T. Scheffer

发表

Discriminative learning for differing training and test distributions

Steffen Bickel, Tobias Scheffer, Michael Brückner, 2007, ICML '07.

Co-EM support vector learning

Ulf Brefeld, Tobias Scheffer, Ulf Brefeld, 2004, ICML.

Dirichlet-Enhanced Spam Filtering based on Biased Samples

Steffen Bickel, Tobias Scheffer, S. Bickel, 2006, NIPS.

Transductive support vector machines for structured variables

Alexander Zien, Ulf Brefeld, Tobias Scheffer, 2007, ICML '07.

Discriminative Learning Under Covariate Shift

Steffen Bickel, Tobias Scheffer, Michael Brückner, 2009, J. Mach. Learn. Res..

Static prediction games for adversarial learning problems

Tobias Scheffer, Michael Brückner, Christian Kanzow, 2012, J. Mach. Learn. Res..

Algebraic foundations and improved methods of induction or ripple-down rules

Tobias Scheffer, T. Scheffer, 1996 .

Unsupervised prediction of citation influences

Steffen Bickel, Tobias Scheffer, Laura Dietz, 2007, ICML '07.

Learning with Multiple Views Proposal for an ICML Workshop

S. Rüping, T. Scheffer, 2022 .

Taxonomic metagenome sequence assignment with structured output models

T. Scheffer, P. Turnbaugh, P. B. Pope, 2011, Nature Methods.

Efficient co-regularised least squares regression

Thomas Gärtner, Ulf Brefeld, Stefan Wrobel, 2006, ICML.

Accurate Schema Matching on Streams

T. Scheffer, S. Jaroszewicz, Lenka Ivantysynova, 2006 .

Bayesian Games for Adversarial Regression Problems

Tobias Scheffer, Michael Brückner, Michael Großhans, 2013, ICML.

Active Comparison of Prediction Models ( Online Appendix )

T. Scheffer, Niels Landwehr, Christoph Sawade, 2012 .

Data Mining and Text Mining for Bioinformatics: Proceedings of the European Workshop

T. Scheffer, 2003 .

Active Learning of Partially Hidden Markov Models

Stefan Wrobel, Tobias Scheffer, S. Wrobel, 2001 .

International Conference on Machine Learning (ICML-99)

Tobias Scheffer, T. Scheffer, 1999, Künstliche Intell..

Clipping and Analyzing News Using Machine Learning Techniques

Tobias Scheffer, Tino Naphtali, Hans Gründel, 2001, Discovery Science.

Proceedings of the 17th European conference on Machine Learning

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Discriminative Identification of Duplicates

Ulf Brefeld, T. Scheffer, P. Haider, 2006 .

Detection of ADHD based on Eye Movements during Natural Viewing

T. Scheffer, N. Langer, L. Jäger, 2022, ECML/PKDD.

Detection of ADHD based on Eye Movements during Natural Viewing

T. Scheffer, N. Langer, L. Jäger, 2022, ECML/PKDD.

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

T. Scheffer, R. Herwig, M. Lienhard, 2022, Cancers.

Proceedings of the Workshops on Learning, Knowledge Discovery, and Adaptivity (LWA)

Ulf Brefeld, Steffen Bickel, Tobias Scheffer, 2004 .

A Model of Individual Differences in Gaze Control During Reading

Reinhold Kliegl, Tobias Scheffer, Niels Landwehr, 2014, EMNLP.

Oculomotoric Biometric Identification and Presentation-Attack Detection using Deep Neural Networks

T. Scheffer, L. Jäger, Paul Prasse, 2021 .

Detecting Autism by Analyzing a Simulated Social Interaction

Tobias Scheffer, Niels Landwehr, Isabel Dziobek, 2018, ECML/PKDD.

Discriminative Learning under Covariate Shift with a Single Optimization Problem

Steffen Bickel, Tobias Scheffer, Michael Brückner, 2009 .

Predicting the Generalization Performance of Cross Validatory Model Selection Criteria

Tobias Scheffer, T. Scheffer, 2000, ICML.

Proceedings of the 8th international conference on Discovery Science

Achim G. Hoffmann, Hiroshi Motoda, Tobias Scheffer, 2005 .

Learning With Multiple Views

Tobias Scheffer, Stefan Rüping, S. Rüping, 2005 .

Lerning Hidden Markov Models for Information Extraction Actively from Partially Labeled Text

Susanne Hoche, Stefan Wrobel, Tobias Scheffer, 2002, Künstliche Intell..

Learning Game Theoretic Model Parameters Applied to Adversarial Classiﬁcation

Tobias Scheffer, Orhan Sönmez, T. Scheffer, 2008 .

Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems

Stefan Wrobel, Tobias Scheffer, S. Wrobel, 2001, ICML.

On the Relationship between Eye Tracking Resolution and Performance of Oculomotoric Biometric Identification

Tobias Scheffer, Paul Prasse, Lena A. Jäger, 2020, KES.

Fairness in Oculomotoric Biometric Identification

T. Scheffer, L. Jäger, Paul Prasse, 2022, ETRA.

RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

Tobias Scheffer, Maik Heistermann, Georgy Ayzel, 2020 .

Proceedings of the Twenty-Eighth International Conference on Machine Learning

Lise Getoor, Tobias Scheffer, L. Getoor, 2011 .

Knowledge Discovery in Databases: PKDD 2006: 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September ... (Lecture Notes in Computer Science)

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006 .

Active evaluation of ranking functions based on graded relevance

S. Bickel, T. Scheffer, Niels Landwehr, 2013, Machine Learning.

Matching anticancer compounds and tumor cell lines by neural networks with ranking loss

T. Scheffer, R. Herwig, M. Lienhard, 2022, NAR genomics and bioinformatics.

Multi-view clustering

Steffen Bickel, Tobias Scheffer, S. Bickel, 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

Estimation of Mixture Models Using Co-EM

Steffen Bickel, Tobias Scheffer, S. Bickel, 2005, ECML.

Multi-view Discriminative Sequential Learning

Ulf Brefeld, Tobias Scheffer, Christoph Büscher, 2005, ECML.

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

Tobias Scheffer, Mark-A. Krogel, T. Scheffer, 2004, Machine Learning.

Effectiveness of information extraction, multi-relational, and multi-view learning for prediction gene deletion experiments

Tobias Scheffer, Mark-A. Krogel, T. Scheffer, 2003, BIOKDD.

Clipping and Analyzing News Using Machine Learning Techniques

T. Scheffer, H. Gründel, Tino Naphtali, 2001, Discovery Science.

Active Hidden Markov Models for Information Extraction

Stefan Wrobel, Tobias Scheffer, Christian Decomain, 2001, IDA.

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

T. Scheffer, J. Schuchhardt, R. Herwig, 2021, Journal of Translational Medicine.

Scalable pattern mining with Bayesian networks as background knowledge

Szymon Jaroszewicz, Dan A. Simovici, Tobias Scheffer, 2009, Data Mining and Knowledge Discovery.

Semi-supervised learning for structured output variables

Ulf Brefeld, Tobias Scheffer, Ulf Brefeld, 2006, ICML.

Towards the automatic detection of social biomarkers in autism spectrum disorder: introducing the simulated interaction task (SIT)

T. Scheffer, I. Dziobek, Niels Landwehr, 2020, npj Digital Medicine.

Highly Scalable Discriminative Spam Filtering

Peter Haider, Tobias Scheffer, Michael Brückner, 2006, TREC.

Mining the Web with active hidden Markov models

Stefan Wrobel, Tobias Scheffer, Christian Decomain, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

Learning to Identify Regular Expressions that Describe Email Campaigns pdf

Tobias Scheffer, Christoph Sawade, Niels Landwehr, 2012, ICML.

Joint detection of malicious domains and infected clients

Tobias Scheffer, René Knaebel, Tomáš Pevný, 2019, Machine Learning.

Stackelberg games for adversarial prediction problems

Tobias Scheffer, Michael Brückner, Michael Brückner, 2011, KDD.

Nash Equilibria of Static Prediction Games

Tobias Scheffer, Michael Brückner, Michael Brückner, 2009, NIPS.

Thwarting the Nigritude Ultramarine: Learning to Identify Link Spam

Tobias Scheffer, Isabel Drost, T. Scheffer, 2005, ECML.

RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

Tobias Scheffer, G. V. Ayzel, Maik Heistermann, 2020, Geoscientific Model Development.

Finding association rules that trade support optimally against confidence

Tobias Scheffer, T. Scheffer, 2001, Intell. Data Anal..

Using Transduction and Multi-view Learning to Answer Emails

Tobias Scheffer, Michael Kockelkorn, Andreas Lüneburg, 2003, PKDD.

Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling

Stefan Wrobel, Tobias Scheffer, S. Wrobel, 2003, J. Mach. Learn. Res..

A sequential sampling algorithm for a general class of utility criteria

Stefan Wrobel, Tobias Scheffer, S. Wrobel, 2000, KDD '00.

Solving Prediction Games with Parallel Batch Gradient Descent

Tobias Scheffer, Michael Großhans, T. Scheffer, 2015, ECML/PKDD.

Localizing Bugs in Program Executions with Graphical Models

Andreas Zeller, Tobias Scheffer, Laura Dietz, 2009, NIPS.

A Nonergodic Ground‐Motion Model for California with Spatially Varying Coefficients

Tobias Scheffer, Norman A. Abrahamson, Niels Landwehr, 2016 .

Predicting Sentences using N-Gram Language Models

Peter Haider, Steffen Bickel, Tobias Scheffer, 2005, HLT.

Sentence Completion

Tobias Scheffer, Korinna Grabski, T. Scheffer, 1921, SIGIR '04.

Generation of task-specific segmentation procedures as a model selection task

Tobias Scheffer, Ralf Herbrich, R. Herbrich, 1998 .

A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases

Stefan Wrobel, Tobias Scheffer, S. Wrobel, 2002, PKDD.

Error Estimation and Model Selection

Tobias Scheffer, T. Scheffer, 1999, Künstliche Intell..

Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models

S. Lapuschkin, T. Scheffer, L. Jäger, 2023, ETRA.

Selection of XAI Methods Matters: Evaluation of Feature Attribution Methods for Oculomotoric Biometric Identification

S. Lapuschkin, T. Scheffer, L. Jäger, 2022 .

SP-EyeGAN: Generating Synthetic Eye Movement Data with Generative Adversarial Networks

T. Scheffer, L. Jäger, Seoyoung Ahn, 2023, ETRA.

Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading

T. Scheffer, Paul Prasse, Patrick Haller, 2023, Proc. ACM Hum. Comput. Interact..

DeepEyedentificationLive: Oculomotoric Biometric Identification and Presentation-Attack Detection Using Deep Neural Networks

Tobias Scheffer, Daniel Krakowczyk, Paul Prasse, 2021, IEEE Transactions on Biometrics, Behavior, and Identity Science.

Varying-coefficient models for geospatial transfer learning

Tobias Scheffer, Christoph Sawade, Niels Landwehr, 2017, Machine Learning.

Classifying search engine queries using the web as background knowledge

Peter Haider, Steffen Bickel, Tobias Scheffer, 2005, SKDD.

Multi-task learning for HIV therapy screening

Thomas Lengauer, Steffen Bickel, Tobias Scheffer, 2008, ICML '08.

Biometric Identification and Presentation-Attack Detection using Micro- and Macro-Movements of the Eyes

Lena A. Jäger, Silvia Makowski, Paul Prasse, 2020, 2020 IEEE International Joint Conference on Biometrics (IJCB).

Discriminative Viewer Identification using Generative Models of Eye Gaze

Tobias Scheffer, Ralf Engbert, Silvia Makowski, 2020, KES.

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye pdf

Sascha Liehr, Tobias Scheffer, Paul Prasse, 2019, ECML/PKDD.

A Discriminative Model for Identifying Readers and Assessing Text Comprehension from Eye Movements

Tobias Scheffer, Niels Landwehr, Lena A. Jäger, 2018, ECML/PKDD.

Huber-Norm Regularization for Linear Prediction Models

Marius Kloft, Tobias Scheffer, Stephan Mandt, 2016, ECML/PKDD.

The VC-Dimension of Subclasses of Pattern

Arun Sharma, Frank Stephan, Tobias Scheffer, 1999, ALT.

Multi-view clustering

S. Bickel, T. Scheffer, 2004 .

A Generic Algorithm for Learning Rules with Hierarchical Exceptions

Tobias Scheffer, T. Scheffer, 1995, SBIA.

Learning from Message Pairs for Automatic Email Answering

Steffen Bickel, Tobias Scheffer, S. Bickel, 2004, ECML.

Learning to identify concise regular expressions that describe email campaigns

Tobias Scheffer, Christoph Sawade, Niels Landwehr, 2015, J. Mach. Learn. Res..

Malware Detection by Analysing Encrypted Network Traffic with Neural Networks

Tobias Scheffer, Tomás Pevný, Lukás Machlica, 2017, ECML/PKDD.

Malware Detection by Analysing Network Traffic with Neural Networks

Tobias Scheffer, Tomás Pevný, Lukás Machlica, 2017, 2017 IEEE Security and Privacy Workshops (SPW).

Malware Detection by HTTPS Traffic Analysis

Tobias Scheffer, Michal Sofka, Tomas Pevny, 2017 .

{AUC} maximizing support vector learning

Ulf Brefeld, Tobias Scheffer, Ulf Brefeld, 2005 .

Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings

Johannes Fürnkranz, Myra Spiliopoulou, Tobias Scheffer, 2006, ECML.

Nonparametric Regularization of Decision Trees

Tobias Scheffer, T. Scheffer, 2000, ECML.

Active Comparison of Prediction Models

Tobias Scheffer, Christoph Sawade, Niels Landwehr, 2012, NIPS.

Active Risk Estimation

Steffen Bickel, Tobias Scheffer, Christoph Sawade, 2010, ICML.

Learning from incomplete data with infinite imputations

Peter Haider, Tobias Scheffer, Uwe Dick, 2008, ICML '08.

Combining data and text mining techniques for yeast gene regulation prediction: a case study

Tobias Scheffer, Mark-A. Krogel, Marcus Denecke, 2002, SKDD.

A Support Vector Machine Classifier for Gene Name Recognition

Ulf Leser, Jörg Hakenberg, Ulf Brefeld, 2004 .

Active evaluation of ranking functions based on graded relevance

S. Bickel, T. Scheffer, Niels Landwehr, 2012, Machine Learning.

Systematic feature evaluation for gene name recognition

Ulf Leser, Jörg Hakenberg, Ulf Brefeld, 2005, BMC Bioinformatics.

Multi-View Hidden Markov Perceptrons

Ulf Brefeld, Tobias Scheffer, Christoph Büscher, 2005, LWA.

Learning to control a structured-prediction decoder for detection of HTTP-layer DDoS attackers

T. Scheffer, Uwe Dick, 2016, Machine Learning.

Discovering Communities in Linked Data by Multi-view Clustering

Steffen Bickel, Tobias Scheffer, Isabel Drost, 2005, GfKl.

Efficiency and Stability of Clustering Algorithms for Linked Data

Tobias Scheffer, Isabel Drost, T. Scheffer, 2004, LWA.

Why Experimentation can be better than "Perfect Guidance"

Russell Greiner, Tobias Scheffer, Christian J. Darken, 1997, ICML.

Transfer Learning by Distribution Matching for Targeted Advertising

Steffen Bickel, Tobias Scheffer, Christoph Sawade, 2008, NIPS.