50 results on '"Jefrey Lijffijt"'
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2. ReCon: Reducing Congestion in Job Recommendation using Optimal Transport.
3. Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors.
4. FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources.
5. Adversarial Robustness of Probabilistic Network Embedding for Link Prediction.
6. Explanations for Network Embedding-Based Link Predictions.
7. CSNE: Conditional Signed Network Embedding.
8. Block-Approximated Exponential Random Graphs.
9. FONDUE: Framework for Node Disambiguation Using Network Embeddings.
10. Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?
11. Gibbs Sampling Subjectively Interesting Tiles.
12. Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach.
13. Topologically Regularized Data Embeddings.
14. Contrastive Antichains in Hierarchies.
15. Discovering Interesting Cycles in Directed Graphs.
16. EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
17. Quantifying and Reducing Imbalance in Networks.
18. A Systematic Evaluation of Node Embedding Robustness.
19. Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach.
20. Subjectively Interesting Subgroup Discovery on Real-Valued Targets.
21. Quantifying and Minimizing Risk of Conflict in Social Networks.
22. Conditional t-SNE: More informative t-SNE embeddings.
23. Subjectively Interesting Connecting Trees.
24. Hierarchical Novelty Detection.
25. Conditional Network Embeddings.
26. EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
27. Conditional Network Embeddings.
28. Detecting trends in twitter time series.
29. Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations.
30. Direct Mining of Subjectively Interesting Relational Patterns.
31. Interactive Visual Data Exploration with Subjective Feedback.
32. A Tool for Subjective and Interactive Visual Data Exploration.
33. Covering the Egonet: A Crowdsourcing Approach to Social Circle Discovery on Twitter.
34. Interactively Exploring Supply and Demand in the UK Independent Music Scene.
35. P-N-RMiner: A generic framework for mining interesting structured relational patterns.
36. A Fast and Simple Method for Mining Subsequences with Surprising Event Counts.
37. Informative data projections: a framework and two examples.
38. Size Matters: Finding the Most Informative Set of Window Lengths.
39. Analyzing Word Frequencies in Large Text Corpora Using Inter-arrival Times and Bootstrapping.
40. Visually Controllable Data Mining Methods.
41. Supply and demand of independent UK music artists on the web.
42. Tracking your steps on the track: body sensor recordings of a controlled walking experiment.
43. Benchmarking dynamic time warping for music retrieval.
44. Artificial Intelligence and Machine Learning - 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7-9, 2022, Revised Selected Papers
45. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II
46. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
47. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III
48. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I
49. Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II
50. Artificial Intelligence and Machine Learning - 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19-20, 2020, Revised Selected Papers
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