Granitzer, Michael
264  Ergebnisse:
Personensuche X
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1

DriftGAN: Using historical data for Unsupervised Recurring ..:

, In: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing,
 
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2

The First International Workshop on Open Web Search (WOWS):

, In: Lecture Notes in Computer Science; Advances in Information Retrieval,
 
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3

A Longitudinal Study of Content Control Mechanisms:

, In: Companion Proceedings of the ACM on Web Conference 2024,
Dinzinger, Michael ; Granitzer, Michael - p. 1382-1387 , 2024
 
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4

Informed Heterogeneous Attention Networks for Metapath Base..:

, In: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing,
Wendlinger, Lorenz ; Granitzer, Michael - p. 458-465 , 2024
 
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5

Knowledge Distillation with Segment Anything (SAM) Model fo..:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,
Julka, Sahib ; Granitzer, Michael - p. 68-77 , 2024
 
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6

Efficient NAS with FaDE on Hierarchical Spaces:

, In: Lecture Notes in Computer Science; Advances in Intelligent Data Analysis XXII,
 
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7

Deep Active Learning with Concept Drifts for Detection of M..:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,
 
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8

The Open Web Index: Crawling and Indexing the Web for Publi..:

, In: Lecture Notes in Computer Science; Advances in Information Retrieval,
 
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9

GRAN Is Superior to GraphRNN: Node Orderings, Kernel- and G..:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,
 
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10

Impact of Position Bias on Language Models in Token Classif..:

, In: Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing,
 
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11

Neural Network Based Drift Detection:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,
 
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12

Exploring Semantic Similarity Between German Legal Texts an..:

, In: Communications in Computer and Information Science; Knowledge Discovery, Knowledge Engineering and Knowledge Management,
 
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13

Pooling Graph Convolutional Networks for Structural Perform..:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,
 
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