a novel training framework for shared-kernel wavelet neural networks that bypasses traditional backpropagation. This forward-only learning approach utilizes CMA-ES optimization and introduces …
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New Bayesian Optimization Methods Achieve 1000x Speedup
Researchers have developed new Bayesian optimization (BO) algorithms that significantly increase speed while maintaining performance. These methods leverage the linear structure within existing BO techniques, offering s…
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New hybrid metaheuristics boost architectural design optimization
A new paper introduces two hybrid metaheuristics for architectural and structural design optimization, specifically tailored for scenarios with limited model evaluations and computational time. These methods, a modified…
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LLMs show early promise as engineering simulator calibration agents
A new research paper explores the effectiveness of large language models (LLMs) as calibration agents for expensive engineering simulators. The study found that LLMs, when prompted with physics-based error descriptions,…
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AI agents automate analog/RF chip design with RFChipAgent · 2 sources tracked
Researchers have developed RFChipAgent, a novel multi-agent system utilizing large language models (LLMs) to automate the end-to-end design of analog/RF circuits. This system integrates a retrieval-augmented generation …
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New Modular CMA-ES Framework Enables Systematic Study of Evolution Strategies
Researchers have introduced the Modular CMA-ES (ModCMA), a flexible framework designed to integrate and systematically explore various modifications of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). This …
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New LESS method slashes neural architecture search time to minutes
Researchers have developed LESS (Lightweight Evolutionary Supernet Search), a novel method for neural architecture search that significantly reduces computation time. By combining a brief warm-up with a discrete search …
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New CMDO algorithm uses cognitive memory for adaptive search
Researchers have introduced a new optimization algorithm called Cognitive Memory-Driven Optimization (CMDO). This algorithm enhances population-based search by representing past search experiences as relationships betwe…
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Diffusion models enable efficient inverse design of metasurfaces for smart electromagnetic environments
Researchers have developed a diffusion-based framework for the inverse design of dielectric resonator metasurfaces, aiming to create smart electromagnetic environments for future wireless systems. This method, trained o…
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LLM-guided framework enhances neural architecture search proxies
Researchers have developed Bi-EZP, a novel bilevel framework designed to improve the discovery of ensemble zero-cost proxies for neural architecture search (NAS). This framework separates the discrete structural optimiz…
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New Integer Natural Evolution Strategy Developed for Optimization Problems
Researchers have developed a new optimization strategy called the Integer Natural Evolution Strategy (INES) that is natively designed for integer optimization problems. Unlike existing methods that adapt continuous Gaus…
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JANUS module enhances black-box optimization with Jacobian alignment
Researchers have developed JANUS, a novel plug-and-play module designed to enhance population-based optimizers like CMA-ES. JANUS extracts local geometric signals from recent evaluation traces without replacing the host…
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Social media simulation model calibrated for content moderation research
Researchers have developed a calibrated extension of the SimSoM agent-based model to simulate social media dynamics, specifically focusing on content moderation. This enhanced model, grounded in real-world data from the…
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New hybrid framework enhances LLM optimization by decoupling structure and parameters
Researchers have developed a novel hybrid nested search framework designed to improve the efficiency of large language models (LLMs) in optimization tasks. This approach decouples the structural and parameter updates, a…
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UAV photogrammetry method improves 3D reconstruction accuracy
Researchers have developed a new iterative hybrid discrete-continuous viewpoint planning method specifically for unmanned aerial vehicle (UAV) photogrammetry. This method aims to improve reconstruction accuracy and comp…