Mathematics
6,356 papers (9 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Papers per year
2
6
3
11
43
40
56
47
63
82
130
204
219
256
250
325
374
489
556
620
576
651
697
512
144
'5
'10
'15
'20
'25
Papers (including subtopics)
Gaussian Copula Precision Estimation with Missing Values
AISTATS 2014
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation
ICML 2014
Global graph kernels using geometric embeddings
ICML 2014
Global Optimization Methods for Extended Fisher Discriminant Analysis
AISTATS 2014
GPS-Tag Refinement using Random Walks with an Adaptive Damping Factor
CVPR 2014
Graph Estimation From Multi-Attribute Data
JMLR 2014
Greedy Subspace Clustering
NeurIPS 2014
Hardness of parameter estimation in graphical models
NeurIPS 2014
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models
JMLR 2014
High-Dimensional Learning of Linear Causal Networks via Inverse Covariance Estimation
JMLR 2014
Hitting and Commute Times in Large Random Neighborhood Graphs
JMLR 2014
Human Action Recognition Based on Context-Dependent Graph Kernels
CVPR 2014
Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group
CVPR 2014
Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit
NeurIPS 2014
Information-Theoretic Characterization of Sparse Recovery
AISTATS 2014
Jointly Informative Feature Selection
AISTATS 2014
Joint Structure Learning of Multiple Non-Exchangeable Networks
AISTATS 2014
Kernel Mean Estimation and Stein Effect
ICML 2014
Kernel-PCA Analysis of Surface Normals for Shape-from-Shading
CVPR 2014
large scale canonical correlation analysis with iterative least squares
NeurIPS 2014
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data
ICML 2014
Learning Chordal Markov Networks by Dynamic Programming
NeurIPS 2014
Learning Euclidean-to-Riemannian Metric for Point-to-Set Classification
CVPR 2014
Learning from Contagion (Without Timestamps)
ICML 2014
Learning Graphs with a Few Hubs
ICML 2014