Alexander J. Smola

According to our database1, Alexander J. Smola authored at least 277 papers between 1996 and 2018.

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Bibliography

2018
Detecting and Correcting for Label Shift with Black Box Predictors.
CoRR, 2018

Detecting and Correcting for Label Shift with Black Box Predictors.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Steady-States of Iterative Algorithms over Graphs.
Proceedings of the 35th International Conference on Machine Learning, 2018

Compressed Video Action Recognition.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

A Generic Approach for Escaping Saddle points.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Variational Reasoning for Question Answering With Knowledge Graph.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Compressed Video Action Recognition.
CoRR, 2017

State Space LSTM Models with Particle MCMC Inference.
CoRR, 2017

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning.
CoRR, 2017

Variational Reasoning for Question Answering with Knowledge Graph.
CoRR, 2017

A Generic Approach for Escaping Saddle points.
CoRR, 2017

Efficient Multi-task Feature and Relationship Learning.
CoRR, 2017

Deep Sets.
CoRR, 2017

Sampling Matters in Deep Embedding Learning.
CoRR, 2017

Spectral Methods for Nonparametric Models.
CoRR, 2017

F2F: A Library For Fast Kernel Expansions.
CoRR, 2017

HashBox: Hash Hierarchical Segmentation exploiting Bounding Box Object Detection.
CoRR, 2017

Recurrent Recommender Networks.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Neural Survival Recommender.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Deep Sets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Canopy Fast Sampling with Cover Trees.
Proceedings of the 34th International Conference on Machine Learning, 2017

Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data.
Proceedings of the 34th International Conference on Machine Learning, 2017

Sampling Matters in Deep Embedding Learning.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Neural Machine Translation with Recurrent Attention Modeling.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

Attributing Hacks.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Data Driven Resource Allocation for Distributed Learning.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Data Driven Resource Allocation for Distributed Learning.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference.
ACM TIST, 2016

Trend Filtering on Graphs.
Journal of Machine Learning Research, 2016

Neural Machine Translation with Recurrent Attention Modeling.
CoRR, 2016

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy.
CoRR, 2016

Stochastic Frank-Wolfe Methods for Nonconvex Optimization.
CoRR, 2016

Fast Stochastic Methods for Nonsmooth Nonconvex Optimization.
CoRR, 2016

Fast Incremental Method for Nonconvex Optimization.
CoRR, 2016

AIDE: Fast and Communication Efficient Distributed Optimization.
CoRR, 2016

Stochastic Variance Reduction for Nonconvex Optimization.
CoRR, 2016

Attributing Hacks.
CoRR, 2016

Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering.
Proceedings of the 25th International Conference on World Wide Web, 2016

DiFacto: Distributed Factorization Machines.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Using Navigation to Improve Recommendations in Real-Time.
Proceedings of the 10th ACM Conference on Recommender Systems, 2016

Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variance Reduction in Stochastic Gradient Langevin Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Hierarchical Attention Networks for Document Classification.
Proceedings of the NAACL HLT 2016, 2016

Stochastic Variance Reduction for Nonconvex Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Stacked Attention Networks for Image Question Answering.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Fast incremental method for smooth nonconvex optimization.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Stochastic Frank-Wolfe methods for nonconvex optimization.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

Exponential Stochastic Cellular Automata for Massively Parallel Inference.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

AdaDelay: Delay Adaptive Distributed Stochastic Optimization.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Stacked Attention Networks for Image Question Answering.
CoRR, 2015

Explaining reviews and ratings with PACO: Poisson Additive Co-Clustering.
CoRR, 2015

Fast and Guaranteed Tensor Decomposition via Sketching.
CoRR, 2015

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo.
CoRR, 2015

AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization.
CoRR, 2015

On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants.
CoRR, 2015

Fast Differentially Private Matrix Factorization.
CoRR, 2015

Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning.
CoRR, 2015

Data Driven Resource Allocation for Distributed Learning.
CoRR, 2015

ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly.
CoRR, 2015

ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly.
Proceedings of the 24th International Conference on World Wide Web, 2015

Inferring Movement Trajectories from GPS Snippets.
Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, 2015

Communication Efficient Coresets for Empirical Loss Minimization.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Fast Differentially Private Matrix Factorization.
Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Fast and Guaranteed Tensor Decomposition via Sketching.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Cuckoo Linear Algebra.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Who Supported Obama in 2012?: Ecological Inference through Distribution Regression.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Deep Fried Convnets.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

A la Carte - Learning Fast Kernels.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Trend Filtering on Graphs.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Preferential Attachment in Graphs with Affinities.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Doubly Robust Covariate Shift Correction.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
A la Carte - Learning Fast Kernels.
CoRR, 2014

Deep Fried Convnets.
CoRR, 2014

Trend Filtering on Graphs.
CoRR, 2014

Randomized Nonlinear Component Analysis.
CoRR, 2014

Fastfood: Approximate Kernel Expansions in Loglinear Time.
CoRR, 2014

CoBaFi: collaborative bayesian filtering.
Proceedings of the 23rd International World Wide Web Conference, 2014

Taxonomy discovery for personalized recommendation.
Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising.
Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Scaling Distributed Machine Learning with the Parameter Server.
Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, 2014

Spectral Methods for Indian Buffet Process Inference.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Communication Efficient Distributed Machine Learning with the Parameter Server.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Efficient mini-batch training for stochastic optimization.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Reducing the sampling complexity of topic models.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS).
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

The Falling Factorial Basis and Its Statistical Applications.
Proceedings of the 31th International Conference on Machine Learning, 2014

Randomized Nonlinear Component Analysis.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts.
Proceedings of the 22nd International World Wide Web Conference, 2013

Distributed large-scale natural graph factorization.
Proceedings of the 22nd International World Wide Web Conference, 2013

Hierarchical geographical modeling of user locations from social media posts.
Proceedings of the 22nd International World Wide Web Conference, 2013

Variance Reduction for Stochastic Gradient Optimization.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The dataminer's guide to scalable mixed-membership and nonparametric bayesian models.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Fastfood - Computing Hilbert Space Expansions in loglinear time.
Proceedings of the 30th International Conference on Machine Learning, 2013

Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling.
Proceedings of the 30th International Conference on Machine Learning, 2013

Instant foodie: predicting expert ratings from grassroots.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012
Feature Selection via Dependence Maximization.
Journal of Machine Learning Research, 2012

A Kernel Two-Sample Test.
Journal of Machine Learning Research, 2012

Hokusai - Sketching Streams in Real Time
CoRR, 2012

Exponential Families for Conditional Random Fields
CoRR, 2012

Super-Samples from Kernel Herding
CoRR, 2012

Regret Bounds for Deterministic Gaussian Process Bandits
CoRR, 2012

Discovering geographical topics in the twitter stream.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Fair and balanced: learning to present news stories.
Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Scalable inference in latent variable models.
Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Hokusai - Sketching Streams in Real Time.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Friend or frenemy?: predicting signed ties in social networks.
Proceedings of the 35th International ACM SIGIR conference on research and development in Information Retrieval, 2012

Learning Networks of Heterogeneous Influence.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

FastEx: Hash Clustering with Exponential Families.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Linear support vector machines via dual cached loops.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations.
Proceedings of the 29th International Conference on Machine Learning, 2012

Web-scale multi-task feature selection for behavioral targeting.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Guest editorial: model selection and optimization in machine learning.
Machine Learning, 2011

Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Linear-Time Estimators for Propensity Scores.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Human Action Segmentation and Recognition Using Discriminative Semi-Markov Models.
International Journal of Computer Vision, 2011

Parallel Online Learning
CoRR, 2011

Like like alike: joint friendship and interest propagation in social networks.
Proceedings of the 20th International Conference on World Wide Web, 2011

WWW 2011 invited tutorial overview: latent variable models on the internet.
Proceedings of the 20th International Conference on World Wide Web, 2011

Unified analysis of streaming news.
Proceedings of the 20th International Conference on World Wide Web, 2011

Scalable clustering of news search results.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Bid generation for advanced match in sponsored search.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Collaborative competitive filtering: learning recommender using context of user choice.
Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

Multiple domain user personalization.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Scalable distributed inference of dynamic user interests for behavioral targeting.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010
Discriminative frequent subgraph mining with optimality guarantees.
Statistical Analysis and Data Mining, 2010

An Architecture for Parallel Topic Models.
PVLDB, 2010

Wearable sensor activity analysis using semi-Markov models with a grammar.
Pervasive and Mobile Computing, 2010

Kernelized Sorting.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Bundle Methods for Regularized Risk Minimization.
Journal of Machine Learning Research, 2010

Collaborative Filtering on a Budget.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

IntervalRank: isotonic regression with listwise and pairwise constraints.
Proceedings of the Third International Conference on Web Search and Web Data Mining, 2010

Super-Samples from Kernel Herding.
Proceedings of the UAI 2010, 2010

Parallelized Stochastic Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multitask Learning without Label Correspondences.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Word Features for Latent Dirichlet Allocation.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Optimal Web-Scale Tiering as a Flow Problem.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Hilbert Space Embeddings of Hidden Markov Models.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Distributed Flow Algorithms for Scalable Similarity Visualization.
Proceedings of the ICDMW 2010, 2010

2009
Learning Graph Matching.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Hash Kernels for Structured Data.
Journal of Machine Learning Research, 2009

Hash Kernels.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Estimating Labels from Label Proportions.
Journal of Machine Learning Research, 2009

Relative Novelty Detection.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Feature Hashing for Large Scale Multitask Learning
CoRR, 2009

Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Proceedings of the SIAM International Conference on Data Mining, 2009

Slow Learners are Fast.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Distribution Matching for Transduction.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Feature hashing for large scale multitask learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Hilbert space embeddings of conditional distributions with applications to dynamical systems.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Improving maximum margin matrix factorization.
Machine Learning, 2008

Robust Near-Isometric Matching via Structured Learning of Graphical Models
CoRR, 2008

Learning Graph Matching
CoRR, 2008

A Kernel Method for the Two-Sample Problem
CoRR, 2008

Adaptive collaborative filtering.
Proceedings of the 2008 ACM Conference on Recommender Systems, 2008

Improving Maximum Margin Matrix Factorization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Kernel Measures of Independence for non-iid Data.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Kernelized Sorting.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Robust Near-Isometric Matching via Structured Learning of Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Tighter Bounds for Structured Estimation.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Tailoring density estimation via reproducing kernel moment matching.
Proceedings of the Machine Learning, 2008

Estimating labels from label proportions.
Proceedings of the Machine Learning, 2008

Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning.
Proceedings of the Computational Science, 2008

Discriminative human action segmentation and recognition using semi-Markov model.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
The Need for Open Source Software in Machine Learning.
Journal of Machine Learning Research, 2007

Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes.
International Journal of Computer Vision, 2007

Direct Optimization of Ranking Measures
CoRR, 2007

Supervised Feature Selection via Dependence Estimation
CoRR, 2007

COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking .
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Convex Learning with Invariances.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Colored Maximum Variance Unfolding.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Bundle Methods for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A Kernel Statistical Test of Independence.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Learning Graph Matching.
Proceedings of the Mining and Learning with Graphs, 2007

A scalable modular convex solver for regularized risk minimization.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Gene selection via the BAHSIC family of algorithms.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

Supervised feature selection via dependence estimation.
Proceedings of the Machine Learning, 2007

A dependence maximization view of clustering.
Proceedings of the Machine Learning, 2007

Learning Graph Matching.
Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

Semi-Markov Models for Sequence Segmentation.
Proceedings of the EMNLP-CoNLL 2007, 2007

A Hilbert Space Embedding for Distributions.
Proceedings of the Discovery Science, 10th International Conference, 2007

A Hilbert Space Embedding for Distributions.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

A Kernel Approach to Comparing Distributions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Step Size Adaptation in Reproducing Kernel Hilbert Space.
Journal of Machine Learning Research, 2006

Nonparametric Quantile Estimation.
Journal of Machine Learning Research, 2006

Second Order Cone Programming Approaches for Handling Missing and Uncertain Data.
Journal of Machine Learning Research, 2006

Kernel extrapolation.
Neurocomputing, 2006

Kernel methods and the exponential family.
Neurocomputing, 2006

Correcting Sample Selection Bias by Unlabeled Data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Integrating structured biological data by Kernel Maximum Mean Discrepancy.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Newton-Like Methods for Nonparametric Independent Component Analysis.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Learning high-order MRF priors of color images.
Proceedings of the Machine Learning, 2006

Simpler knowledge-based support vector machines.
Proceedings of the Machine Learning, 2006

Transductive Gaussian Process Regression with Automatic Model Selection.
Proceedings of the Machine Learning: ECML 2006, 2006

Unifying Divergence Minimization and Statistical Inference Via Convex Duality.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
Boîte à outils SVM simple et rapide.
Revue d'Intelligence Artificielle, 2005

Experimentally optimal nu in support vector regression for different noise models and parameter settings.
Neural Networks, 2005

Learning the Kernel with Hyperkernels.
Journal of Machine Learning Research, 2005

Kernel Methods for Measuring Independence.
Journal of Machine Learning Research, 2005

Large-Scale Multiclass Transduction.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Universal Clustering with Regularization in Probabilistic Space.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Step size-adapted online support vector learning.
Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005

Protein function prediction via graph kernels.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Heteroscedastic Gaussian process regression.
Proceedings of the Machine Learning, 2005

Kernel methods and the exponential family.
Proceedings of the ESANN 2005, 2005

Joint Regularization.
Proceedings of the ESANN 2005, 2005

Parametric model-based clustering.
Proceedings of the Data Mining, 2005

Measuring Statistical Dependence with Hilbert-Schmidt Norms.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Kernel Methods for Missing Variables.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

Kernel Constrained Covariance for Dependence Measurement.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Online learning with kernels.
IEEE Trans. Signal Processing, 2004

A tutorial on support vector regression.
Statistics and Computing, 2004

Experimentally optimal v in support vector regression for different noise models and parameter settings.
Neural Networks, 2004

Exponential Families for Conditional Random Fields.
Proceedings of the UAI '04, 2004

Binet-Cauchy Kernels.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

A Second Order Cone programming Formulation for Classifying Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Learning with non-positive kernels.
Proceedings of the Machine Learning, 2004

Gaussian process classification for segmenting and annotating sequences.
Proceedings of the Machine Learning, 2004

2003
Classification in a normalized feature space using support vector machines.
IEEE Trans. Neural Networks, 2003

Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Laplace Propagation.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

SimpleSVM.
Proceedings of the Machine Learning, 2003

Machine Learning with Hyperkernels.
Proceedings of the Machine Learning, 2003

The kernel mutual information.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Kernels and Regularization on Graphs.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Minimal Kernel Classifiers.
Journal of Machine Learning Research, 2002

Fast Kernels for String and Tree Matching.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Adapting Codes and Embeddings for Polychotomies.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Hyperkernels.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Bayesian Kernel Methods.
Proceedings of the Advanced Lectures on Machine Learning, 2002

A Short Introduction to Learning with Kernels.
Proceedings of the Advanced Lectures on Machine Learning, 2002

Multi-Instance Kernels.
Proceedings of the Machine Learning, 2002

Large Margin Classification for Moving Targets.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

Learning with Kernels: support vector machines, regularization, optimization, and beyond.
Adaptive computation and machine learning series, MIT Press, ISBN: 9780262194754, 2002

2001
Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators.
IEEE Trans. Information Theory, 2001

Estimating the Support of a High-Dimensional Distribution.
Neural Computation, 2001

Regularized Principal Manifolds.
Journal of Machine Learning Research, 2001

Kernel Machines and Boolean Functions.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Online Learning with Kernels.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

A Generalized Representer Theorem.
Proceedings of the Computational Learning Theory, 2001

An improved training algorithm for kernel Fisher discriminants.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
New Support Vector Algorithms.
Neural Computation, 2000

Robust Ensemble Learning for Data Mining.
Proceedings of the Knowledge Discovery and Data Mining, 2000

Regularization with Dot-Product Kernels.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Sparse Greedy Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Choosing in Support Vector Regression with Different Noise Models: Theory and Experiments.
IJCNN (5), 2000

Sparse Greedy Matrix Approximation for Machine Learning.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Query Learning with Large Margin Classifiers.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Entropy Numbers of Linear Function Classes.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
Input space versus feature space in kernel-based methods.
IEEE Trans. Neural Networks, 1999

Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten.
Inform., Forsch. Entwickl., 1999

The Entropy Regularization Information Criterion.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Support Vector Method for Novelty Detection.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

v-Arc: Ensemble Learning in the Presence of Outliers.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Invariant Feature Extraction and Classification in Kernel Spaces.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.
German Conference on Bioinformatics, 1999

Entropy Numbers, Operators and Support Vector Kernels.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Regularized Principal Manifolds.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

1998
Learning with kernels.
PhD thesis, 1998

The connection between regularization operators and support vector kernels.
Neural Networks, 1998

Nonlinear Component Analysis as a Kernel Eigenvalue Problem.
Neural Computation, 1998

On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion.
Algorithmica, 1998

Semiparametric Support Vector and Linear Programming Machines.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Shrinking the Tube: A New Support Vector Regression Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Kernel PCA and De-Noising in Feature Spaces.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces.
Proceedings of the Mustererkennung 1998, 20. DAGM-Symposium, Stuttgart, 29. September, 1998

1997
From Regularization Operators to Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Prior Knowledge in Support Vector Kernels.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Kernel Principal Component Analysis.
Proceedings of the Artificial Neural Networks, 1997

Predicting Time Series with Support Vector Machines.
Proceedings of the Artificial Neural Networks, 1997

1996
Support Vector Method for Function Approximation, Regression Estimation and Signal Processing.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Support Vector Regression Machines.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996


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