Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Megaman: scalable manifold learning in python
megaman: Manifold Learning with Millions of points
Principal manifolds and nonlinear dimensionality reduction via tangent space alignment
Curvature-aware Manifold Learning
Metric Learning and Manifolds Metric Learning and Manifolds : Preserving the Intrinsic Geometry
Locally Linear Hashing for Extracting Non-linear Manifolds
Unsupervised Multi-Manifold Clustering by Learning Deep Representation.
Manifold Partition Discriminant Analysis
Unsupervised Learning of Image Manifolds by Semidefinite Programming
Robust manifold matrix factorization for joint clustering and feature extraction
Applications of Average Geodesic Distance in Manifold learning
A General Framework for Manifold Alignment
Robust Manifold Nonnegative Matrix Factorization
Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-Scale Image Retrieval
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds
Trace Ratio Optimization-Based Semi-Supervised Nonlinear Dimensionality Reduction for Marginal Manifold Visualization
Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning
Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment
Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent
Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models
Building of an Information Retrieval System Based on Genetic Algorithms
Evaluating the magnitude and duration of cold load pick-up on residential distribution using multi-state load models
Non-Adversarial Unsupervised Word Translation
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics