2013
77Distributed large-scale natural graph factorization. Amr Ahmed, Nino Shervashidze, Shravan M. Narayanamurthy, Vanja Josifovski, Alexander J. Smola. WWW 2013, 37-48. Web SearchBibTeXDownload
76Hierarchical geographical modeling of user locations from social media posts. Amr Ahmed, Liangjie Hong, Alexander J. Smola. WWW 2013, 25-36. Web SearchBibTeXDownload
2012
75Web-scale multi-task feature selection for behavioral targeting. Amr Ahmed, Mohamed Aly, Abhimanyu Das, Alexander J. Smola, Tasos Anastasakos. CIKM 2012, 1737-1741. Web SearchBibTeXDownload
74Exponential Families for Conditional Random Fields. Yasemin Altun, Alexander J. Smola, Thomas Hofmann. CoRR (abs/1207.4131) (2012). Web SearchBibTeXDownload
73A Kernel Two-Sample Test. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola. Journal of Machine Learning Research (13): 723-773 (2012). Web SearchBibTeXDownload
72Linear support vector machines via dual cached loops. Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola. KDD 2012, 177-185. Web SearchBibTeXDownload
71FastEx: Hash Clustering with Exponential Families. Amr Ahmed, Sujith Ravi, Shravan M. Narayanamurthy, Alexander J. Smola. NIPS 2012, 2807-2815. Web SearchBibTeXDownload
70Friend or frenemy?: predicting signed ties in social networks. Shuang-Hong Yang, Alexander J. Smola, Bo Long, Hongyuan Zha, Yi Chang. SIGIR 2012, 555-564. Web SearchBibTeXDownload
69Hokusai - Sketching Streams in Real Time. Sergiy Matusevych, Alexander J. Smola, Amr Ahmed. UAI 2012, 594-603. Web SearchBibTeXDownload
68Scalable inference in latent variable models. Amr Ahmed, Mohamed Aly, Joseph Gonzalez, Shravan M. Narayanamurthy, Alexander J. Smola. WSDM 2012, 123-132. Web SearchBibTeXDownload
67Discovering geographical topics in the twitter stream. Liangjie Hong, Amr Ahmed, Siva Gurumurthy, Alexander J. Smola, Kostas Tsioutsiouliklis. WWW 2012, 769-778. Web SearchBibTeXDownload
2011
66Parallel Online Learning. Daniel Hsu, Nikos Karampatziakis, John Langford, Alexander J. Smola. CoRR (abs/1103.4204) (2011). Web SearchBibTeXDownload
65Linear-Time Estimators for Propensity Scores. Deepak Agarwal, Lihong Li, Alexander J. Smola. Journal of Machine Learning Research - Proceedings Track (15): 93-100 (2011). Web SearchBibTeXDownload
64Online 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 (15): 101-109 (2011). Web SearchBibTeXDownload
63Scalable distributed inference of dynamic user interests for behavioral targeting. Amr Ahmed, Yucheng Low, Mohamed Aly, Vanja Josifovski, Alexander J. Smola. KDD 2011, 114-122. Web SearchBibTeXDownload
62Multiple domain user personalization. Yucheng Low, Deepak Agarwal, Alexander J. Smola. KDD 2011, 123-131. Web SearchBibTeXDownload
61Guest editorial: model selection and optimization in machine learning. Süreyya Özögür-Akyüz, Devrim Ünay, Alexander J. Smola. Machine Learning (85): 1-2 (2011). Web SearchBibTeXDownload
60Collaborative competitive filtering: learning recommender using context of user choice. Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hongyuan Zha, Zhaohui Zheng. SIGIR 2011, 295-304. Web SearchBibTeXDownload
59Scalable 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, 675-684. Web SearchBibTeXDownload
58Unified analysis of streaming news. Amr Ahmed, Qirong Ho, Jacob Eisenstein, Eric P. Xing, Alexander J. Smola, Choon Hui Teo. WWW 2011, 267-276. Web SearchBibTeXDownload
57Like 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, 537-546. Web SearchBibTeXDownload
56WWW 2011 invited tutorial overview: latent variable models on the internet. Amr Ahmed, Alexander J. Smola. WWW (Companion Volume) 2011, 281-282. Web SearchBibTeXDownload
2010
55Hilbert Space Embeddings of Hidden Markov Models. Le Song, Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon, Alexander J. Smola. ICML 2010, 991-998. Web SearchBibTeXDownload
54Collaborative Filtering on a Budget. Alexandros Karatzoglou, Alexander J. Smola, Markus Weimer. Journal of Machine Learning Research - Proceedings Track (9): 389-396 (2010). Web SearchBibTeXDownload
53Word Features for Latent Dirichlet Allocation. James Petterson, Alexander J. Smola, Tibério S. Caetano, Wray L. Buntine, Shravan Narayanamurthy. NIPS 2010, 1921-1929. Web SearchBibTeXDownload
52Multitask Learning without Label Correspondences. Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson. NIPS 2010, 1957-1965. Web SearchBibTeXDownload
51Parallelized Stochastic Gradient Descent. Martin Zinkevich, Markus Weimer, Alexander J. Smola, Lihong Li. NIPS 2010, 2595-2603. Web SearchBibTeXDownload
50Optimal Web-Scale Tiering as a Flow Problem. Gilbert Leung, Novi Quadrianto, Alexander J. Smola, Kostas Tsioutsiouliklis. NIPS 2010, 1333-1341. Web SearchBibTeXDownload
49Wearable 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 (6): 342-350 (2010). Web SearchBibTeXDownload
48An Architecture for Parallel Topic Models. Alexander J. Smola, Shravan Narayanamurthy. PVLDB (3): 703-710 (2010). Web SearchBibTeXDownload
47Discriminative 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 (3): 302-318 (2010). Web SearchBibTeXDownload
2009
46Hilbert space embeddings of conditional distributions with applications to dynamical systems. Le Song, Jonathan Huang, Alexander J. Smola, Kenji Fukumizu. ICML 2009, 121. Web SearchBibTeXDownload
45Feature hashing for large scale multitask learning. Kilian Q. Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg. ICML 2009, 140. Web SearchBibTeXDownload
44Learning Graph Matching. Tibério S. Caetano, Julian John McAuley, Li Cheng, Quoc V. Le, Alexander J. Smola. IEEE Trans. Pattern Anal. Mach. Intell. (31): 1048-1058 (2009). Web SearchBibTeXDownload
43Hash Kernels for Structured Data. Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, S. V. N. Vishwanathan. Journal of Machine Learning Research (10): 2615-2637 (2009). Web SearchBibTeXDownload
42Relative Novelty Detection. Alexander J. Smola, Le Song, Choon Hui Teo. Journal of Machine Learning Research - Proceedings Track (5): 536-543 (2009). Web SearchBibTeXDownload
41Hash Kernels. Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan. Journal of Machine Learning Research - Proceedings Track (5): 496-503 (2009). Web SearchBibTeXDownload
40Near-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, 1075-1086. Cited by 5Web SearchBibTeXDownload
2008
39A Kernel Method for the Two-Sample Problem. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola. CoRR (abs/0805.2368) (2008). Web SearchBibTeXDownload
38Discriminative human action segmentation and recognition using semi-Markov model. Qinfeng Shi, Li Wang, Li Cheng, Alexander J. Smola. CVPR 2008. Web SearchBibTeXDownload
37Robust Near-Isometric Matching via Structured Learning of Graphical Models. Julian John McAuley, Tibério S. Caetano, Alexander J. Smola. NIPS 2008, 1057-1064. Web SearchBibTeXDownload
36Tighter Bounds for Structured Estimation. Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo. NIPS 2008, 281-288. Web SearchBibTeXDownload
2007
35A Kernel Approach to Comparing Distributions. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola. AAAI 2007, 1637-1641. Web SearchBibTeXDownload
34Supervised Feature Selection via Dependence Estimation. Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo. CoRR (abs/0704.2668) (2007). Web SearchBibTeXDownload
33Direct Optimization of Ranking Measures. Quoc V. Le, Alexander J. Smola. CoRR (abs/0704.3359) (2007). Web SearchBibTeXDownload
32A Hilbert Space Embedding for Distributions. Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schölkopf. Discovery Science 2007, 40-41. Web SearchBibTeXDownload
31A dependence maximization view of clustering. Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt. ICML 2007, 815-822. Web SearchBibTeXDownload
30Binet-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 (73): 95-119 (2007). Web SearchBibTeXDownload
29Gene 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, 490-498. Web SearchBibTeXDownload
28The Need for Open Source Software in Machine Learning. Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson. Journal of Machine Learning Research (8): 2443-2466 (2007). Web SearchBibTeXDownload
2006
27Unifying Divergence Minimization and Statistical Inference Via Convex Duality. Yasemin Altun, Alexander J. Smola. COLT 2006, 139-153. Web SearchBibTeXDownload
26Transductive Gaussian Process Regression with Automatic Model Selection. Quoc V. Le, Alexander J. Smola, Thomas Gärtner, Yasemin Altun. ECML 2006, 306-317. Web SearchBibTeXDownload
25Newton-Like Methods for Nonparametric Independent Component Analysis. Hao Shen, Knut Hüper, Alexander J. Smola. ICONIP (1) 2006, 1068-1077. Web SearchBibTeXDownload
24Integrating 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, 49-57. Cited by 41Web SearchBibTeXDownload
23Second Order Cone Programming Approaches for Handling Missing and Uncertain Data. Pannagadatta K. Shivaswamy, Chiranjib Bhattacharyya, Alexander J. Smola. Journal of Machine Learning Research (7): 1283-1314 (2006). Web SearchBibTeXDownload
22Nonparametric Quantile Estimation. Ichiro Takeuchi, Quoc V. Le, Tim D. Sears, Alexander J. Smola. Journal of Machine Learning Research (7): 1231-1264 (2006). Web SearchBibTeXDownload
21Kernel extrapolation. S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola. Neurocomputing (69): 721-729 (2006). Web SearchBibTeXDownload
20Kernel methods and the exponential family. Stéphane Canu, Alexander J. Smola. Neurocomputing (69): 714-720 (2006). Web SearchBibTeXDownload
19Correcting Sample Selection Bias by Unlabeled Data. Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf. NIPS 2006, 601-608. Web SearchBibTeXDownload
18A Kernel Method for the Two-Sample-Problem. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola. NIPS 2006, 513-520. Web SearchBibTeXDownload
2005
17Kernel methods and the exponential family. Stéphane Canu, Alexander J. Smola. ESANN 2005, 447-454. Web SearchBibTeXDownload
16Joint Regularization. Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola. ESANN 2005, 455-460. Web SearchBibTeXDownload
15Heteroscedastic Gaussian process regression. Quoc V. Le, Alexander J. Smola, Stéphane Canu. ICML 2005, 489-496. Web SearchBibTeXDownload
14Protein 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, 47-56. Cited by 90Web SearchBibTeXDownload
13Step size-adapted online support vector learning. Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola. ISSPA 2005, 823-826. Web SearchBibTeXDownload
12Kernel Methods for Measuring Independence. Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf. Journal of Machine Learning Research (6): 2075-2129 (2005). Web SearchBibTeXDownload
11Learning the Kernel with Hyperkernels. Cheng Soon Ong, Alexander J. Smola, Robert C. Williamson. Journal of Machine Learning Research (6): 1043-1071 (2005). Web SearchBibTeXDownload
10Boîte à outils SVM simple et rapide. Gaëlle Loosli, Stéphane Canu, S. V. N. Vishwanathan, Alexander J. Smola, M. Chattopadhyay. Revue d'Intelligence Artificielle (19): 741-767 (2005). Web SearchBibTeXDownload
2004
9Learning with non-positive kernels. Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola. ICML 2004. Web SearchBibTeXDownload
8Online learning with kernels. Jyrki Kivinen, Alexander J. Smola, Robert C. Williamson. IEEE Transactions on Signal Processing (52): 2165-2176 (2004). Web SearchBibTeXDownload
7A tutorial on support vector regression. Alexander J. Smola, Bernhard Schölkopf. Statistics and Computing (14): 199-222 (2004). Web SearchBibTeXDownload
6Exponential Families for Conditional Random Fields. Yasemin Altun, Alexander J. Smola, Thomas Hofmann. UAI 2004, 2-9. Web SearchBibTeXDownload
2003
5Classification in a normalized feature space using support vector machines. Arnulf B. A. Graf, Alexander J. Smola, Silvio Borer. IEEE Transactions on Neural Networks (14): 597-605 (2003). Web SearchBibTeXDownload
4Laplace Propagation. Alexander J. Smola, Vishy Vishwanathan, Eleazar Eskin. NIPS 2003. Web SearchBibTeXDownload
2002
3Fast Kernels for String and Tree Matching. S. V. N. Vishwanathan, Alexander J. Smola. NIPS 2002, 569-576. Web SearchBibTeXDownload
2Adapting Codes and Embeddings for Polychotomies. Gunnar Rätsch, Alexander J. Smola, Sebastian Mika. NIPS 2002, 513-520. Web SearchBibTeXDownload
1999
1Input 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 (10): 1000-1017 (1999). Web SearchBibTeXDownload
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References
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