
CODE
The code below is free for academic purposes but not intended for commercial purposes. If you use it, please cite our papers (the papers with the same titles in papers.html) in your work. This code is provided asis; we don't have resources to support your use of it. Some additinoal code resides in the generic directory
here. This work was supported in part by the following grants from the National Science Foundation: III1526914, IIS1451500, CCF1302269, IIS1117631, IIS0347499 and CCR0312690.
Variational AutoEncoders with a new Simplex Distribution (as in NeurIPS 2019)
CODE
Correlated Variational AutoEncoders (as in ICML 2019)
CODE
Variational AutoEncoders for Collaborative Filtering (as in WWW 2018)
CODE
Thompson Sampling with NonCompliance (as in ArXiv 2018)
CODE
Bethe learning of graphical models via MAP decoding (as in AISTATS 2016).
CODE
BMatching 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
SemiSupervised Learning Using Greedy MaxCut
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 bMatching
CODE
Minimum Volume Embedding
CODE
MultiObject Tracking with Representations of the Symmetric Group
CODE
Graph Reconstruction with DegreeConstrained 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
MultiTask 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
