MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation阅读笔记 阅读目录(Content) 动机 方法 实验结果 总结 回到顶部(go to top) 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)...
Meta-optimizationThe last couple of decades have witnessed a steadily increasing applications of nature inspired optimization (NIO) in vast fields such as power engineering, environmental engineering, and civil engineering. Behavioral parameters deeply affect the optimization performance for a NIO algorithm....
The legendary Donald Knuth was right about many things, but meta-optimization is indeed strong evidence that most people can be pretty happy optimizing most things (not quite everything , admittedly). Optimization in its standard form concerns the reconciliation of ambiguities and uncertainties on the...
MetaMath是可以生成一些带参考答案的题目,但是ScPO不需要参考答案,所以可以采用MuggleMath等方法进行题目生成。 构造自我一致的偏好数据对 每个问题,对模型的回复进行投票,如果最多的票数多于某个阈值,那么保留这样的样本。把票数最多的当作偏好样本,票数最少的当作拒绝样本。 Ps: Q: 为什么投票票数最大的结果能...
We show preliminary results of meta-learning on results for several algorithms and large set of TSP instances. These results indicate that meta-optimization can improve quality of solution by automatic algorithm recommendation. 展开 年份: 2013
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 ...
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This paper presents the extension of framework for automatic design space exploration (FADSE) tool using a meta-optimization approach, which is used to improve the performance of design space exploration algorithms, by driving two different multiobjective meta-heuristics concurrently. More precisely, we...
Meta-learning算法:Latent Embedding Optimization xplutoy 与其感慨路难行,不如马上出发 23 人赞同了该文章之前介绍的MAML算法,其内循环(inner-loop)所用的网络参数空间很大,当应用于few-shot任务时很容易造成过拟合(参数空间>>数据空间)。这是很明显的,如果仔细看看few...
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...