|
Bharath K
Sriperumbudur |
|
Preprints Optimal function-on-scalar regression over complex domains M. Reimherr, B. K. Sriperumbudur and Hyun Bin Kang [arxiv] Minimax estimation of quadratic Fourier functionals S. Singh, B. K. Sriperumbudur and B. Poczos [arxiv] Gaussian processes and kernel methods: A review on connections and equivalences M. Kanagawa, P. Hennig, D. Sejdinovic and B. K. Sriperumbudur [arxiv] Approximate kernel PCA using random features: Computational vs. statistical trade-off B. K. Sriperumbudur and N. Sterge [arxiv] Adaptive clustering using kernel density estimators I. Steinwart, B. K. Sriperumbudur and P. Thomann [arxiv] 2019 On kernel derivative approximation with random Fourier features Z. Szabo and B. K. Sriperumbudur AISTATS, To appear. [arxiv] 2018 Optimal prediction for additive function-on-function regression M. Reimherr, B. K. Sriperumbudur and B. Taoufik Electronic Journal of Statistics, 12(2), 4571-4601, 2018. [pdf] Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings M. Kanagawa, B. K. Sriperumbudur and K. Fukumizu Foundations of Computational Mathematics, To appear. [pdf] Characteristic and universal tensor product kernels Z. Szabo and B. K. Sriperumbudur Journal of Machine Learning Research, 18(233): 1-29, 2018. [pdf] 2017 Minimax estimation of kernel mean embeddings I. Tolstikhin, B. K. Sriperumbudur, and K. Muandet Journal of Machine Learning Research, 18(86): 1-47, 2017. [pdf] Density estimation in infinite dimensional exponential families B. K. Sriperumbudur, K. Fukumizu, A. Gretton, A. Hyvarinen and R. Kumar Journal of Machine Learning Research, 18(57):1-59, 2017. [pdf] Kernel mean embedding of distributions: A review and beyond K. Muandet, K. Fukumizu, B. K. Sriperumbudur and B. Scholkopf Foundations and Trends in Machine Learning, 10(1-2):1-141, 2017. [arxiv] 2016 Convergence guarantees for kernel-based quadrature rules in misspecified settings M. Kanagawa. B. K. Sriperumbudur and K. Fukumizu Neural Information Processing Systems, 2016. [pdf] Minimax estimation of maximal mean discrepancy with radial kernels I. Tolstikhin, B. K. Sriperumbudur and B. Scholkopf Neural Information Processing Systems, 2016. [pdf] Learning theory for distribution regression Z. Szabo, B. K. Sriperumbudur, B. Poczos and A. Gretton Journal of Machine Learning Research, 17 (152):1-40, 2016. [pdf] Kernel mean shrinkage estimators K. Muandet, B. K. Sriperumbudur, K. Fukumizu, A. Gretton and B. Scholkopf Journal of Machine Learning Research, 17 (48):1-41, 2016. [pdf] On the optimal estimation of probability measures in weak and strong topologies B. K. Sriperumbudur Bernoulli, 22(3): 1839-1893, 2016. [arxiv] 2015 Optimal rates for random Fourier features B. K. Sriperumbudur and Z. Szabo Neural Information Processing Systems, 2015. [pdf] Two-stage sampled learning theory on distributions Z. Szabo, A. Gretton, B. Poczos and B. K. Sriperumbudur International Conference on Artificial Intelligence and Statistics, 2015. [pdf] 2014 Kernel mean estimation via spectral filtering K. Muandet, B. K. Sriperumbudur and B. Scholkopf Neural Information Processing Systems, 2014. [pdf,supplement] Kernel mean estimation and Stein's effect K. Muandet, K. Fukumizu, B. K. Sriperumbudur, A. Gretton and B. Scholkopf International Conference of Machine Learning, 2014. [pdf,supplement] 2013 Equivalence of distance-based and RKHS-based statistics in hypothesis testing D. Sejdinovic, B. K. Sriperumbudur, A. Gretton and K. Fukumizu Annals of Statistics, 41(5): 2263-2291, 2013. [pdf] On the generalization ability of online learning algorithms for pairwise loss functions P. Kar, B. K. Sriperumbudur, P. Jain and H. Karnick International Conference on Machine Learning, 2013. [pdf] Ultrahigh dimensional feature screening via RKHS embeddings K. Balasubramanian, B. K. Sriperumbudur and G. Lebanon International Conference on Artificial Intelligence and Statistics, 2013. [pdf,supplement] 2012 Optimal kernel choice for large-scale two-sample tests A. Gretton, B. K. Sriperumbudur, D. Sejdinovic, H. Strathmann, S. Balakrishnan, M. Pontil and K. Fukumizu Neural Information Processing Systems, 2012. [pdf] On the empirical estimation of integral probability metrics B. K. Sriperumbudur, K. Fukumizu, A. Gretton, B. Scholkopf and G. R. G. Lanckriet Electronic Journal of Statistics, 6: 1550-1599, 2012. [pdf] Hypothesis testing using pairwise distances and associated kernels D. Sejdinovic, A. Gretton, B. K. Sriperumbudur and K. Fukumizu International Conference on Machine Learning, 2012. [pdf] A proof of convergence of the concave-convex procedure using Zangwill's theory B. K. Sriperumbudur and G. R. G. Lanckriet Neural Computation, 24(6): 1391–1407, 2012. [pdf] Consistency and rates for clustering with DBSCAN B. K. Sriperumbudur and I. Steinwart International Conference on Artificial Intelligence and Statistics, 2012. [pdf,supplement] 2011 Learning in
Hilbert vs. Banach spaces: A measure embedding viewpoint A
majorization-minimization approach to the sparse generalized
eigenvalue problem Universality,
characteristic kernels and RKHS embedding of measures 2010 Reproducing
kernel space embeddings and metrics on probability measures Non-parametric
estimation of integral probability metrics Hilbert space
embeddings and metrics on probability measures On the relation
between universality, characteristic kernels and RKHS
embedding of measures 2009 Kernel choice and
classifiability for RKHS embeddings of probability
distributions On
the convergence of the concave-convex procedure A
fast, consistent kernel two-sample test Discussion
of: Brownian distance covariance A d.c.
programming approach to the sparse generalized eigenvalue
problem 2008 RKHS
representation of measures applied to homogeneity,
independence and Fourier optics Non-uniform
speaker normalization using affine transformation
Injective Hilbert space embeddings of
probability measures Metric
embedding for kernel classification rules
The effect of kernel choice on RKHS based
statistical tests Finding musically meaningful words using
sparse CCA
Sparse eigen methods
by d.c. programming
Study of non-linear frequency warping
functions for speaker normalization A framework for
parameter optimization in mutual information based
registration algorithms
A fast piece-wise
deformable method for multi-modality image registration Lossless volumetric medical image compression
with progressive multi-planar reformatting using 3-D DPCM Textural content in 3T MR: An image-based
marker for Alzheimer's disease
Non-uniform
speaker normalization using frequency-dependent scaling
function A texture
analysis approach for automatic flaw detection in pipelines A novel
progressive thick slab paradigm for volumetric medical image
compression and navigation Non-uniform
speaker normalization using affine transformation An investigation into front-end signal
processing for speaker normalization Spatial
distribution of T2 values in the hippocampus of
Alzheimer’s disease and control subjects
3-D loss-less multi-resolution image
compression for medical images Block-based conditional entropy coding for
medical image compression
A simple approach to non-uniform vowel
normalization A model based approach to non-uniform vowel
normalization
Realization of linear time-invariant system
stability analyzers |