Tobias Scheffer

According to our database1, Tobias Scheffer authored at least 96 papers between 1995 and 2018.

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Bibliography

2018
A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements.
CoRR, 2018

2017
Varying-coefficient models for geospatial transfer learning.
Machine Learning, 2017

Malware Detection by Analysing Network Traffic with Neural Networks.
Proceedings of the 2017 IEEE Security and Privacy Workshops, 2017

Malware Detection by Analysing Encrypted Network Traffic with Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016
Learning to control a structured-prediction decoder for detection of HTTP-layer DDoS attackers.
Machine Learning, 2016

Huber-Norm Regularization for Linear Prediction Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

2015
Learning to identify concise regular expressions that describe email campaigns.
Journal of Machine Learning Research, 2015

Varying-coefficient models with isotropic Gaussian process priors.
CoRR, 2015

Solving Prediction Games with Parallel Batch Gradient Descent.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Joint Prediction of Topics in a URL Hierarchy.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

A Model of Individual Differences in Gaze Control During Reading.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2013
Active evaluation of ranking functions based on graded relevance.
Machine Learning, 2013

Active Evaluation of Ranking Functions Based on Graded Relevance (Extended Abstract).
Proceedings of the IJCAI 2013, 2013

Bayesian Games for Adversarial Regression Problems.
Proceedings of the 30th International Conference on Machine Learning, 2013

Lagrangian Strain Tensor Computation with Higher Order Variational Models.
Proceedings of the British Machine Vision Conference, 2013

2012
Static prediction games for adversarial learning problems.
Journal of Machine Learning Research, 2012

Finding Botnets Using Minimal Graph Clusterings
CoRR, 2012

Learning to Identify Regular Expressions that Describe Email Campaigns
CoRR, 2012

Active Evaluation of Ranking Functions Based on Graded Relevance.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Active Comparison of Prediction Models.
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

Learning to Identify Regular Expressions that Describe Email Campaigns.
Proceedings of the 29th International Conference on Machine Learning, 2012

Finding Botnets Using Minimal Graph Clusterings.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Stackelberg games for adversarial prediction problems.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010
Active Estimation of F-Measures.
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

Throttling Poisson Processes.
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

Active Risk Estimation.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009
Semi-Supervised Learning.
Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Discriminative Learning Under Covariate Shift.
Journal of Machine Learning Research, 2009

Scalable pattern mining with Bayesian networks as background knowledge.
Data Min. Knowl. Discov., 2009

Localizing Bugs in Program Executions with Graphical Models.
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

Nash Equilibria of Static Prediction Games.
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

Bayesian clustering for email campaign detection.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Schema matching on streams with accuracy guarantees.
Intell. Data Anal., 2008

Exact and Approximate Inference for Annotating Graphs with Structural SVMs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Transfer Learning by Distribution Matching for Targeted Advertising.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Learning from incomplete data with infinite imputations.
Proceedings of the Machine Learning, 2008

Multi-task learning for HIV therapy screening.
Proceedings of the Machine Learning, 2008

2007
Support Vector Machines for Collective Inference.
Proceedings of the Mining and Learning with Graphs, 2007

Scalable look-ahead linear regression trees.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Transductive support vector machines for structured variables.
Proceedings of the Machine Learning, 2007

Supervised clustering of streaming data for email batch detection.
Proceedings of the Machine Learning, 2007

Unsupervised prediction of citation influences.
Proceedings of the Machine Learning, 2007

Discriminative learning for differing training and test distributions.
Proceedings of the Machine Learning, 2007

2006
Highly Scalable Discriminative Spam Filtering.
Proceedings of the Fifteenth Text REtrieval Conference, 2006

Dirichlet-Enhanced Spam Filtering based on Biased Samples.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Semi-supervised learning for structured output variables.
Proceedings of the Machine Learning, 2006

Efficient co-regularised least squares regression.
Proceedings of the Machine Learning, 2006

2005
Classifying search engine queries using the web as background knowledge.
SIGKDD Explorations, 2005

Finding association rules that trade support optimally against confidence.
Intell. Data Anal., 2005

Systematic feature evaluation for gene name recognition.
BMC Bioinformatics, 2005

Predicting Sentences using N-Gram Language Models.
Proceedings of the HLT/EMNLP 2005, 2005

Multi-View Hidden Markov Perceptrons.
Proceedings of the Lernen, 2005

Fast discovery of unexpected patterns in data, relative to a Bayesian network.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Discovering Communities in Linked Data by Multi-view Clustering.
Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam.
Proceedings of the Machine Learning: ECML 2005, 2005

Multi-view Discriminative Sequential Learning.
Proceedings of the Machine Learning: ECML 2005, 2005

Estimation of Mixture Models Using Co-EM.
Proceedings of the Machine Learning: ECML 2005, 2005

Learning to Complete Sentences.
Proceedings of the Machine Learning: ECML 2005, 2005

Multi-View Learning and Link Farm Discovery.
Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005

2004
Multi-Relational Learning, Text Mining, and Semi-Supervised Learning for Functional Genomics.
Machine Learning, 2004

Email answering assistance by semi-supervised text classification.
Intell. Data Anal., 2004

Sentence completion.
Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Workshop der GI-Fachgruppe "Maschinelles Lernen" (FGML).
Proceedings of the LWA 2004: Lernen - Wissensentdeckung - Adaptivität, Berlin, 4., 2004

Efficiency and Stability of Clustering Algorithms for Linked Data.
Proceedings of the LWA 2004: Lernen - Wissensentdeckung - Adaptivität, Berlin, 4., 2004

Multi-View Lernen.
Proceedings of the LWA 2004: Lernen - Wissensentdeckung - Adaptivität, Berlin, 4., 2004

Co-EM support vector learning.
Proceedings of the Machine Learning, 2004

Multi-View Clustering.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

Learning from Message Pairs for Automatic Email Answering.
Proceedings of the Machine Learning: ECML 2004, 2004

2003
Using Transduction and Multi-view Learning to Answer Emails.
Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

Effectiveness of information extraction, multi-relational, and multi-view learning for prediction gene deletion experiments.
Proceedings of the 3nd ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2003), 2003

Learning to Answer Emails.
Proceedings of the Advances in Intelligent Data Analysis V, 2003

Effectiveness of Information Extraction, Multi-Relational, and Semi-Supervised Learning for Predicting Functional Properties of Genes.
Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

2002
Combining Data and Text Mining Techniques for Yeast Gene Regulation Prediction: A Case Study.
SIGKDD Explorations, 2002

Lerning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text.
KI, 2002

Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling.
Journal of Machine Learning Research, 2002

A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2002

2001
Finding Association Rules That Trade Support Optimally against Confidence.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2001

Active Hidden Markov Models for Information Extraction.
Proceedings of the Advances in Intelligent Data Analysis, 4th International Conference, 2001

Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Mining the Web with Active Hidden Markov Models.
Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November, 2001

Clipping and Analyzing News Using Machine Learning Techniques.
Proceedings of the Discovery Science, 4th International Conference, DS 2001, Washington, 2001

2000
A sequential sampling algorithm for a general class of utility criteria.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

Predicting the Generalization Performance of Cross Validatory Model Selection Criteria.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Nonparametric Regularization of Decision Trees.
Proceedings of the Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31, 2000

Average-Case Analysis of Classification Algorithms for Boolean Functions and Decision Trees.
Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

1999
Error Estimation and Model Selection.
KI, 1999

International Conference on Machine Learning (ICML-99).
KI, 1999

Expected Error Analysis for Model Selection.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

The VC-Dimension of Subclasses of Pattern.
Proceedings of the Algorithmic Learning Theory, 10th International Conference, 1999

Error estimation and model selection.
DISKI 225, Infix, ISBN: 978-3-89601-225-8, 1999

1998
Estimating the Expected Error of Empirical Minimizers for Model Selection.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997
Unbiased Assesment of Learning Algorithms.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Why Experimentation can be better than "Perfect Guidance".
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
Aerial Robotics in Computer Science Education.
Computer Science Education, 1996

Efficient Theta-Subsumption Based on Graph Algorithms.
Proceedings of the Inductive Logic Programming, 6th International Workshop, 1996

1995
A Generic Algorithm for Learning Rules with Hierarchical Exceptions.
Proceedings of the Advances in Artificial Intelligence, 1995


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