Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Generalization Properties of Learning with Random Features
A Generalized Representer Theorem
Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives
Random Projection Random Discretization Ensembles—Ensembles of Linear Multivariate Decision Trees
Unsupervised Learning of Feature Hierarchies
Sparse Bayesian Learning and the Relevance Vector Machine
Robust multi-task feature learning
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
Deep Kernel Learning
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Sample compression, learnability, and the Vapnik-Chervonenkis dimension
A survey of dimensionality reduction techniques based on random projection
Online regularized learning with pairwise loss functions
Large-Scale Kernel Machines
Efficient Additive Kernels via Explicit Feature Maps
Joint self-representation and subspace learning for unsupervised feature selection
Painless Unsupervised Learning with Features
Dimension Reduction With Extreme Learning Machine
Large-Scale Feature Learning With Spike-and-Slab Sparse Coding
Pairwise Constraint-Guided Sparse Learning for Feature Selection
Granger-causal Attentive Mixtures of Experts : Learning Important Features with Neural Networks
Designing Planar Deployable Objects via Scissor Structures
Numerical linear algebra in the streaming model
Antenatal Corticosteroids Prior to 24 Weeks' Gestation and Neonatal Outcome of Extremely Low Birth Weight Infants
One Parser, Many Languages
Reality-based interaction: a framework for post-WIMP interfaces