4 Methods 4.1 Meta-Representation 4.2 Meta-Optimizer 4.3 Meta-Objective and Episode Design 5 Applications 5.1 Computer Vision and Graphics 5.2 Meta Reinforcement Learning and Robotics 5.3 Neural Architecture Search (NAS) 5.4 Hyper-Parameter Optimization 5.5 Bayesian Meta-Learning 5.6 Unsupervised and Semi...
传统方法中的MTL(linear model, kernel methods, Bayesian algo),其主要关注两点: 通过norm regularization使模型在任务之间具有稀疏性 对多任务之间关系进行建模 1.1 Block-sparse regularization (mixed l1/lq norm) 目标:强制模型只考虑部分特征,前提为不同任务之...
***优化过程,通常是参数中心的(parameter-centric methods)通过存在的优化器(SGD with momentum/ADAM)优化初始值,优化中心的方法(optimizer-centric approaches),关注于学习一个inner optimizer,可以训练的w将超参设置为固定的大小,通过非线性变换用w来定义一个梯度优化器,这些方法用来加速优化过程,与传统的贝叶斯优化效...
Learning neural network (30) realizes that random weight changes learning algorithm in adjustment of weight mechanism (28), for being applied to the network (30) that network (30) obtain desired function to the weight of input. Weight is changed randomly to be changed from original state with...
Sequential learning in neural networks: A review and a discussion of pseudorehearsal based methods. Anthony Robins. Intelligent Data Analysis . 2004... A Robins - 《Intelligent Data Analysis》 被引量: 39发表: 2004年 Exploring the Process of Inference Generation in Sarcasm: A Review of Normal an...
Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels; Cambridge University Press: New York, NY, USA, 2009; p. 349... WW Hsieh - Cambridge University Press 被引量: 158发表: 2009年 machine learning methods in the environmental sciences neural networks and kernels mac...
Analysis Methods in Neural Language Processing: A Survey. Trans. Assoc. Comput. Linguistics 2019 paper bib Yonatan Belinkov, James R. Glass Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop. Nat. Lang. Eng. 2019 paper bib Afra Alishahi, Grzegorz ...
Meka - An open source implementation of methods for multi-label classification and evaluation (extension to Weka). MLlib in Apache Spark - Distributed machine learning library in Spark. Hydrosphere Mist - a service for deployment Apache Spark MLLib machine learning models as realtime, batch or re...
In that way, reinforcement learning handles more complex and dynamic situations than other methods because it allows the context of the project goal to influence the risk in choices. Teaching a computer to play chess is a good example. The overall goal is to win the game, but that may ...
HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data Many perturbations affect only a subset of cells, while the rest remain largely unaffected. Existing single-cell analysis methods may fail to isolate the affected cells and ...