Alex Smola

Publications440
h-index113
Citations96,194
Highly Influential Citations10,189
Author pages are created from data sourced from our academic publisher partnerships and public sources.

Recommended Authors

  • B. Schölkopf
  • 852 Publications, 97,828 Citations
  • Michael I. Jordan
  • 835 Publications, 151,398 Citations
  • Quoc V. Le
  • 198 Publications, 62,165 Citations
  • A. Gretton
  • 225 Publications, 16,030 Citations
  • Publications
  • Influence
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
TLDR
A new method for performing a nonlinear form of principal component analysis in high-dimensional feature spaces, related to input space by some nonlinear map. Expand
  • 7,425
  • 987
  • PDF
Learning with kernels
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without… Expand
  • 6,354
  • 859
  • PDF
A tutorial on support vector regression
TLDR
In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Expand
  • 8,233
  • 732
  • PDF
Estimating the Support of a High-Dimensional Distribution
TLDR
We propose a method to approach this problem by trying to estimate a function f that is positive on S and negative on the complement. Expand
  • 4,190
  • 615
  • PDF
A Kernel Two-Sample Test
TLDR
We propose a framework for analyzing and comparing distributions, which we use to construct statistical tests to determine if two samples are drawn from different distributions. Expand
  • 1,890
  • 510
  • PDF
Hierarchical Attention Networks for Document Classification
We propose a hierarchical attention network for document classification. Our model has two distinctive characteristics: (i) it has a hierarchical structure that mirrors the hierarchical structure of… Expand
  • 2,438
  • 394
  • PDF
A Kernel Method for the Two-Sample-Problem
TLDR
We propose two statistical tests to determine if two samples are from different distributions. Expand
  • 1,256
  • 277
  • PDF
Support Vector Regression Machines
TLDR
A new regression technique based on Vapnik's concept of support vectors is introduced. Expand
  • 2,951
  • 275
  • PDF
Advances in kernel methods: support vector learning
Introduction to support vector learning roadmap. Part 1 Theory: three remarks on the support vector method of function estimation, Vladimir Vapnik generalization performance of support vector… Expand
  • 5,662
  • 255
Kernel Principal Component Analysis
TLDR
A new method for performing a nonlinear form of Principal Component Analysis is proposed. Expand
  • 1,832
  • 239
  • PDF