← Back to papers
2011 AISTATS AISTATS 2011

Discussion of “Spectral Dimensionality Reduction via Maximum Entropy”

Abstract

Discussion of Spectral Dimensionality Reduction via Maximum Entropy.

🐝 Cross-Pollinator — Artificial Intelligence, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning

Authors

Laurens van der Maaten

Topics

Machine Learning > Core Methods > Embedding Learning Machine Learning > Optimization & Theory > Optimization Machine Learning > Core Methods > Dimensionality Reduction

Keywords

maximum entropy spectral dimensionality reduction gaussian random field
Download PDF

Related papers

Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm 2011
Deep Learners Benefit More from Out-of-Distribution Examples 2011
Bagged Structure Learning of Bayesian Network 2011
Convergent Decomposition Solvers for Tree-reweighted Free Energies 2011
Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization 2011