https://github.com/siyuyuan/evoagent
공식 코드EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
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Stochastic Optimization is the task of optimizing certain objective functional by generating and using stochastic random variables. Usually the Stochastic Optimization is an iterative process of generating random variables that progressively finds out the minima or the maxima of the objective functional. Stochastic Optimization is usually applied in the non-convex functional spaces where the usual deterministic optimization such as linear or quadratic programming or their variants cannot be used.
Source: ASOC: An Adaptive Parameter-free Stochastic Optimization Techinique for Continuous Variables
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms
Predictor-corrector algorithms for stochastic optimization under gradual distribution shift
Efficient Generator of Mathematical Expressions for Symbolic Regression
SCAPE: Searching Conceptual Architecture Prompts using Evolution
Opportunistic Routing in Wireless Communications via Learnable State-Augmented Policies
Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Local Search is a Remarkably Strong Baseline for Neural Architecture Search
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes
Bivariate Estimation-of-Distribution Algorithms Can Find an Exponential Number of Optima
Averaging Weights Leads to Wider Optima and Better Generalization
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching
Conformal Symplectic Optimization for Stable Reinforcement Learning
Grammar-based Game Description Generation using Large Language Models
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions
VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution
Evolvability ES: Scalable and Direct Optimization of Evolvability
SketchySGD: Reliable Stochastic Optimization via Randomized Curvature Estimates
Balancing Forecast Accuracy and Switching Costs in Online Optimization of Energy Management Systems
Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh Networks
GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.