Smola, Alex J

46 publications

ICML 2022 Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition Haotao Wang, Aston Zhang, Yi Zhu, Shuai Zheng, Mu Li, Alex J Smola, Zhangyang Wang

NeurIPS 2012 FastEx: Hash Clustering with Exponential Families Amr Ahmed, Sujith Ravi, Alex J. Smola, Shravan M. Narayanamurthy

NeurIPS 2012 Learning Networks of Heterogeneous Influence Nan Du, Le Song, Ming Yuan, Alex J. Smola

JMLR 2010 Bundle Methods for Regularized Risk Minimization Choon Hui Teo, S.V.N. Vishwanthan, Alex J. Smola, Quoc V. Le

NeurIPS 2010 Multitask Learning Without Label Correspondences Novi Quadrianto, James Petterson, Tibério S. Caetano, Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2010 Optimal Web-Scale Tiering as a Flow Problem Gilbert Leung, Novi Quadrianto, Kostas Tsioutsiouliklis, Alex J. Smola

NeurIPS 2010 Parallelized Stochastic Gradient Descent Martin Zinkevich, Markus Weimer, Lihong Li, Alex J. Smola

NeurIPS 2010 Word Features for Latent Dirichlet Allocation James Petterson, Wray Buntine, Shravan M. Narayanamurthy, Tibério S. Caetano, Alex J. Smola

NeurIPS 2009 Distribution Matching for Transduction Novi Quadrianto, James Petterson, Alex J. Smola

JMLR 2009 Estimating Labels from Label Proportions Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le

NeurIPS 2009 Slow Learners Are Fast Martin Zinkevich, John Langford, Alex J. Smola

NeurIPS 2008 Kernel Measures of Independence for Non-Iid Data Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smola

NeurIPS 2008 Kernelized Sorting Novi Quadrianto, Le Song, Alex J. Smola

NeurIPS 2008 Robust Near-Isometric Matching via Structured Learning of Graphical Models Alex J. Smola, Julian J. Mcauley, Tibério S. Caetano

NeurIPS 2008 Tighter Bounds for Structured Estimation Olivier Chapelle, Chuong B. Do, Choon H. Teo, Quoc V. Le, Alex J. Smola

NeurIPS 2007 A Kernel Statistical Test of Independence Arthur Gretton, Kenji Fukumizu, Choon H. Teo, Le Song, Bernhard Schölkopf, Alex J. Smola

NeurIPS 2007 Bundle Methods for Machine Learning Quoc V. Le, Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2007 COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alex J. Smola

NeurIPS 2007 Colored Maximum Variance Unfolding Le Song, Arthur Gretton, Karsten Borgwardt, Alex J. Smola

NeurIPS 2007 Convex Learning with Invariances Choon H. Teo, Amir Globerson, Sam T. Roweis, Alex J. Smola

NeurIPS 2006 A Kernel Method for the Two-Sample-Problem Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, Alex J. Smola

NeurIPS 2006 Correcting Sample Selection Bias by Unlabeled Data Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, Alex J. Smola

JMLR 2006 Step Size Adaptation in Reproducing Kernel Hilbert Space S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola

AISTATS 2005 Kernel Methods for Missing Variables Alex J. Smola, S. V. N. Vishwanathan, Thomas Hofmann

NeurIPS 2005 Large-Scale Multiclass Transduction Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, Vishy Vishwanathan

NeurIPS 2004 A Second Order Cone Programming Formulation for Classifying Missing Data Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy, Alex J. Smola

NeurIPS 2004 Binet-Cauchy Kernels Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2003 Laplace Propagation Eleazar Eskin, Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2002 Adapting Codes and Embeddings for Polychotomies Gunnar Rätsch, Sebastian Mika, Alex J. Smola

NeurIPS 2002 Fast Kernels for String and Tree Matching Alex J. Smola, S.v.n. Vishwanathan

NeurIPS 2002 Hyperkernels Cheng S. Ong, Robert C. Williamson, Alex J. Smola

NeurIPS 2001 Kernel Machines and Boolean Functions Adam Kowalczyk, Alex J. Smola, Robert C. Williamson

NeurIPS 2001 Online Learning with Kernels Jyrki Kivinen, Alex J. Smola, Robert C. Williamson

NeurIPS 2000 Regularization with Dot-Product Kernels Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson

NeurIPS 2000 Sparse Greedy Gaussian Process Regression Alex J. Smola, Peter L. Bartlett

NeurIPS 1999 Invariant Feature Extraction and Classification in Kernel Spaces Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller

NeurIPS 1999 Support Vector Method for Novelty Detection Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt

NeurIPS 1999 The Entropy Regularization Information Criterion Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson

NeurIPS 1999 V-Arc: Ensemble Learning in the Presence of Outliers Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika

NeurIPS 1998 Kernel PCA and De-Noising in Feature Spaces Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch

NeurIPS 1998 Semiparametric Support Vector and Linear Programming Machines Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf

NeurIPS 1998 Shrinking the Tube: A New Support Vector Regression Algorithm Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson

NeurIPS 1997 From Regularization Operators to Support Vector Kernels Alex J. Smola, Bernhard Schölkopf

NeurIPS 1997 Prior Knowledge in Support Vector Kernels Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik

NeurIPS 1996 Support Vector Method for Function Approximation, Regression Estimation and Signal Processing Vladimir Vapnik, Steven E. Golowich, Alex J. Smola

NeurIPS 1996 Support Vector Regression Machines Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik