Alex J. Smola
Co-Authors
Google Publications
-
Hierarchical Geographical Modeling of User locations from Social Media Posts
Amr Ahmed, Liangjie Hong, Alexander J Smola
Proceedings of the 22nd International World Wide Web Conference (WWW 2013) (to appear)
-
KDD tutorial: The Dataminer Guide to Scalable Mixed-Membership and Nonparametric Bayesian Models
ACM conference on Knowledge Discovery and Data Mining (KDD) (2013) (to appear)
-
Measurement and modeling of eye-mouse behavior
Vidhya Navalpakkam, LaDawn Jentzsch, Rory Sayres, Sujith Ravi, Amr Ahmed, Alex J. Smola
Proceedings of the 22nd International World Wide Web Conference (2013)
-
The Nested Chinese Restaurant Franchise Process: User Tracking and Document Modeling
Amr Ahmed, Liangjie Hong, Alexander J Smola
International Conference on Machine Learning (ICML) (2013) (to appear)
-
FastEx: Hash Clustering with Exponential Families
Amr Ahmed, Sujith Ravi, Shravan Narayanamurthy, Alex Smola
Proceedings of the 26th Conference on Neural Information Processing Systems. (NIPS) (2012)
-
Hokusai | Sketching Streams in Real Time
Sergiy Matusevych, Alex Smola, Amr Ahmed
Proceedings of the 28th International Conference on Conference on Uncertainty in Artificial Intelligence (UAI) (2012)
-
Web-Scale Multi-Task Feature Selection for Behavioral Targeting
Amr Ahmed, Mohamed Aly, Abhimanyu Das, Alex Smola, Tasos Anastasakos
Proceedings of The 21st ACM International Conference on Information and Knowledge Management (CIKM), ACM (2012) (to appear)
Previous Publications
-
Distributed Large-scale Natural Graph Factorization
Amr Ahmed, Nino Shervashidze, Shravan Narayanamurthy,, Vanja Josifovski, Alexander J Smola
Proceedings of the 22nd International World Wide Web Conference (WWW 2013) (to appear)
-
A Kernel Two-Sample Test
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
Journal of Machine Learning Research, vol. 13 (2012), pp. 723-773
-
Discovering Geographical Topics In The Twitter Stream
Liangjie Hong, Amr Ahmed, Siva Gurumurthy, Kostas Tsioutsiouliklis, Alex Smola
Proceedings of The 21st International World Wide Web conference (WWW) (2012)
-
Exponential Families for Conditional Random Fields
Yasemin Altun, Alexander J. Smola, Thomas Hofmann
CoRR, vol. abs/1207.4131 (2012)
-
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations
Nando de Freitas, Alex J. Smola, Masrour Zoghi
ICML (2012)
-
Fair and Balanced: Learning to Present News Stories
Amr Ahmed, Choon-hui Teo, S.V.N Vishwanathan, Alex Smola
Proceedings of The 5th ACM International Conference on Web Search and Data Mining (WSDM) (2012)
-
Friend or frenemy?: predicting signed ties in social networks
Shuang-Hong Yang, Alexander J. Smola, Bo Long, Hongyuan Zha, Yi Chang
SIGIR (2012), pp. 555-564
-
Hokusai - Sketching Streams in Real Time
Sergiy Matusevych, Alex J. Smola, Amr Ahmed
CoRR, vol. abs/1210.4891 (2012)
-
Learning Networks of Heterogeneous Influence
Nan Du, Le Song, Alex J. Smola, Ming Yuan
NIPS (2012), pp. 2789-2797
-
Linear support vector machines via dual cached loops
Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola
KDD (2012), pp. 177-185
-
Regret Bounds for Deterministic Gaussian Process Bandits
Nando de Freitas, Alex J. Smola, Masrour Zoghi
CoRR, vol. abs/1203.2177 (2012)
-
Scalable Inference in Latent Variable Models
Amr Ahmed, Mohamed Aly, Joseph Gonzalez, Shravan Narayanamurthy, Alex Smola
Proceedings of The 5th ACM International Conference on Web Search and Data Mining (WSDM) (2012)
-
Super-Samples from Kernel Herding
Yutian Chen, Max Welling, Alex J. Smola
CoRR, vol. abs/1203.3472 (2012)
-
Tutorial: New Templates for Scalable Data Analysis
Amr Ahmed, Alex Smola, Markus Weimer
The 21st International World Wide Web conference (WWW) (2012)
-
Bid generation for advanced match in sponsored search
Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josifovski, George Mavromatis, Alex J. Smola
WSDM (2011), pp. 515-524
-
Collaborative competitive filtering: learning recommender using context of user choice
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hongyuan Zha, Zhaohui Zheng
SIGIR (2011), pp. 295-304
-
Guest editorial: model selection and optimization in machine learning
Süreyya Özögür-Akyüz, Devrim Ünay, Alexander J. Smola
Machine Learning, vol. 85 (2011), pp. 1-2
-
Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models
Qinfeng Shi, Li Cheng, Li Wang, Alex J. Smola
International Journal of Computer Vision, vol. 93 (2011), pp. 22-32
-
Like like alike: joint friendship and interest propagation in social networks
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Narayanan Sadagopan, Zhaohui Zheng, Hongyuan Zha
WWW (2011), pp. 537-546
-
Linear-Time Estimators for Propensity Scores
Deepak Agarwal, Lihong Li, Alexander J. Smola
Journal of Machine Learning Research - Proceedings Track, vol. 15 (2011), pp. 93-100
-
Multiple domain user personalization
Yucheng Low, Deepak Agarwal, Alexander J. Smola
KDD (2011), pp. 123-131
-
Online Inference for the Infinite Cluster-topic Model: Storylines from Streaming Text
Amr Ahmed, Qirong Ho, Choon-hui Teo, Jacobe Eisenstein, Alex Smola, Eric Xing
Proceedings of the 14th Conference on Artificial Intelligence and Statistics (AISTATS) (2011)
-
Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text
Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alexander J. Smola, Eric P. Xing
Journal of Machine Learning Research - Proceedings Track, vol. 15 (2011), pp. 101-109
-
Parallel Online Learning
Daniel Hsu, Nikos Karampatziakis, John Langford, Alexander J. Smola
CoRR, vol. abs/1103.4204 (2011)
-
Scalable Distributed Inference of Dynamic User Interests for Behavioral Targeting
Amr Ahmed, Yucheng Low, Mohamed Aly, Vanja Josifovski, Alex Smola
Proceedings of The 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2011., ACM
-
Scalable clustering of news search results
Srinivas Vadrevu, Choon Hui Teo, Suju Rajan, Kunal Punera, Byron Dom, Alexander J. Smola, Yi Chang, Zhaohui Zheng
WSDM (2011), pp. 675-684
-
Tutorial: Latent Variable Models for the Internet
the 20th International World Wide Web conference (WWW) (2011)
-
Tutorial: Graphical Models for the Internet
The 25th Conference on Neural Information Processing Systems. (NIPS), (2011)
-
Unified analysis of streaming news
Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alexander J. Smola, Choon Hui Teo
WWW (2011), pp. 267-276
-
Unified Analysis of Streaming News
Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alex Smola, Choon-hui Teo
Proceedings of the 20th International World Wide Web conference (WWW) (2011)
-
WWW 2011 invited tutorial overview: latent variable models on the internet
WWW (Companion Volume) (2011), pp. 281-282
-
An Architecture for Parallel Topic Models
Alexander J. Smola, Shravan M. Narayanamurthy
PVLDB, vol. 3 (2010), pp. 703-710
-
Bundle Methods for Regularized Risk Minimization
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smola, Quoc V. Le
Journal of Machine Learning Research, vol. 11 (2010), pp. 311-365
-
Collaborative Filtering on a Budget
Alexandros Karatzoglou, Alexander J. Smola, Markus Weimer
Journal of Machine Learning Research - Proceedings Track, vol. 9 (2010), pp. 389-396
-
Discriminative frequent subgraph mining with optimality guarantees
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
Statistical Analysis and Data Mining, vol. 3 (2010), pp. 302-318
-
Distributed Flow Algorithms for Scalable Similarity Visualization
Novi Quadrianto, Dale Schuurmans, Alex J. Smola
ICDM Workshops (2010), pp. 1220-1227
-
Hilbert Space Embeddings of Hidden Markov Models
Le Song, Byron Boots, Sajid Siddiqi, Geoffrey J. Gordon, Alex Smola
Proceedings of the International Conference on Machine Learning (ICML) (2010)
-
IntervalRank: isotonic regression with listwise and pairwise constraints
Taesup Moon, Alex J. Smola, Yi Chang, Zhaohui Zheng
WSDM (2010), pp. 151-160
-
Kernelized Sorting
Novi Quadrianto, Alex J. Smola, Le Song, Tinne Tuytelaars
IEEE Trans. Pattern Anal. Mach. Intell., vol. 32 (2010), pp. 1809-1821
-
Multitask Learning without Label Correspondences
Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson
NIPS (2010), pp. 1957-1965
-
Optimal Web-Scale Tiering as a Flow Problem
Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis
NIPS (2010), pp. 1333-1341
-
Parallelized Stochastic Gradient Descent
Martin Zinkevich, Markus Weimer, Alexander J. Smola, Lihong Li
NIPS (2010), pp. 2595-2603
-
Super-Samples from Kernel Herding
Yutian Chen, Max Welling, Alex J. Smola
UAI (2010), pp. 109-116
-
Wearable sensor activity analysis using semi-Markov models with a grammar
O. Thomas, Peter Sunehag, Gideon Dror, S. Yun, S. Kim, Matthew W. Robards, Alexander J. Smola, D. Green, P. Saunders
Pervasive and Mobile Computing, vol. 6 (2010), pp. 342-350
-
Word Features for Latent Dirichlet Allocation
James Petterson, Alexander J. Smola, Tibério S. Caetano, Wray L. Buntine, Shravan M. Narayanamurthy
NIPS (2010), pp. 1921-1929
-
Distribution Matching for Transduction
Novi Quadrianto, James Petterson, Alex J. Smola
NIPS (2009), pp. 1500-1508
-
Estimating Labels from Label Proportions
Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le
Journal of Machine Learning Research, vol. 10 (2009), pp. 2349-2374
-
Feature Hashing for Large Scale Multitask Learning
Kilian Q. Weinberger, Anirban Dasgupta, Josh Attenberg, John Langford, Alex J. Smola
CoRR, vol. abs/0902.2206 (2009)
-
Hash Kernels
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan
Journal of Machine Learning Research - Proceedings Track, vol. 5 (2009), pp. 496-503
-
Hash Kernels for Structured Data
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, S. V. N. Vishwanathan
Journal of Machine Learning Research, vol. 10 (2009), pp. 2615-2637
-
Hilbert space embeddings of conditional distributions with applications to dynamical systems
Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu
ICML (2009), pp. 121
-
Near-optimal Supervised Feature Selection among Frequent Subgraphs
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
SDM (2009), pp. 1075-1086
-
Relative Novelty Detection
Alexander J. Smola, Le Song, Choon Hui Teo
Journal of Machine Learning Research - Proceedings Track, vol. 5 (2009), pp. 536-543
-
Slow Learners are Fast
Martin Zinkevich, Alex J. Smola, John Langford
NIPS (2009), pp. 2331-2339
-
A Kernel Method for the Two-Sample Problem
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
CoRR, vol. abs/0805.2368 (2008)
-
Adaptive collaborative filtering
Markus Weimer, Alexandros Karatzoglou, Alex J. Smola
RecSys (2008), pp. 275-282
-
Discriminative human action segmentation and recognition using semi-Markov model
Qinfeng Shi, Li Wang, Li Cheng, Alexander J. Smola
CVPR (2008)
-
Estimating labels from label proportions
Novi Quadrianto, Alex J. Smola, Tibério S. Caetano, Quoc V. Le
ICML (2008), pp. 776-783
-
Improving Maximum Margin Matrix Factorization
Markus Weimer, Alexandros Karatzoglou, Alex J. Smola
ECML/PKDD (1) (2008), pp. 14
-
Improving maximum margin matrix factorization
Markus Weimer, Alexandros Karatzoglou, Alex J. Smola
Machine Learning, vol. 72 (2008), pp. 263-276
-
Kernel Measures of Independence for non-iid Data
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smola
NIPS (2008), pp. 1937-1944
-
Kernelized Sorting
Novi Quadrianto, Le Song, Alex J. Smola
NIPS (2008), pp. 1289-1296
-
Learning Graph Matching
Tibério S. Caetano, Julian John McAuley, Li Cheng, Quoc V. Le, Alex J. Smola
CoRR, vol. abs/0806.2890 (2008)
-
Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning
Ahmed H. El Zein, Eric McCreath, Alistair P. Rendell, Alex J. Smola
ICCS (1) (2008), pp. 466-475
-
Robust Near-Isometric Matching via Structured Learning of Graphical Models
Julian John McAuley, Tibério S. Caetano, Alexander J. Smola
NIPS (2008), pp. 1057-1064
-
Robust Near-Isometric Matching via Structured Learning of Graphical Models
Julian John McAuley, Tibério S. Caetano, Alexander J. Smola
CoRR, vol. abs/0809.3618 (2008)
-
Tailoring density estimation via reproducing kernel moment matching
Le Song, Xinhua Zhang, Alex J. Smola, Arthur Gretton, Bernhard Schölkopf
ICML (2008), pp. 992-999
-
Tighter Bounds for Structured Estimation
Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo
NIPS (2008), pp. 281-288
-
A Hilbert Space Embedding for Distributions
Alex J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf
ALT (2007), pp. 13-31
-
A Kernel Approach to Comparing Distributions
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
AAAI (2007), pp. 1637-1641
-
A Kernel Statistical Test of Independence
Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alex J. Smola
NIPS (2007)
-
A dependence maximization view of clustering
Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt
ICML (2007), pp. 815-822
-
A scalable modular convex solver for regularized risk minimization
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
KDD (2007), pp. 727-736
-
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
S. V. N. Vishwanathan, Alexander J. Smola, René Vidal
International Journal of Computer Vision, vol. 73 (2007), pp. 95-119
-
Bundle Methods for Machine Learning
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
NIPS (2007)
-
COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking
Markus Weimer, Alexandros Karatzoglou, Quoc V. Le, Alex J. Smola
NIPS (2007)
-
Colored Maximum Variance Unfolding
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arthur Gretton
NIPS (2007)
-
Convex Learning with Invariances
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex J. Smola
NIPS (2007)
-
Direct Optimization of Ranking Measures
Quoc V. Le, Alexander J. Smola
CoRR, vol. abs/0704.3359 (2007)
-
Gene selection via the BAHSIC family of algorithms
Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola
ISMB/ECCB (Supplement of Bioinformatics) (2007), pp. 490-498
-
Learning Graph Matching
Tibério S. Caetano, Li Cheng, Quoc V. Le, Alex J. Smola
ICCV (2007), pp. 1-8
-
Semi-Markov Models for Sequence Segmentation
Qinfeng Shi, Yasemin Altun, Alex J. Smola, S. V. N. Vishwanathan
EMNLP-CoNLL (2007), pp. 640-648
-
Supervised feature selection via dependence estimation
Le Song, Alex J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
ICML (2007), pp. 823-830
-
The Need for Open Source Software in Machine Learning
Soren Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoff Holmes, Yann LeCun, Klaus-Robert Mueller, Fernando Pereira, Carl-Edward Rasmussen, Gunnar Raetsch, Bernhard Schoelkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert C. Williamson
Journal of Machine Learning Research, vol. 8 (2007), pp. 2443-2466
-
A Kernel Method for the Two-Sample-Problem
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
NIPS (2006), pp. 513-520
-
Correcting Sample Selection Bias by Unlabeled Data
Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf
NIPS (2006), pp. 601-608
-
Integrating structured biological data by Kernel Maximum Mean Discrepancy
Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola
ISMB (Supplement of Bioinformatics) (2006), pp. 49-57
-
Kernel extrapolation
S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola
Neurocomputing, vol. 69 (2006), pp. 721-729
-
Kernel methods and the exponential family
Stéphane Canu, Alexander J. Smola
Neurocomputing, vol. 69 (2006), pp. 714-720
-
Learning high-order MRF priors of color images
Julian John McAuley, Tibério S. Caetano, Alex J. Smola, Matthias O. Franz
ICML (2006), pp. 617-624
-
Newton-Like Methods for Nonparametric Independent Component Analysis
Hao Shen, Knut Hüper, Alexander J. Smola
ICONIP (1) (2006), pp. 1068-1077
-
Nonparametric Quantile Estimation
Ichiro Takeuchi, Quoc V. Le, Tim D. Sears, Alexander J. Smola
Journal of Machine Learning Research, vol. 7 (2006), pp. 1231-1264
-
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola
Journal of Machine Learning Research, vol. 7 (2006), pp. 1283-1314
-
Simpler knowledge-based support vector machines
Quoc V. Le, Alex J. Smola, Thomas Gärtner
ICML (2006), pp. 521-528
-
Step Size Adaptation in Reproducing Kernel Hilbert Space
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola
Journal of Machine Learning Research, vol. 7 (2006), pp. 1107-1133
-
Transductive Gaussian Process Regression with Automatic Model Selection
Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun
ECML (2006), pp. 306-317
-
Unifying Divergence Minimization and Statistical Inference Via Convex Duality
Yasemin Altun, Alexander J. Smola
COLT (2006), pp. 139-153
-
Boîte à outils SVM simple et rapide
Gaëlle Loosli, Stéphane Canu, S. V. N. Vishwanathan, Alexander J. Smola, M. Chattopadhyay
Revue d'Intelligence Artificielle, vol. 19 (2005), pp. 741-767
-
Experimentally optimal nu in support vector regression for different noise models and parameter settings
Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Neural Networks, vol. 18 (2005), pp. 205-
-
Heteroscedastic Gaussian process regression
Quoc V. Le, Alexander J. Smola, Stéphane Canu
ICML (2005), pp. 489-496
-
Joint Regularization
Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola
ESANN (2005), pp. 455-460
-
Kernel Methods for Measuring Independence
Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf
Journal of Machine Learning Research, vol. 6 (2005), pp. 2075-2129
-
Kernel methods and the exponential family
Stéphane Canu, Alexander J. Smola
ESANN (2005), pp. 447-454
-
Large-Scale Multiclass Transduction
Thomas Gärtner, Quoc V. Le, Simon Burton, Alex J. Smola, S. V. N. Vishwanathan
NIPS (2005)
-
Learning the Kernel with Hyperkernels
Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
Journal of Machine Learning Research, vol. 6 (2005), pp. 1043-1071
-
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Arthur Gretton, Olivier Bousquet, Alex J. Smola, Bernhard Schölkopf
ALT (2005), pp. 63-77
-
Protein function prediction via graph kernels
Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel
ISMB (Supplement of Bioinformatics) (2005), pp. 47-56
-
Universal Clustering with Regularization in Probabilistic Space
Vladimir Nikulin, Alex J. Smola
MLDM (2005), pp. 142-152
-
A Second Order Cone programming Formulation for Classifying Missing Data
Chiranjib Bhattacharyya, Pannagadatta K. Shivaswamy, Alex J. Smola
NIPS (2004)
-
A tutorial on support vector regression
Alexander J. Smola, Bernhard Schölkopf
Statistics and Computing, vol. 14 (2004), pp. 199-222
-
Binet-Cauchy Kernels
S. V. N. Vishwanathan, Alex J. Smola
NIPS (2004)
-
Experimentally optimal v in support vector regression for different noise models and parameter settings
Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
Neural Networks, vol. 17 (2004), pp. 127-141
-
Exponential Families for Conditional Random Fields
Yasemin Altun, Alexander J. Smola, Thomas Hofmann
UAI (2004), pp. 2-9
-
Gaussian process classification for segmenting and annotating sequences
Yasemin Altun, Thomas Hofmann, Alex J. Smola
ICML (2004)
-
Learning with non-positive kernels
Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola
ICML (2004)
-
Classification in a normalized feature space using support vector machines
Arnulf B. A. Graf, Alexander J. Smola, Silvio Borer
IEEE Transactions on Neural Networks, vol. 14 (2003), pp. 597-605
-
Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces
Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, A.J. Smola, Klaus-Robert Müller
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25 (2003), pp. 623-628
-
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces
Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
IEEE Trans. Pattern Anal. Mach. Intell., vol. 25 (2003), pp. 623-633
-
Kernels and Regularization on Graphs
Alex J. Smola, Risi Imre Kondor
COLT (2003), pp. 144-158
-
Laplace Propagation
Alexander J. Smola, Vishy Vishwanathan, Eleazar Eskin
NIPS (2003)
-
Machine Learning with Hyperkernels
Cheng Soon Ong, Alex J. Smola
ICML (2003), pp. 568-575
-
SimpleSVM
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha Murty
ICML (2003), pp. 760-767
-
A Short Introduction to Learning with Kernels
Bernhard Schölkopf, Alex J. Smola
Machine Learning Summer School (2002), pp. 41-64
-
Adapting Codes and Embeddings for Polychotomies
Gunnar Rätsch, Alexander J. Smola, Sebastian Mika
NIPS (2002), pp. 513-520
-
Bayesian Kernel Methods
Alex J. Smola, Bernhard Schölkopf
Machine Learning Summer School (2002), pp. 65-117
-
Fast Kernels for String and Tree Matching
S. V. N. Vishwanathan, Alexander J. Smola
NIPS (2002), pp. 569-576
-
Hyperkernels
Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson
NIPS (2002), pp. 478-485
-
Large Margin Classification for Moving Targets
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ALT (2002), pp. 113-127
-
Minimal Kernel Classifiers
Glenn Fung, Olvi L. Mangasarian, Alex J. Smola
Journal of Machine Learning Research, vol. 3 (2002), pp. 303-321
-
Multi-Instance Kernels
Thomas Gärtner, Peter A. Flach, Adam Kowalczyk, Alex J. Smola
ICML (2002), pp. 179-186
-
A Generalized Representer Theorem
Bernhard Schölkopf, Ralf Herbrich, Alex J. Smola
COLT/EuroCOLT (2001), pp. 416-426
-
Estimating the Support of a High-Dimensional Distribution
Bernhard Schölkopf, John C. Platt, John Shawe-Taylor, Alex J. Smola, Robert C. Williamson
Neural Computation, vol. 13 (2001), pp. 1443-1471
-
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators
Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
IEEE Transactions on Information Theory, vol. 47 (2001), pp. 2516-2532
-
Kernel Machines and Boolean Functions
Adam Kowalczyk, Alex J. Smola, Robert C. Williamson
NIPS (2001), pp. 439-446
-
Online Learning with Kernels
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
NIPS (2001), pp. 785-792
-
Regularized Principal Manifolds
Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson
Journal of Machine Learning Research, vol. 1 (2001), pp. 179-209
-
Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments
Athanassia Chalimourda, Bernhard Schölkopf, Alex J. Smola
IJCNN (5) (2000), pp. 199-204
-
Entropy Numbers of Linear Function Classes
Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
COLT (2000), pp. 309-319
-
New Support Vector Algorithms
Bernhard Schölkopf, Alex J. Smola, Robert C. Williamson, Peter L. Bartlett
Neural Computation, vol. 12 (2000), pp. 1207-1245
-
Query Learning with Large Margin Classifiers
Colin Campbell, Nello Cristianini, Alex J. Smola
ICML (2000), pp. 111-118
-
Regularization with Dot-Product Kernels
Alex J. Smola, Zoltán L. Óvári, Robert C. Williamson
NIPS (2000), pp. 308-314
-
Robust Ensemble Learning for Data Mining
Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Sebastian Mika, Takashi Onoda, Klaus-Robert Müller
PAKDD (2000), pp. 341-344
-
Sparse Greedy Gaussian Process Regression
Alex J. Smola, Peter L. Bartlett
NIPS (2000), pp. 619-625
-
Sparse Greedy Matrix Approximation for Machine Learning
Alex J. Smola, Bernhard Schölkopf
ICML (2000), pp. 911-918
-
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites
Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Christian Lemmen, Alex J. Smola, Thomas Lengauer, Klaus-Robert Müller
German Conference on Bioinformatics (1999), pp. 37-43
-
Entropy Numbers, Operators and Support Vector Kernels
Robert C. Williamson, Alex J. Smola, Bernhard Schölkopf
EuroCOLT (1999), pp. 285-299
-
Input space versus feature space in kernel-based methods
Bernhard Schölkopf, Sebastian Mika, Christopher J. C. Burges, Phil Knirsch, Klaus-Robert Müller, Gunnar Rätsch, Alexander J. Smola
IEEE Transactions on Neural Networks, vol. 10 (1999), pp. 1000-1017
-
Invariant Feature Extraction and Classification in Kernel Spaces
Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
NIPS (1999), pp. 526-532
-
Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten
Bernhard Schölkopf, Klaus-Robert Müller, Alex J. Smola
Inform., Forsch. Entwickl., vol. 14 (1999), pp. 154-163
-
Regularized Principal Manifolds
Alex J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf
EuroCOLT (1999), pp. 214-229
-
Support Vector Method for Novelty Detection
Bernhard Schölkopf, Robert C. Williamson, Alex J. Smola, John Shawe-Taylor, John C. Platt
NIPS (1999), pp. 582-588
-
The Entropy Regularization Information Criterion
Alex J. Smola, John Shawe-Taylor, Bernhard Schölkopf, Robert C. Williamson
NIPS (1999), pp. 342-348
-
v-Arc: Ensemble Learning in the Presence of Outliers
Gunnar Rätsch, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Takashi Onoda, Sebastian Mika
NIPS (1999), pp. 561-567
-
Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces
Bernhard Schölkopf, Alex J. Smola, Phil Knirsch, Chris Burges
DAGM-Symposium (1998), pp. 125-132
-
Kernel PCA and De-Noising in Feature Spaces
Sebastian Mika, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller, Matthias Scholz, Gunnar Rätsch
NIPS (1998), pp. 536-542
-
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
Neural Computation, vol. 10 (1998), pp. 1299-1319
-
On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion
Alex J. Smola, Bernhard Schölkopf
Algorithmica, vol. 22 (1998), pp. 211-231
-
Semiparametric Support Vector and Linear Programming Machines
Alex J. Smola, Thilo-Thomas Frieß, Bernhard Schölkopf
NIPS (1998), pp. 585-591
-
Shrinking the Tube: A New Support Vector Regression Algorithm
Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, Robert C. Williamson
NIPS (1998), pp. 330-336
-
The connection between regularization operators and support vector kernels
Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller
Neural Networks, vol. 11 (1998), pp. 637-649
-
From Regularization Operators to Support Vector Kernels
Alex J. Smola, Bernhard Schölkopf
NIPS (1997)
-
Kernel Principal Component Analysis
Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller
ICANN (1997), pp. 583-588
-
Predicting Time Series with Support Vector Machines
Klaus-Robert Müller, Alex J. Smola, Gunnar Rätsch, Bernhard Schölkopf, Jens Kohlmorgen, Vladimir Vapnik
ICANN (1997), pp. 999-1004
-
Prior Knowledge in Support Vector Kernels
Bernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik
NIPS (1997)
-
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing
Vladimir Vapnik, Steven E. Golowich, Alex J. Smola
NIPS (1996), pp. 281-287
-
Support Vector Regression Machines
Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik
NIPS (1996), pp. 155-161








