Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Sample compression, learnability, and the Vapnik-Chervonenkis dimension
A General Lower Bound on the Number of Examples Needed for Learning
Exploiting generalization in the subspaces for faster model-based learning
Generalized Learning Vector Quantization
Learning from Limited Demonstrations in High Dimensional Feature Spaces
Compressing Neural Networks using the Variational Information Bottleneck
an overview of statistical learning theory .
IGTree: Using Trees for Compression and Classification in Lazy Learning Algorithms
A vector-contraction inequality for Rademacher complexities
A Problem of Dimensionality: A Simple Example
Reduction Techniques for Instance-Based Learning Algorithms
compressive sampling and lossy compression .
Latent Hinge-Minimax Risk Minimization for Inference from a Small Number of Training Samples
Training Invariant Support Vector Machines using Selective Sampling
A Generalized Representer Theorem
Sparse Bayesian Learning and the Relevance Vector Machine
Learning to Learn: Model Regression Networks for Easy Small Sample Learning
Dimensionality reduction for supervised learning with reproducing kernel Hilbert spaces
Information Theoretic Learning
Polynomial Bounds for VC Dimension of Sigmoidal and General Pfaffian Neural Networks
Progress&Compress: A scalable framework for continual learning
Two different myiasis cases in southeast of Turkey: ophthalmomyiasis and cutaneous myiasis
IMAGINATION: a robust image-based CAPTCHA generation system
Engineering safety in machine learning
A complexity theory based on Boolean algebra
Experimental evaluation of model predictive control of ball and beam systems