Variational Auto-Encoders with a new Simplex Distribution (as in NeurIPS 2019) CODE

Correlated Variational Auto-Encoders (as in ICML 2019) CODE

Variational Auto-Encoders for Collaborative Filtering (as in WWW 2018) CODE

Thompson Sampling with Non-Compliance (as in ArXiv 2018) CODE

Bethe learning of graphical models via MAP decoding (as in AISTATS 2016). CODE

B-Matching and Adaptive Anonymity (as in our NIPS 2013 Paper) CODE

Polynomial Time Inference of Bethe Partition Function and Marginals CODE

pSVM for Learning with Label Proportions CODE

Semi-Supervised Learning Using Greedy Max-Cut CODE

Majorization for Conditional Random Fields and Latent Likelihoods CODE

Structure Preserving Metric Learning CODE

Graphical Modeling with Perfect Graphs CODE

Collaborative Filtering via Rating Concentration CODE

Laplacian Spectrum Learning CODE

Structure Preserving Embedding CODE

Relative Margin Machines CODE

Belief Propagation for Maximum Weight b-Matching CODE

Minimum Volume Embedding CODE

Multi-Object Tracking with Representations of the Symmetric Group CODE

Graph Reconstruction with Degree-Constrained Subgraphs CODE (SLOW)

Permutation Invariant SVMs CODE

Spectral Clustering and Embedding with Hidden Markov Models CODE

Probability Product Kernels CODE

Bhattacharyya Kernel Between Sets of Vectors CODE

Dynamical Systems Trees CODE

Multi-Task Feature and Kernel Selection for SVMs CODE

3D Structure from 2D Motion CODE

Fast Expecation Maximization CODE

Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm CODE