Hierarchically compositional kernels for scalable nonparametric learning
- Jie Chen
- Haim Avron
- et al.
- 2017
- JMLR
Paper
Publications
32 results for Vikas Sindhwani
Near-separable non-negative matrix factorization with ℓ1 and Bregman loss functions
- Abhishek Kumar
- Vikas Sindhwani
- 2015
- SDM 2015
Conference paperRandom laplace feature maps for semigroup kernels on histograms
- Jiyan Yang
- Vikas Sindhwani
- et al.
- 2014
- CVPR 2014
Conference paperPersonalized classifiers: Evolving a classifier from a large reference Knowledge Graph
- Ramakrishna B. Bairi
- Ganesh Ramakrishnan
- et al.
- 2014
- IDEAS 2014
Conference paperQuasi-Monte Carlo feature maps for shift-invariant kernels
- Jiyan Yang
- Vikas Sindhwani
- et al.
- 2014
- ICML 2014
Conference paperKernel methods match deep neural networks on TIMIT
- Po-Sen Huang
- Haim Avron
- et al.
- 2014
- ICASSP 2014
Conference paperSketching structured matrices for faster nonlinear regression
- Haim Avron
- Vikas Sindhwani
- et al.
- 2013
- NeurIPS 2013
Conference paperScalable matrix-valued kernel learning for high-dimensional nonlinear multivariate regression and granger causality
- Vikas Sindhwani
- Hà Quang Minh
- et al.
- 2013
- UAI 2013
Conference paperLow-rank matrix factorization for Deep Neural Network training with high-dimensional output targets
- Tara N. Sainath
- Brian Kingsbury
- et al.
- 2013
- ICASSP 2013
Conference paperFast conical hull algorithms for near-separable non-negative matrix factorization
- Abhishek Kumar
- Vikas Sindhwani
- et al.
- 2013
- ICML 2013
Conference paper