Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Pathologies in information bottleneck for deterministic supervised learning.
Deep learning and the information bottleneck principle
An Information-Theoretic View for Deep Learning
Information Theoretic Learning with Infinitely Divisible Kernels
Supervised Restricted Boltzmann Machines
Backprop as Functor: A compositional perspective on supervised learning
A Reproducing Kernel Hilbert Space Framework for Information-Theoretic Learning
A General Lower Bound on the Number of Examples Needed for Learning
Selective Supervision: Guiding Supervised Learning with Decision-Theoretic Active Learning
Learning belief networks from data: an information theory based approach
End-to-end Learning of Deterministic Decision Trees
A Minimum Relative Entropy Principle for Learning and Acting
Semi-supervised learning with an imperfect supervisor
Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural Network
Investigating Loss Functions And Optimization Methods For Discriminative Learning Of Label Sequences
Unsupervised Learning with Stein's Unbiased Risk Estimator
Dual coordinate descent methods for logistic regression and maximum entropy models
Learning to learn with the informative vector machine
Latent Hinge-Minimax Risk Minimization for Inference from a Small Number of Training Samples
Large-Sample Learning of Bayesian Networks is NP-Hard
Empirical Bayes for Learning to Learn
a wearable system to assist walking of parkinson s disease patients .
Expression of homeotic mutations in duplicated and regenerated antennae of Drosophila melanogaster.
Deterministic Annealing for Clustering, Compression, Classification, Regression, and Related Optimization Problems
Semantic Integration in the Information Flow Framework
Isometric Test Data Compression