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Alex J. Smola:
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Publications of Author
- Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf
Measuring Statistical Dependence with Hilbert-Schmidt Norms. [Citation Graph (0, 0)][DBLP] ALT, 2005, pp:63-77 [Conf]
- Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
Large Margin Classification for Moving Targets. [Citation Graph (0, 0)][DBLP] ALT, 2002, pp:113-127 [Conf]
- Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola
A Generalized Representer Theorem. [Citation Graph (0, 0)][DBLP] COLT/EuroCOLT, 2001, pp:416-426 [Conf]
- Alex J. Smola, Risi Imre Kondor
Kernels and Regularization on Graphs. [Citation Graph (0, 0)][DBLP] COLT, 2003, pp:144-158 [Conf]
- Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
Entropy Numbers of Linear Function Classes. [Citation Graph (0, 0)][DBLP] COLT, 2000, pp:309-319 [Conf]
- Bernhard Schölkopf, Alex J. Smola, Phil Knirsch, Chris Burges
Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces. [Citation Graph (0, 0)][DBLP] DAGM-Symposium, 1998, pp:125-132 [Conf]
- Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
Entropy Numbers, Operators and Support Vector Kernels. [Citation Graph (0, 0)][DBLP] EuroCOLT, 1999, pp:285-299 [Conf]
- Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP] EuroCOLT, 1999, pp:214-229 [Conf]
- Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alex J. Smola, Thomas Lengauer, Klaus-Robert Müller
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites. [Citation Graph (0, 0)][DBLP] German Conference on Bioinformatics, 1999, pp:37-43 [Conf]
- Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
Predicting Time Series with Support Vector Machines. [Citation Graph (0, 0)][DBLP] ICANN, 1997, pp:999-1004 [Conf]
- Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Kernel Principal Component Analysis. [Citation Graph (0, 0)][DBLP] ICANN, 1997, pp:583-588 [Conf]
- Yasemin Altun, Thomas Hofmann, Alex J. Smola
Gaussian process classification for segmenting and annotating sequences. [Citation Graph (0, 0)][DBLP] ICML, 2004, pp:- [Conf]
- Colin Campbell, Nello Cristianini, Alex J. Smola
Query Learning with Large Margin Classifiers. [Citation Graph (0, 0)][DBLP] ICML, 2000, pp:111-118 [Conf]
- Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alex J. Smola
Multi-Instance Kernels. [Citation Graph (0, 0)][DBLP] ICML, 2002, pp:179-186 [Conf]
- Quoc V. Le, Alex J. Smola, Thomas Gärtner
Simpler knowledge-based support vector machines. [Citation Graph (0, 0)][DBLP] ICML, 2006, pp:521-528 [Conf]
- Julian John McAuley, Tibério S. Caetano, Alex J. Smola, Matthias O. Franz
Learning high-order MRF priors of color images. [Citation Graph (0, 0)][DBLP] ICML, 2006, pp:617-624 [Conf]
- Cheng Soon Ong, Alex J. Smola
Machine Learning with Hyperkernels. [Citation Graph (0, 0)][DBLP] ICML, 2003, pp:568-575 [Conf]
- Alex J. Smola, Bernhard Schölkopf
Sparse Greedy Matrix Approximation for Machine Learning. [Citation Graph (0, 0)][DBLP] ICML, 2000, pp:911-918 [Conf]
- S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha Murty
SimpleSVM. [Citation Graph (0, 0)][DBLP] ICML, 2003, pp:760-767 [Conf]
- Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments. [Citation Graph (0, 0)][DBLP] IJCNN (5), 2000, pp:199-204 [Conf]
- Vladimir Nikulin, Alex J. Smola
Universal Clustering with Regularization in Probabilistic Space. [Citation Graph (0, 0)][DBLP] MLDM, 2005, pp:142-152 [Conf]
- Bernhard Schölkopf, Alex J. Smola
A Short Introduction to Learning with Kernels. [Citation Graph (0, 0)][DBLP] Machine Learning Summer School, 2002, pp:41-64 [Conf]
- Alex J. Smola, Bernhard Schölkopf
Bayesian Kernel Methods. [Citation Graph (0, 0)][DBLP] Machine Learning Summer School, 2002, pp:65-117 [Conf]
- Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy, Alex J. Smola
A Second Order Cone programming Formulation for Classifying Missing Data. [Citation Graph (0, 0)][DBLP] NIPS, 2004, pp:- [Conf]
- Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik
Support Vector Regression Machines. [Citation Graph (0, 0)][DBLP] NIPS, 1996, pp:155-161 [Conf]
- Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, S. V. N. Vishwanathan
Large-Scale Multiclass Transduction. [Citation Graph (0, 0)][DBLP] NIPS, 2005, pp:- [Conf]
- Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
Online Learning with Kernels. [Citation Graph (0, 0)][DBLP] NIPS, 2001, pp:785-792 [Conf]
- Adam Kowalczyk, Alex J. Smola, Robert C. Williamson
Kernel Machines and Boolean Functions. [Citation Graph (0, 0)][DBLP] NIPS, 2001, pp:439-446 [Conf]
- Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Invariant Feature Extraction and Classification in Kernel Spaces. [Citation Graph (0, 0)][DBLP] NIPS, 1999, pp:526-532 [Conf]
- Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
Kernel PCA and De-Noising in Feature Spaces. [Citation Graph (0, 0)][DBLP] NIPS, 1998, pp:536-542 [Conf]
- Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
v-Arc: Ensemble Learning in the Presence of Outliers. [Citation Graph (0, 0)][DBLP] NIPS, 1999, pp:561-567 [Conf]
- Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson
Shrinking the Tube: A New Support Vector Regression Algorithm. [Citation Graph (0, 0)][DBLP] NIPS, 1998, pp:330-336 [Conf]
- Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik
Prior Knowledge in Support Vector Kernels. [Citation Graph (0, 0)][DBLP] NIPS, 1997, pp:- [Conf]
- Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
Support Vector Method for Novelty Detection. [Citation Graph (0, 0)][DBLP] NIPS, 1999, pp:582-588 [Conf]
- Alex J. Smola, Peter L. Bartlett
Sparse Greedy Gaussian Process Regression. [Citation Graph (0, 0)][DBLP] NIPS, 2000, pp:619-625 [Conf]
- Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
Semiparametric Support Vector and Linear Programming Machines. [Citation Graph (0, 0)][DBLP] NIPS, 1998, pp:585-591 [Conf]
- Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson
Regularization with Dot-Product Kernels. [Citation Graph (0, 0)][DBLP] NIPS, 2000, pp:308-314 [Conf]
- Alex J. Smola, Bernhard Schölkopf
From Regularization Operators to Support Vector Kernels. [Citation Graph (0, 0)][DBLP] NIPS, 1997, pp:- [Conf]
- Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
The Entropy Regularization Information Criterion. [Citation Graph (0, 0)][DBLP] NIPS, 1999, pp:342-348 [Conf]
- Vladimir Vapnik, Steven E. Golowich, Alex J. Smola
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing. [Citation Graph (0, 0)][DBLP] NIPS, 1996, pp:281-287 [Conf]
- S. V. N. Vishwanathan, Alex J. Smola
Binet-Cauchy Kernels. [Citation Graph (0, 0)][DBLP] NIPS, 2004, pp:- [Conf]
- Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller
Robust Ensemble Learning for Data Mining. [Citation Graph (0, 0)][DBLP] PAKDD, 2000, pp:341-344 [Conf]
- Alex J. Smola, Bernhard Schölkopf
On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion. [Citation Graph (0, 0)][DBLP] Algorithmica, 1998, v:22, n:1/2, pp:211-231 [Journal]
- Bernhard Schölkopf, Klaus-Robert Müller, Alex J. Smola
Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten. [Citation Graph (0, 0)][DBLP] Inform., Forsch. Entwickl., 1999, v:14, n:3, pp:154-163 [Journal]
- Glenn Fung, Olvi L. Mangasarian, Alex J. Smola
Minimal Kernel Classifiers. [Citation Graph (0, 0)][DBLP] Journal of Machine Learning Research, 2002, v:3, n:, pp:303-321 [Journal]
- Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
Regularized Principal Manifolds. [Citation Graph (0, 0)][DBLP] Journal of Machine Learning Research, 2001, v:1, n:, pp:179-209 [Journal]
- S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola
Step Size Adaptation in Reproducing Kernel Hilbert Space. [Citation Graph (0, 0)][DBLP] Journal of Machine Learning Research, 2006, v:7, n:, pp:1107-1133 [Journal]
- Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alex J. Smola, Robert C. Williamson
Estimating the Support of a High-Dimensional Distribution. [Citation Graph (0, 0)][DBLP] Neural Computation, 2001, v:13, n:7, pp:1443-1471 [Journal]
- Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Nonlinear Component Analysis as a Kernel Eigenvalue Problem. [Citation Graph (0, 0)][DBLP] Neural Computation, 1998, v:10, n:5, pp:1299-1319 [Journal]
- Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett
New Support Vector Algorithms. [Citation Graph (0, 0)][DBLP] Neural Computation, 2000, v:12, n:5, pp:1207-1245 [Journal]
- Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Experimentally optimal v in support vector regression for different noise models and parameter settings. [Citation Graph (0, 0)][DBLP] Neural Networks, 2004, v:17, n:1, pp:127-141 [Journal]
- Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Experimentally optimal nu in support vector regression for different noise models and parameter settings. [Citation Graph (0, 0)][DBLP] Neural Networks, 2005, v:18, n:2, pp:205-0 [Journal]
- Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
The connection between regularization operators and support vector kernels. [Citation Graph (0, 0)][DBLP] Neural Networks, 1998, v:11, n:4, pp:637-649 [Journal]
- Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. [Citation Graph (0, 0)][DBLP] IEEE Trans. Pattern Anal. Mach. Intell., 2003, v:25, n:5, pp:623-633 [Journal]
- Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. [Citation Graph (0, 0)][DBLP] IEEE Transactions on Information Theory, 2001, v:47, n:6, pp:2516-2532 [Journal]
- Alex J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
A Hilbert Space Embedding for Distributions. [Citation Graph (0, 0)][DBLP] ALT, 2007, pp:13-31 [Conf]
- Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
Supervised feature selection via dependence estimation. [Citation Graph (0, 0)][DBLP] ICML, 2007, pp:823-830 [Conf]
- Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
A scalable modular convex solver for regularized risk minimization. [Citation Graph (0, 0)][DBLP] KDD, 2007, pp:727-736 [Conf]
Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning. [Citation Graph (, )][DBLP]
Learning Graph Matching. [Citation Graph (, )][DBLP]
Tailoring density estimation via reproducing kernel moment matching. [Citation Graph (, )][DBLP]
Estimating labels from label proportions. [Citation Graph (, )][DBLP]
Colored Maximum Variance Unfolding. [Citation Graph (, )][DBLP]
COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking . [Citation Graph (, )][DBLP]
Bundle Methods for Machine Learning. [Citation Graph (, )][DBLP]
A Kernel Statistical Test of Independence. [Citation Graph (, )][DBLP]
Convex Learning with Invariances. [Citation Graph (, )][DBLP]
Kernelized Sorting. [Citation Graph (, )][DBLP]
Kernel Measures of Independence for non-iid Data. [Citation Graph (, )][DBLP]
Improving Maximum Margin Matrix Factorization. [Citation Graph (, )][DBLP]
Learning Graph Matching. [Citation Graph (, )][DBLP]
Adaptive collaborative filtering. [Citation Graph (, )][DBLP]
Semi-Markov Models for Sequence Segmentation. [Citation Graph (, )][DBLP]
Learning Graph Matching [Citation Graph (, )][DBLP]
Feature Hashing for Large Scale Multitask Learning [Citation Graph (, )][DBLP]
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