Meta Tags Optimization - How Important Are Meta Tags Now?Serge DaudelinSearch Engine Marketing Success
MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation阅读笔记 动机 本文是2020年KDD上的一篇论文。当时的工作已经有不少方法使用元学习来缓解推荐系统冷启动问题,它们大部分都是基于MAML的,这种方法通常是为所有冷启动用户(物品)生成一个初始化向量,然后让这些冷启动用户(物品)经过少量训练就可以快速...
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这篇文章指出 上下文学习(In-Context Learning) 是一种隐式的Fintuning。ICL实际构造了一种的meta-optimization,prompt中的样本经过attention计算的结果,可以视作Finetuning通过反向传播产生的梯度。除了公式推导外,作者还给attention设计了一个变种(类似momentum之于GD),通过实验验证确实有效,进一步论证这个类比是有道理的 ...
但是Meta这篇工作ScPO从模型的自我一致性出发,构造偏好数据。具体而言,对模型的不同回答进行统计分类,将投票数最多的回复视作偏好数据,投票数最少的视作拒绝数据,以此来构造数据对。 Method 初始化 ScPO是一个在线学习的方法,即每一轮模型在一些高质量的prompt上采样回复,提取偏好数据对,然后优化。再用优化后的...
Summary: We proposed Evolutionary Particle Swarm Optimization (EPSO) which provides a new paradigm of meta-optimization for model selection in swarm intelligence. In this paper, we extend the technique of online evolutionary computation of EPSO to Canonical Particle Swarm Optimizer (CPSO), and propo...
Sampling meta-tasks can be considered as a combinatorial optimization problem. Assuming that source dataset contains C classes and M samples in total, N classes and K samples per class are selected for a specific meta-task. There are CCN×(CMK)N situations for meta-tasks and we iteratively ch...
Too Long; Didn't ReadThis section introduces the meta-prompt specifically crafted for math optimization, focusing on its role in guiding large language models (LLMs) to generate enhanced solutions for various mathematical problems. The strategic design of the meta-prompt is emphasized for optimizing...
Optimization through meta-heuristics in electric vehicular (EV) transport has emerged as the key to improve the existing technologies and pave way for their mass deployment and revolutionize the current transport system while lowering greenhouse emissions. Range and cost have been the main aspects that...
Meta-learner 根据从 Learner 处得来的( \nabla_t,L_t )计算下一时刻的参数 \theta_{t+1} 最后Learner 用最新生成的参数 \theta_T 在\mathcal{D}_{meta-test} 计算损失,进行梯度回传跟新优化器 Meta-Learner 的参数。 下面是论文中的算法描述: [1] OPTIMIZATION AS A MODEL FOR FEW-SHOT LEARNING ...