Publications

Neural nets R. Kondor, Z. Lin and S. Trivedi:  Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network (NeurIPS 2018)

R. Kondor:  N-body networks: a covariant hierarchical neural network architecture for learning atomic potentials (preprint 3/5/18)

R. Kondor and S. Trivedi:  On the generalization of equivariance and convolution in neural networks to the action of compact groups (ICML 2018)

R. Kondor, Hy Truong Son, Horace Pan, Brandon Anderson, Shubhendu Trivedi:  Covariant compositional networks for learning graphs (preprint 1/7/18) [PyTorch code] [GraphFlow]

Multiresolution
Matrix Fact.
Y. Ding, R. Kondor and J. Eskreis-Winkler:  Multiresolution kernel approximation for Gaussian process regression (NIPS 2016)

P. K. Mudrakarta and R. Kondor:  A generic multiresolution preconditioner for sparse symmetric systems (preprint)

V. Ithapu, R. Kondor and V. Singh:  The Incremental Multiresolution Matrix Factorization Algorithm (CVPR 2017)

N. Teneva, P. K. Mudrakarta and R. Kondor:  Multiresolution Matrix Compression (AISTATS 2016)

R. Kondor, N. Teneva and P. K. Mudrakarta:  pMMF: a high performance C++ library for parallel multiresolution matrix factorization (Pre-release version)

R. Kondor, N. Teneva and P. K. Mudrakarta:  Parallel MMF: a multiresolution approach to matrix computation (preprint, July 2015)

R. Kondor, N. Teneva and V. Garg:  Multiresolution matrix factorization (ICML 2014) [supplement] [video]

Matching
in Vision
D. Pachauri, R. Kondor, G. Sargur and V. Singh:  Permutation diffusion maps with application to the image association problem in computer vision (NIPS 2014)

D. Pachauri, R. Kondor and V. Singh:  Solving the multi-way matching problem by permutation synchronization (NIPS 2013)

D. Pachauri, M. Collins, R. Kondor, V. Singh:  Incorporating domain knowledge in matching problems via harmonic analysis (ICML 2012)

Harmonic
Analysis
on Sn
R. Kondor, W. Dempsey:  Multiresolution analysis on the symmetric group (NIPS 2012) [supplement]

R. Kondor and M. Barbosa:  Ranking with kernels in Fourier space (COLT 2010) [supplement]

R. Kondor:  A Fourier space algorithm for solving quadratic assignment problems (SODA 2010)

Graph
Kernels
K. Rajendran, A. A. Kattis, A. Holiday, R. Kondor and I. G. Kevrekidis:  Data mining when each data point is a network (preprint)

R. Kondor and H. Pan:  The Multiscale Laplacian Graph Kernel (NIPS 2016)  Oral presentation  [arXiv] [code] [slides]

S. V. N. Vishwanathan, N. N. Schraudolf, R. Kondor and K. M. Borgwardt:  Graph kernels (Journal of Machine Learning Research 11, 2010) [arXiv]

R. Kondor, N. Shervashidze and K. M. Borgwardt: The graphlet spectrum (ICML 2009)

R. Kondor and K. M. Borgwardt:  The skew spectrum of graphs (ICML 2008) [ICML video] [C++ code]

Invariants
in Vision
R. Kondor:  A novel set of rotationally and translationally invariant features for images based on the non-commutative bispectrum (preprint, 2007) [arXiv]

Molecular
descriptors
A. P. Bartok, R. Kondor and G. Csanyi:  On representing chemical environments (Phys. Rev. B 87, 2013) [arXiv]

A. P. Bartok, M. C. Payne, R. Kondor and G. Csanyi:  Gaussian Approximation Potentials: the accuracy of quantum mechanics, without the electrons (Physical Review Letters 104, 2010) [arXiv]

Tracking R. Kondor:  Non-commutative harmonic analysis in multi-object tracking in "Bayesian Time-series Models" ed. D. Barber, A. T. Cemgil and S. Chiappa (Cambridge University Press, 2011)

R. Kondor, A. Howard and T. Jebara:  Multi-object tracking with representations of the symmetric group (AISTATS 2007) [Newton video] [AISPDS video]

Kernels
between
distributions
R. Kondor and T. Jebara: Gaussian and Wishart hyperkernels (NIPS 2006) [pdf] [bib]

T. Jebara, R. Kondor and A. Howard:  Probability product kernels (Journal of Machine Learning Research 5, 2004)

T. Jebara and R. Kondor: Bhattacharyya and expected likelihood kernels (COLT 2003) [bib]

R. Kondor and T. Jebara: A kernel between sets of vectors (ICML 2003) [errata] [bib] [note]

Kernels
on graphs
R. Kondor and J.-P. Vert:  Diffusion kernels in "Kernel Methods in Computational Biology" ed. B. Scholkopf, K. Tsuda and J.-P. Vert, (The MIT Press, 2004)

A. Smola and R. Kondor: Kernels and regularization on graphs (COLT 2003) [bib]

R. Kondor and J. Lafferty: Diffusion kernels on graphs and other discrete input spaces (ICML 2002) [bib]

Other
preprints
R. Kondor, G. Csanyi, S. E. Ahnert and T. Jebara: Multi-facet learning in Hilbert spaces (CU tech report, 2005)

R. Kondor: The skew spectrum of functions on finite groups and their homogeneous spaces (preprint, 2007) [arXiv]

Thesis R. Kondor: Group theoretical methods in machine learning. (unofficial version)

Software R. Kondor:  Mondrian:  C++ parallel blocked matrix library

R. Kondor, N. Teneva and P. K. Mudrakarta:  pMMF:  a high performance C++ library for parallel multiresolution matrix factorization

R. Kondor: SnOB:  a C++ library for computing fast Fourier transforms on the symmetric group