Stabilized sparse online learning for sparse data
Y Ma, T Zheng - Journal of Machine Learning Research, 2017 - jmlr.org
Stochastic gradient descent (SGD) is commonly used for optimization in large-scale
machine learning problems. Langford et al.(2009) introduce a sparse online learning …
machine learning problems. Langford et al.(2009) introduce a sparse online learning …
Feature-aware regularization for sparse online learning
Learning a compact predictive model in an online setting has recently gained a great deal of
attention. The combination of online learning with sparsity-inducing regularization enables …
attention. The combination of online learning with sparsity-inducing regularization enables …
[图书][B] Flexible Sparse Learning of Feature Subspaces
Y Ma - 2017 - search.proquest.com
It is widely observed that the performances of many traditional statistical learning methods
degenerate when confronted with high-dimensional data. One promising approach to …
degenerate when confronted with high-dimensional data. One promising approach to …
授かり効果付きオンライン学習
大岩秀和， 中川裕志 - 人工知能学会全国大会論文集第27 回(2013), 2013 - jstage.jst.go.jp
抄録 オンライン学習は, データを受け取るたび逐次的に学習器を更新する手法である. そのため,
過去の学習器で正答したデータに対し, 学習器のルール更新後に誤答する事がある. 所得効果より …
過去の学習器で正答したデータに対し, 学習器のルール更新後に誤答する事がある. 所得効果より …