Johannes Fürnkranz

Johannes Fürnkranz's AcademicInfluence.com Rankings

Johannes Fürnkranz

Computer Science

#5874

World Rank

#6198

Historical Rank

Database

#2998

World Rank

#3126

Historical Rank

computer-science Degrees

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Computer Science

Johannes Fürnkranz's Degrees

PhD Computer Science Technische Universität Darmstadt
Masters Computer Science Technische Universität Darmstadt
Bachelors Computer Science Technische Universität Darmstadt

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Johannes Fürnkranz's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Multilabel classification via calibrated label ranking (2008) (800)
Separate-and-Conquer Rule Learning (1999) (565)
Label ranking by learning pairwise preferences (2008) (538)
Round Robin Classification (2002) (490)
Incremental Reduced Error Pruning (1994) (444)
Large-Scale Multi-label Text Classification - Revisiting Neural Networks (2013) (319)
Foundations of Rule Learning (2012) (305)
Preference Learning (2005) (279)
ROC ‘n’ Rule Learning—Towards a Better Understanding of Covering Algorithms (2005) (259)
A Study Using $n$-gram Features for Text Categorization (1998) (246)
Pairwise Preference Learning and Ranking (2003) (236)
Unsupervised generation of data mining features from linked open data (2012) (193)
A Survey of Preference-Based Reinforcement Learning Methods (2017) (182)
Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings (2006) (179)
Decision Tree (2010) (170)
Exploiting Structural Information for Text Classification on the WWW (1999) (166)
Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain (2008) (157)
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification (2017) (139)
An Evaluation of Grading Classifiers (2001) (136)
Pruning Algorithms for Rule Learning (1997) (128)
A Unified Model for Multilabel Classification and Ranking (2006) (125)
An Analysis of Rule Evaluation Metrics (2003) (116)
Preference Learning: An Introduction (2010) (115)
Efficient Pairwise Classification (2007) (109)
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm (2012) (107)
From Local Patterns to Global Models: The LeGo Approach to Data Mining (2008) (102)
Preference Learning and Ranking by Pairwise Comparison (2010) (90)
An Evaluation of Landmarking Variants (2001) (88)
Efficient voting prediction for pairwise multilabel classification (2010) (80)
Binary Decomposition Methods for Multipartite Ranking (2009) (79)
On the quest for optimal rule learning heuristics (2010) (77)
Machine learning in games: a survey (2001) (75)
An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain (2007) (74)
Mean Absolute Error (2010) (74)
Model-Free Preference-Based Reinforcement Learning (2016) (72)
Round Robin Rule Learning (2001) (71)
Machine Learning in Computer Chess: The Next Generation (1996) (64)
Hyperlink ensembles: a case study in hypertext classification (2002) (63)
Integrative Windowing (1998) (61)
All-in Text: Learning Document, Label, and Word Representations Jointly (2016) (56)
Machine learning and games (2006) (54)
Pairwise Classification as an Ensemble Technique (2002) (53)
A Brief Overview of Rule Learning (2015) (52)
On cognitive preferences and the plausibility of rule-based models (2018) (51)
FOSSIL: A Robust Relational Learner (1994) (49)
Multi-Label Classification with Label Constraints (2008) (48)
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models (2018) (46)
Machines that learn to play games (2001) (44)
Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning (2011) (42)
Round robin ensembles (2003) (41)
Time-to-lane-change prediction with deep learning (2017) (40)
Pairwise learning of multilabel classifications with perceptrons (2008) (39)
Web Mining (2005) (37)
Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach (2000) (36)
Using semantic similarity for multi-label zero-shot classification of text documents (2016) (35)
Comparison of Ranking Procedures in Pairwise Preference Learning (2004) (35)
On Pairwise Naive Bayes Classifiers (2007) (34)
Combining Pairwise Classifiers with Stacking (2003) (32)
On predictive accuracy and risk minimization in pairwise label ranking (2010) (32)
Rank Correlation (2010) (31)
Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web (2002) (27)
Detecting Temporal Change in Event Sequences: An Application to Demographic Data (2001) (27)
The cultural evolution of age-at-marriage norms (2002) (26)
Heuristic Rule-Based Regression via Dynamic Reduction to Classification (2011) (25)
Knowledge Discovery in International Conflict Databases (1997) (24)
Ranking by pairwise comparison a note on risk minimization (2004) (24)
Efficient prediction algorithms for binary decomposition techniques (2011) (24)
A review and comparison of strategies for handling missing values in separate-and-conquer rule learning (2011) (23)
Market Basket Analysis (2010) (21)
Mixture Modeling (2019) (21)
Batchwise Patching of Classifiers (2018) (21)
Link-Local Features for Hypertext Classification (2005) (20)
Preference-Based Reinforcement Learning: A Preliminary Survey (2013) (20)
Refinement and selection heuristics in subgroup discovery and classification rule learning (2017) (20)
From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms (2004) (20)
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning (2008) (20)
Learning Label Preferences: Ranking Error Versus Position Error (2005) (20)
Learning Gradient Boosted Multi-label Classification Rules (2020) (19)
Informed Hybrid Game Tree Search for General Video Game Playing (2017) (18)
On Learning From Game Annotations (2015) (18)
Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms (2010) (18)
Rule Learning in a Nutshell (2012) (18)
Graded Multilabel Classification by Pairwise Comparisons (2014) (18)
Which Scores to Predict in Sentence Regression for Text Summarization? (2018) (18)
Distance Measures (2010) (17)
Top-Down Pruning in Relational Learning (1994) (17)
Shorter Rules Are Better, Aren't They? (2016) (17)
Dimensionality Reduction in ILP: A Call to Arms (1997) (16)
Guest Editorial: Global modeling using local patterns (2010) (16)
On the Use of Fast Subsampling Estimates for Algorithm Recommendation (2002) (16)
Distance Functions (2010) (16)
An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules (2009) (15)
A Comparison of Techniques for Selecting and Combining Class Association Rules (2008) (15)
Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning (2014) (15)
An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics (2008) (15)
Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization (2016) (15)
Learning the Piece Values for Three Chess Variants (2008) (15)
Recent Advances in Machine Learning and Game Playing (2007) (15)
An Analysis of Stopping and Filtering Criteria for Rule Learning (2004) (15)
On Minimizing the Position Error in Label Ranking (2007) (15)
Plan Recognition (2010) (14)
Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning (2015) (14)
On Cognitive Preferences and the Interpretability of Rule-based Models (2018) (14)
Separate-and-conquer Regression (2010) (14)
Determining Factors for Slum Growth with Predictive Data Mining Methods (2018) (14)
Using Links for Classifying Web-Pages (1998) (14)
Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier (2011) (13)
Markov Random Field (2010) (13)
Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases (1996) (13)
On Meta-Learning Rule Learning Heuristics (2007) (13)
Efficient implementation of class-based decomposition schemes for Naïve Bayes (2014) (13)
Searching for Patterns in Political Event Sequences: Experiments with the Keds Database (2000) (13)
EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning (2013) (13)
Proceedings of the 17th European conference on Machine Learning (2006) (12)
Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns (2012) (12)
Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel (2010) (12)
A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning (2002) (12)
On the Combination of Two Decompositive Multi-Label Classification Methods (2009) (11)
Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction (2017) (11)
Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization (2016) (11)
Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification (2009) (11)
Learning Context-dependent Label Permutations for Multi-label Classification (2019) (11)
Process-Based Modeling (2010) (10)
Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data (2019) (10)
An Analysis of Rule Learning Heuristics (2003) (10)
More Efficient Windowing (1997) (10)
Noise-Tolerant Windowing (1997) (10)
Dual Control (2010) (10)
Learning Interpretable Rules for Multi-label Classification (2018) (10)
Mean Squared Error (2010) (9)
A Moderately Successful Attempt to Train Chess Evaluation Functions of Different Strengths (2010) (9)
Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype (2016) (9)
Multi-objective Optimisation-Based Feature Selection for Multi-label Classification (2017) (9)
Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings (2006) (9)
Radial Basis Function Neural Networks (2010) (9)
On Aggregation in Ensembles of Multilabel Classifiers (2020) (8)
Editorial: Preference learning and ranking (2013) (8)
The SeCo-framework for rule learning (2010) (8)
A Policy Iteration Algorithm for Learning from Preference-Based Feedback (2013) (7)
Pruning Methods for Rule Learning Algorithms (1994) (7)
On Trading Off Consistency and Coverage in Inductive Rule Learning (2006) (7)
Machine Learning and Game Playing (2010) (7)
What's Important in a Text? An Extensive Evaluation of Linguistic Annotations for Summarization (2018) (7)
Using Past Maneuver Executions for Personalization of a Driver Model (2018) (7)
MACHINE LEARNING AND CASE-BASED REASONING: THEIR POTENTIAL ROLE IN PREVENTING THE OUTBREAK OF WARS OR IN ENDING THEM (1997) (7)
User profiling for the melvil knowledge retrieval system (2002) (7)
Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing (1999) (7)
Driver Information Embedding with Siamese LSTM networks (2019) (7)
Discriminative Learning (2010) (7)
A Tight Integration of Pruning and Learning (Extended Abstract) (1995) (6)
First Steps Towards Learning from Game Annotations (2012) (6)
On exploiting hierarchical label structure with pairwise classifiers (2011) (6)
Preference Learning (Dagstuhl Seminar 14101) (2014) (6)
A Hypothesis on the Divergence of AI Research (1998) (6)
Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules (2018) (6)
Modeling Rule Precision (2004) (6)
Advances in Machine Learning for the Behavioral Sciences (2019) (6)
Exploiting Code Redundancies in ECOC (2010) (5)
A Comparison of Strategies for Handling Missing Values in Rule Learning (2009) (5)
Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome (1994) (5)
Decision Rule (2020) (5)
Machine Learning and Data Mining (2012) (5)
Advances in Efficient Pairwise Multilabel Classification (2008) (5)
Random Subspace Method (2010) (5)
A Study of Probability Estimation Techniques for Rule Learning (2009) (5)
Efficient Pruning Methods for Relational Learning (1994) (5)
Permutation Learning via Lehmer Codes (2020) (5)
Learning to Use Operational Advice (2000) (5)
A Tight Integration of Pruning and Learning (1995) (5)
From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop (2008) (5)
A Comparison of Pruning Methods for Relational Concept Learning (1994) (5)
Knowledge Discovery in Chess Databases: A Research Proposal (1997) (5)
The Potential Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods with the KOSIMO Database of Conflicts (1994) (5)
Deep Ordinal Reinforcement Learning (2019) (5)
Rule Evaluation Measures (2012) (5)
An Empirical Investigation Into Deep and Shallow Rule Learning (2021) (4)
Relationship Extraction (2010) (4)
Rule-Based Methods (2013) (4)
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy (2019) (4)
An Empirical Quest for Optimal Rule Learning Heuristics (2008) (4)
Interactive Data Analytics for the Humanities (2017) (4)
Decision Stump (2010) (4)
On cognitive preferences and the plausibility of rule-based models (2019) (4)
On Effort in AI Research: A Description Along Two Dimensions (1997) (4)
The Need for Interpretability Biases (2018) (4)
Learning from Label Preferences (2011) (4)
What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation (2016) (4)
Ratio Scale (2020) (4)
Efficient Pairwise Classification and Ranking (2007) (3)
Pruning of Rules and Rule Sets (2012) (3)
Proceedings, Twenty-Seventh International Conference on Machine Learning (2010) (3)
Learning of Piece Values for Chess Variants (2008) (3)
Learning Playing Strategies from Chess Endgame Databases: An ILP Approach (1997) (3)
Decision Lists and Decision Trees (2010) (3)
Rule-Based Multi-label Classification: Challenges and Opportunities (2020) (3)
Towards Preference-Based Reinforcement Learning (2012) (3)
Preference Learning and Ranking (2016) (3)
Preference-Based Monte Carlo Tree Search (2018) (3)
Mixture Distribution (2010) (3)
Learning Structured Declarative Rule Sets - A Challenge for Deep Discrete Learning (2020) (3)
Probability Estimation and Aggregation for Rule Learning (2010) (3)
Exploiting Maneuver Dependency for Personalization of a Driver Model (2018) (3)
Knowledge Discovery in Scientific Literature (2014) (3)
Machines That Learn to Play Games: Volume 8 in the Advances in Computation: Theory and Practice (2001) (3)
A Brief Introduction to Knowledge Discovery in Databases (1995) (3)
Special Issue on Machine Learning and Games (2006) (2)
Meta-Learning a Rule Learning Heuristic (2007) (2)
The Role of Qualitative Knowledge in Machine Learning (1993) (2)
Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning with Generalized Feedback: Beyond Numeric Rewards (2013) (2)
Inductive Logic Programming (A Short Introduction and a Thesis Abstract) (1994) (2)
Principles of Data Mining and Knowledge Discovery (1997) (2)
Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach (2008) (2)
Regularization Networks (2010) (2)
Beta Distribution Drift Detection for Adaptive Classifiers (2018) (2)
Mean Error (2010) (2)
Improving Outbreak Detection with Stacking of Statistical Surveillance Methods (2019) (2)
A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance (2021) (2)
Decision Trees For Regression (2010) (2)
Preference Learning: A Tutorial Introduction (2010) (2)
Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts (2015) (2)
Patching Deep Neural Networks for Nonstationary Environments (2019) (2)
KI 2017: Advances in Artificial Intelligence (2017) (2)
Rule Learning (2010) (2)
Ordinal Monte Carlo Tree Search (2019) (2)
Beyond Concept Learning (2012) (2)
Supervised Descriptive Rule Learning (2012) (2)
Modeling International Negotiation Statistical and Machine Learning Approaches (2006) (2)
Positive Semidefinite (2010) (2)
Gradient-based Label Binning in Multi-label Classification (2021) (2)
Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation (2019) (2)
Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression (2017) (2)
Online Enhancement of existing Nash Equilibrium Poker Agents (2016) (2)
Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction (2012) (2)
An Empirical Comparison of Techniques for Selecting and Combining Local Patterns into a Global Model (2008) (2)
An Investigation into Mini-Batch Rule Learning (2021) (2)
Rotation Forests (2010) (2)
Improving the Fusion of Outbreak Detection Methods with Supervised Learning (2019) (1)
Beyond DNF: First Steps towards Deep Rule Learning (2021) (1)
Revisiting Non-Specific Syndromic Surveillance (2021) (1)
Learning Context-DependentLabel Permutations for Multi-Label Classification (2019) (1)
Passive Learning (2010) (1)
Graded multilabel classification by pairwise comparison (2013) (1)
Preference Learning: Problems and Applications in Ai Preference Learning: Problems and Applications in Ai (pl-12) Contents a Preliminary Study on a Recommender System for the Million Songs Dataset Using and Learning Gai-decompositions for Representing Ordinal Rankings Alleviating Cold-user Start Pro (2012) (1)
Random Decision Forests (2010) (1)
Leveraging Reproduction-Error Representations for Multi-Instance Classification (2018) (1)
Dynamic Decision Networks (2010) (1)
Special Issue on First-Order Knowledge Discovery in Databases (1998) (1)
Proceedings of the ECML/PKDD-04 Workshop on Advances in Inductive Rule Learning (2004) (1)
Efficient learning of large sets of locally optimal classification rules (2023) (1)
LEARNING TO RECOGNIZE MISSING E-MAIL ATTACHMENTS (2010) (1)
ROC Curve (2010) (1)
On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics (2019) (1)
Positive Definite (2010) (1)
Elliptical Ordinal Embedding (2021) (1)
Guest Editorial: Machine Learning and Games (2006) (1)
Evaluation of different Regression Learners under Asymmetric Loss for Predictive Maintenance (2016) (1)
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking (2021) (1)
Learning from Trajectory-Based Action Preferences (2013) (1)
Dimensionality Reduction on Text via Feature Selection (2010) (1)
Plans as a Means for Guiding a Reinforcement Learner (2008) (1)
Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop (2003) (1)
Resubstitution Estimate (2010) (1)
Classification Rule (2017) (1)
Markov Network (2010) (1)
Decision Epoch (2010) (1)
Vertrauenswürdiges, transparentes und robustesMaschinelles Lernen (2020) (1)
Predicate Invention (2010) (1)
Learning to Make Good Use of Operational Advice (1999) (1)
Receiver Operating Characteristic Analysis (2010) (1)
A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems (2021) (1)
Informed Hybrid Game Tree Search (2016) (1)
Proceedings of the ECML/PKDD-08 Workshop on Preference Learning (2008) (1)
Decision Threshold (2010) (1)
Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases (2006) (1)
Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants (2008) (1)
PAC Identification (2010) (1)
Conformal Rule-Based Multi-label Classification (2020) (1)
A flexible class of dependence-aware multi-label loss functions (2020) (1)
Exploiting Code-Redundancies in ECOC for Reducing its Training Complexity using Incremental and (2010) (1)
Representation Language (2010) (1)
Comparing Boosting and Bagging for Decision Trees of Rankings (2021) (1)
Learning Rule Sets (2012) (1)
Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders (2018) (1)
Preference Learning from Annotated Game Databases (2014) (1)
Separate-and-conquer Regression Technical Report TUD – KE – 2010 – 01 (2010) (1)
Basic Instrument for Experimental Probes in Machine Learning (2012) (1)
Programming from Traces (2010) (0)
Sentiment Classification of Chess Annotations (2019) (0)
Relational Value Iteration (2010) (0)
Deductive Learning (2010) (0)
Maxent Models (2010) (0)
On the Importance of a Hierarchy for Learning Continuous Vector Representations of a Label Space (2014) (0)
Formale Fragen zu can. 1739 (2014) (0)
Tabellarische Übersicht über das Verwaltungsbeschwerdeverfahren nach dem CIC/1983 (2014) (0)
Personalized E-Learning Systems (2020) (0)
Must-Link Constraint (2010) (0)
Duplicate Detection (2010) (0)
Induktives Lernen durch Generieren von Decision Trees (1991) (0)
Margin Driven Separate and Conquer by Assymmetric Loss Functions Technical Report TUD – KE – 2011 – 01 (2011) (0)
Most Specific Hypothesis (2010) (0)
Discrete Attribute (2010) (0)
Towards Deep and Interpretable Rule Learning (invited paper) (2022) (0)
Report on the Machine-Learning in Game-Playing Workshop (1999) (0)
Production Rules (2014) (0)
Personalized Driving Assistance to Predict Lane Change Manoeuvres (2016) (0)
An Empirical Comparison of HillClimbing and Exhaustive Search in Inductive Rule Learning (2008) (0)
Personalized Transaction Kernels for Recommendation Using MCTS (2019) (0)
Real-Time Dynamic Programming (2010) (0)
Editorial (2015) (0)
Structuring Rule Sets Using Binary Decision Diagrams (2021) (0)
Decision List (2010) (0)
The Potential Contribution of AI to the Avoidance of Crises and Wars: Bibliography (1994) (0)
Pruning Set (2010) (0)
Bericht über {The 11th International Conference on Machine Learning (ML-94)} (1994) (0)
Event-based Clustering for Reducing Labeling Costs of Incident-Related Microposts (2015) (0)
Random Subspaces (2010) (0)
Exegetische Analyse von can. 1739 (2014) (0)
The S E C O-framework for rule learning (2010) (0)
Label Ranking through Multi-Label Classification Label (2018) (0)
Global Optimization using Monte Carlo Tree Search in discrete State Lattices (2017) (0)
McDiarmid's Inequality (2010) (0)
PLAY: A Profiled Linear Weighting Scheme for Understanding the Influence of Input Variables on the Output of a Deep Artificial Neural Network (2020) (0)
Prot. N. 34723/03 CA – amotionis parochi: Lateinischer Text des Endurteils des SSAT und deutsche Übersetzung (2014) (0)
Program Synthesis From Examples (2010) (0)
Randomized Decision Rule (2010) (0)
Summary of the Workshop on {ILP} for {KDD} (1996) (0)
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability (2022) (0)
The Potential Contribution of AI to the Avoidance of Crises and Wars: International Conflict Databases and Machine Learning (1994) (0)
Comparing Boosting and Bagging for Decision Trees of Rankings (2021) (0)
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess (2022) (0)
ROC Convex Hull (2010) (0)
Avoiding Noise Fitting in a sc Foil-like Learning Algorithm (1993) (0)
Reinforcement Learning in Structured Domains (2010) (0)
Erratum to: Predicting unseen labels using label hierarchies in large-scale multi-label learning (2015) (0)
Class Binarization (2017) (0)
Allgemeine Bemerkungen zur Kirchlichen Verwaltung (2014) (0)
Positive Predictive Value (2010) (0)
PAC-MDP Learning (2010) (0)
Markov Net (2010) (0)
Bericht über {The 13th International Conference on Artificial Intelligence (IJCAI-93)} (1993) (0)
Guest Editorial: First-Order Knowledge Discovery in Databases (1998) (0)
On the Incremental Construction of Deep Rule Theories (2022) (0)
Sum-Product Networks for Early Outbreak Detection of Emerging Diseases (2021) (0)
Predicate Calculus (2010) (0)
Editorial: Preference learning and ranking (2013) (0)
Finding dependencies between time series in satellite data (2017) (0)
A comparison of SVM and Rule-and Decision Tree learning (2013) (0)
Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance (2021) (0)
Improving Answer Selection with Analogy-Preserving Sentence Embeddings (2019) (0)
The PRORETA 4 City Assistant System (2019) (0)
On Position Error and Label Ranking through Iterated Choice (2005) (0)
Incremental Update of Locally Optimal Classification Rules (2022) (0)
Acknowledgment to reviewers (2004) (0)
Report on ALIS Ontology (2008) (0)
A flexible class of dependence-aware multi-label loss functions (2022) (0)
Some Chess-Specific Improvements for Perturbation-Based Saliency Maps (2021) (0)
Efficient Pruning Methods for Relational Learning (Extended Thesis Abstract) (1995) (0)
Rule Set (2017) (0)
Divide-and-Conquer Learning (2010) (0)
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm (2012) (0)
Recurrent Associative Memory (2010) (0)
Multi-Armed Bandit (2010) (0)
Model Space (2010) (0)
Most General Hypothesis (2010) (0)
Investigation of rating systems in competitive eSports (2018) (0)
Recursive Partitioning (2010) (0)
Special Issue on Discovery Science (2016) (0)
Distance Metrics (2010) (0)
Relational Regression Tree (2010) (0)
Combining Decision Tree Predictions under Consideration of Uncertainty (2019) (0)
A Linear-Chain Conditional Random Field Approach to the Guitar Fingering Problem (2016) (0)
Covering Algorithm (2017) (0)
On Table Extraction from Text Sources with Markups (2009) (0)
Efficient implementation of class-based decomposition schemes for Naïve Bayes (2014) (0)
On Learning Vector Representations in Hierarchical Label Spaces (2014) (0)
Die Verwaltungsbeschwerde in der historischen Entwicklung und im CIC/1983 (2014) (0)
Reference Reconciliation (2009) (0)
Piecewise Constant Models (2010) (0)
Driving Style Recognition : Literature Review and Application of Machine Learning (2017) (0)
Decision Stump (2017) (0)
Adaptive Support of Knowledge Work by Analysis of User Objectives (2008) (0)
Dependency Directed Backtracking (2010) (0)
Dynamic Programming For Relational Domains (2010) (0)
Discovery science : 16th international conference, DS 2013, Singapore, October 6-9, 2013 : proceedings (2013) (0)
Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches (2019) (0)
Distribution-Free Learning (2010) (0)
News (2011) (0)
On Solving Pentago Betrachtung Der Lösbarkeit Des Spiels Pentago Bachelor-thesis Von Niklas Büscher Aus Münster Mai 2011 on Solving Pentago Betrachtung Der Lösbarkeit Des Spiels Pentago Vorgelegte Bachelor-thesis Von Niklas Büscher Aus Münster Erklärung Zur Bachelor-thesis (2011) (0)
Piecewise Linear Models (2010) (0)
Adaptive Maneuver Assistance at Urban Intersections using Driver Behavior Modeling (2019) (0)
Morphosyntactic Disambiguation (2010) (0)
Postsynaptic Neuron (2010) (0)
Missing Values (2010) (0)
Reward Selection (2010) (0)
Formal Framework for Rule Analysis (2012) (0)
Learning Single Rules (2012) (0)
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) (2006) (0)
Markovian Decision Rule (2010) (0)
Eine Grafische Benutzeroberfläche für ein Poker-Spiel (2011) (0)
Lernen Abalone zu Spielen Bachelorarbeit (2010) (0)
Die Redaktionsgeschichte von can. 1739 (2014) (0)
Modularity Detection (2010) (0)
Margin Driven Separate and Conquer by Working Set Expansion (2009) (0)
GausSetExpander: A Simple Approach for Entity Set Expansion (2022) (0)
Multistrategy Ensemble Learning (2010) (0)
Learning Ordinal Embedding from Sets (2021) (0)
Mean Absolute Deviation (2010) (0)
Tree-Based Dynamic Classifier Chains (2021) (0)
Proceedings of the ECAI-12 Workshop on Preference Learning: Problems and Applications in AI (PL-12) (2012) (0)
Exploiting Maneuver Dependency for Personalization of Driver Assistance Systems (2018) (0)
Monte Carlo Chess Erklärung Zur Bachelor-thesis (2012) (0)
Effizienz der Verwaltung und Rechtsschutz im Verfahren: Can. 1739 in der Dynamik der hierarchischen Beschwerde (2014) (0)
Efficient prediction algorithms for binary decomposition techniques (2011) (0)
KnowledgeDiscovery in ChessDatabases : A Research Proposal (2002) (0)
Proceedings of the 16th International Conference on Discovery Science (DS-13) (2013) (0)
Bericht über ILP-98, ICML-98 und AAAI-98 (1998) (0)
Inductive Rule Learning for Data and Web Mining (2001) (0)
Relational Dynamic Programming (2010) (0)
Data Mining On Text (2010) (0)
Parallel Corpus (2010) (0)
Die Entscheidung des hierarchischen Oberen nach can. 1739 und die rechtliche Stellung Der Parteien (2014) (0)
Relational Data Mining (2010) (0)
Die Entscheidung des hierarchischen Oberen nach can. 1739 und das Verhältnis von Untergeordnetem und hierarchischem Oberen (2014) (0)
Application of Machine Learning Methods to the KOSIMO Database (1993) (0)
Die entscheidungsfindung nach can. 1729: einige prozessrechtliche anmerkungen (2016) (0)
Explanation-Based Learning in der Domäne Schach (1990) (0)
Most Similar Point (2010) (0)
Bericht über IJCAI-97 und AAAI-97 (1997) (0)
Synoptische Darstellung der Redaktionsgeschichte von can. 1739 (2014) (0)
Workshop Report: Machine Learning in Game Playing (1999) (0)
Multidimensional Ordered Mappings for Empirical Machine Learning Research (2012) (0)
Mistake-Bounded Learning (2010) (0)

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What Schools Are Affiliated With Johannes Fürnkranz?

Johannes Fürnkranz is affiliated with the following schools:

Technische Universität Darmstadt

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