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Tomás Horváth
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Publications
- 2024
- [j22]Rafael Gomes Mantovani, Tomás Horváth, André L. D. Rossi, Ricardo Cerri, Sylvio Barbon Junior, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Min. Knowl. Discov. 38(3): 1364-1416 (2024) - [j21]Zakarya Farou, Yizhi Wang, Tomás Horváth:
Cluster-based oversampling with area extraction from representative points for class imbalance learning. Intell. Syst. Appl. 22: 200357 (2024) - 2023
- [j20]Tomás Horváth, Rafael G. Mantovani, André C. P. L. F. de Carvalho:
Hyper-parameter initialization of classification algorithms using dynamic time warping: A perspective on PCA meta-features. Appl. Soft Comput. 134: 109969 (2023) - [j19]Tsegaye Misikir Tashu, Marc Lenz, Tomás Horváth:
NCC: Neural concept compression for multilingual document recommendation. Appl. Soft Comput. 142: 110348 (2023) - [j18]Dániel Tamás Várkonyi, José Luis Seixas Junior, Tomás Horváth:
Dynamic noise filtering for multi-class classification of beehive audio data. Expert Syst. Appl. 213(Part): 118850 (2023) - [c86]Zakarya Farou, Mohamed Aharrat, Tomás Horváth:
A Comparative Study of Assessment Metrics for Imbalanced Learning. ADBIS (Short Papers) 2023: 119-129 - [c84]L'ubomír Antoni, Peter Elias, Tomás Horváth, Stanislav Krajci, Ondrej Krídlo, Csaba Török:
Squared Symmetric Formal Contexts and Their Connections with Correlation Matrices. ICCS 2023: 19-27 - 2022
- [c80]Wadie Skaf, Tomás Horváth:
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. ADBIS (Short Papers) 2022: 178-187 - [c79]Tsegaye Misikir Tashu, Tomás Horváth:
Synonym-Based Essay Generation and Augmentation for Robust Automatic Essay Scoring. IDEAL 2022: 12-21 - [c78]Zakarya Farou, Liudmila Kopeikina, Tomás Horváth:
Solving Multi-class Imbalance Problems Using Improved Tabular GANs. IDEAL 2022: 527-539 - [c77]Dániel Tamás Várkonyi, Márta Alexy, Tomás Horváth:
Beyond Sensor Data Analysis: Unexpected Challenges in a Honeybee Monitoring Project. ITAT 2022: 61-67 - [i9]Tsegaye Misikir Tashu, Chandresh Kumar Maurya, Tomás Horváth:
Deep Learning Architecture for Automatic Essay Scoring. CoRR abs/2206.08232 (2022) - [i8]Tsegaye Misikir Tashu, Sara Fattouh, Péter Kiss, Tomás Horváth:
Multimodal E-Commerce Product Classification Using Hierarchical Fusion. CoRR abs/2207.03305 (2022) - [i7]Sofiane Ouaari, Tsegaye Misikir Tashu, Tomás Horváth:
Multimodal Feature Extraction for Memes Sentiment Classification. CoRR abs/2207.03317 (2022) - [i5]Wadie Skaf, Tomás Horváth:
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series. CoRR abs/2208.14337 (2022) - [i4]Ermiyas Birihanu, Jiyan Mahmud, Péter Kiss, Adolf Kamuzora, Wadie Skaf, Tomás Horváth, Tamás Jursonovics, Peter Pogrzeba, Imre Lendák:
Client Error Clustering Approaches in Content Delivery Networks (CDN). CoRR abs/2210.05314 (2022) - [i3]Adolf Kamuzora, Wadie Skaf, Ermiyas Birihanu, Jiyan Mahmud, Péter Kiss, Tamás Jursonovics, Peter Pogrzeba, Imre Lendák, Tomás Horváth:
Matrix Factorization for Cache Optimization in Content Delivery Networks (CDN). CoRR abs/2211.08273 (2022) - 2021
- [j13]Tsegaye Misikir Tashu, Sakina Hajiyeva, Tomás Horváth:
Multimodal Emotion Recognition from Art Using Sequential Co-Attention. J. Imaging 7(8): 157 (2021) - [c73]Vilmos Tibor Salamon, Tsegaye Misikir Tashu, Tomás Horváth:
Linear Concept Approximation for Multilingual Document Recommendation. IDEAL 2021: 147-156 - [c72]Tomás Horváth, Rafael Gomes Mantovani, André C. P. L. F. de Carvalho:
Time-Series in Hyper-parameter Initialization of Machine Learning Techniques. IDEAL 2021: 246-258 - [c71]Marc Lenz, Tsegaye Misikir Tashu, Tomás Horváth:
Learning Inter-Lingual Document Representations via Concept Compression. IDEAL 2021: 268-276 - [c70]Péter Kiss, Tomás Horváth:
Migrating Models: A Decentralized View on Federated Learning. PKDD/ECML Workshops (1) 2021: 177-191 - 2020
- [c68]Tsegaye Misikir Tashu, Tomás Horváth:
Attention-Based Multi-modal Emotion Recognition from Art. ICPR Workshops (3) 2020: 604-612 - [c67]Andrea Galloni, Imre Lendák, Tomás Horváth:
A Novel Evaluation Metric for Synthetic Data Generation. IDEAL (2) 2020: 25-34 - [c66]Zakarya Farou, Noureddine Mouhoub, Tomás Horváth:
Data Generation Using Gene Expression Generator. IDEAL (2) 2020: 54-65 - [c65]Péter Kiss, Tomás Horváth, Vukasin Felbab:
Stateful Optimization in Federated Learning of Neural Networks. IDEAL (2) 2020: 348-355 - [c64]Ekaterina Zolotareva, Tsegaye Misikir Tashu, Tomás Horváth:
Abstractive Text Summarization using Transfer Learning. ITAT 2020: 75-80 - [c63]Amjad Balawi, Abdullah Al Zoabi, José Luis Seixas Junior, Tomás Horváth:
Classification of a Small Imbalanced Dataset of Vine Leaves Images using Deep Learning Techniques. ITAT 2020: 108-114 - [c62]José Luis Seixas Junior, Tomás Horváth:
KNN Algorithm with DTW Distance for Signature Classification of Wine Leaves. ITAT 2020: 130-136 - [c61]Gábor Szegedi, Diána Bajdikné Veres, Imre Lendák, Tomás Horváth:
Context-based Information Classification on Hungarian Invoices. ITAT 2020: 147-151 - [c59]Tsegaye Misikir Tashu, Tomás Horváth:
SmartScore-Short Answer Scoring Made Easy Using Sem-LSH. ICSC 2020: 145-149 - [i2]Chandresh Kumar Maurya, Neelamadhav Gantayat, Sampath Dechu, Tomás Horváth:
Online Similarity Learning with Feedback for Invoice Line Item Matching. CoRR abs/2001.00288 (2020) - 2019
- [j8]Ladislav Peska, Tsegaye Misikir Tashu, Tomás Horváth:
Swarm intelligence techniques in recommender systems - A review of recent research. Swarm Evol. Comput. 48: 201-219 (2019) - [c54]Krisztián Búza, Tomás Horváth:
Factorization Machines for Blog Feedback Prediction. CORES 2019: 79-85 - [c52]Tsegaye Misikir Tashu, Tomás Horváth:
Semantic-Based Feedback Recommendation for Automatic Essay Evaluation. IntelliSys (2) 2019: 334-346 - [c51]Imre Lendák, Tomás Horváth:
Efficient Load Profiling and Forecasting in Large Electric Power Systems. ITAT 2019: 36-43 - [c50]Vukasin Felbab, Péter Kiss, Tomás Horváth:
Optimization in Federated Learning. ITAT 2019: 58-65 - [c49]Gábor Szegedi, Péter Kiss, Tomás Horváth:
Evolutionary Federated Learning on EEG-data. ITAT 2019: 71-78 - [c48]Tsegaye Misikir Tashu, Julius P. Esclamado, Tomás Horváth:
Intelligent On-line Exam Management and Evaluation System. ITS 2019: 105-111 - [c47]Tsegaye Misikir Tashu, Dávid Szabó, Tomás Horváth:
Reducing Annotation Effort in Automatic Essay Evaluation Using Locality Sensitive Hashing. ITS 2019: 186-192 - 2018
- [c38]Tsegaye Misikir Tashu, Tomás Horváth:
Pair-Wise: Automatic Essay Evaluation using Word Mover's Distance. CSEDU (1) 2018: 59-66 - [c37]Tsegaye Misikir Tashu, Tomás Horváth:
A Layered Approach to Automatic Essay Evaluation Using Word-Embedding. CSEDU (Selected Papers) 2018: 77-94 - [c36]Andrea Galloni, Balázs Horváth, Tomás Horváth:
Real-time Monitoring of Hungarian Highway Traffic from Cell Phone Network Data. ITAT 2018: 108-115 - [e3]András Benczúr, Bernhard Thalheim, Tomás Horváth, Silvia Chiusano, Tania Cerquitelli, Csaba István Sidló, Peter Z. Revesz:
New Trends in Databases and Information Systems - ADBIS 2018 Short Papers and Workshops, AI*QA, BIGPMED, CSACDB, M2U, BigDataMAPS, ISTREND, DC, Budapest, Hungary, September, 2-5, 2018, Proceedings. Communications in Computer and Information Science 909, Springer 2018, ISBN 978-3-030-00062-2 [contents] - [e2]András Benczúr, Bernhard Thalheim, Tomás Horváth:
Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Budapest, Hungary, September 2-5, 2018, Proceedings. Lecture Notes in Computer Science 11019, Springer 2018, ISBN 978-3-319-98397-4 [contents] - [i1]Rafael Gomes Mantovani, Tomás Horváth, Ricardo Cerri, Sylvio Barbon Junior, Joaquin Vanschoren, André Carlos Ponce de Leon Ferreira de Carvalho:
An empirical study on hyperparameter tuning of decision trees. CoRR abs/1812.02207 (2018) - 2017
- [j7]Tomás Horváth, André Carlos Ponce de Leon Ferreira de Carvalho:
Evolutionary computing in recommender systems: a review of recent research. Nat. Comput. 16(3): 441-462 (2017) - [c31]Milos Kravcik, Olga C. Santos, Jesus Boticario, Mária Bieliková, Tomás Horváth:
UMAP 2017 PALE Workshop Organizers' Welcome. UMAP (Adjunct Publication) 2017: 271-273 - 2016
- [c30]Rafael Gomes Mantovani, Tomás Horváth, Ricardo Cerri, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Hyper-Parameter Tuning of a Decision Tree Induction Algorithm. BRACIS 2016: 37-42 - [c29]Tomás Horváth, Rafael Gomes Mantovani, André C. P. L. F. de Carvalho:
Effects of Random Sampling on SVM Hyper-parameter Tuning. ISDA 2016: 268-278 - 2014
- [j6]Ruth Janning, André Busche, Tomás Horváth, Lars Schmidt-Thieme:
Buried pipe localization using an iterative geometric clustering on GPR data. Artif. Intell. Rev. 42(3): 403-425 (2014) - [c23]Stefan Pero, Tomás Horváth:
How patterns in source codes of students can help in detection of their programming skills? EDM 2014: 371-372 - [c22]Lenka Pisková, Tomás Horváth:
Computing Concept Lattices from Very Sparse Large-Scale Formal Contexts. ICCS 2014: 245-259 - 2013
- [c21]Lenka Pisková, Tomás Horváth:
Comparing Performance of Formal Concept Analysis and Closed Frequent Itemset Mining Algorithms on Real Data. CLA 2013: 299-304 - [c20]Stefan Pero, Tomás Horváth:
Detection of Inconsistencies in Student Evaluations. CSEDU 2013: 246-249 - [c19]Stefan Pero, Tomás Horváth:
Opinion-Driven Matrix Factorization for Rating Prediction. UMAP 2013: 1-13 - 2012
- [j5]Krisztián Búza, Alexandros Nanopoulos, Tomás Horváth, Lars Schmidt-Thieme:
GRAMOFON: General model-selection framework based on networks. Neurocomputing 75(1): 163-170 (2012) - [c18]Lenka Pisková, Stefan Pero, Tomás Horváth, Stanislav Krajci:
Mining Concepts from Incomplete Datasets Utilizing Matrix Factorization. CLA 2012: 33-44 - [c17]André Busche, Ruth Janning, Tomás Horváth, Lars Schmidt-Thieme:
A Unifying Framework for GPR Image Reconstruction. GfKl 2012: 325-332 - [c16]Ruth Janning, Tomás Horváth, André Busche, Lars Schmidt-Thieme:
GamRec: A Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing. AIAI (1) 2012: 347-356 - [c15]Lucas Drumond, Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Factorization techniques for student performance classification and ranking. UMAP Workshops 2012 - [c14]Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Lars Schmidt-Thieme:
Using factorization machines for student modeling. UMAP Workshops 2012 - 2011
- [c13]Nguyen Thai-Nghe, Lucas Drumond, Tomás Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme:
Matrix and Tensor Factorization for Predicting Student Performance. CSEDU (1) 2011: 69-78 - [c12]Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Factorization Models for Forecasting Student Performance. EDM 2011: 11-20 - [c11]Nguyen Thai-Nghe, Tomás Horváth, Lars Schmidt-Thieme:
Personalized Forecasting Student Performance. ICALT 2011: 412-414 - 2009
- [j3]Peter Gurský, Tomás Horváth, Peter Vojtás, Jozef Jirásek, Stanislav Krajci, Robert Novotny, Jana Pribolová, Veronika Vaneková:
User Preference Web Search -- Experiments with a System Connecting Web and User. Comput. Informatics 28(4): 515-553 (2009) - 2008
- [j2]Peter Gurský, Tomás Horváth, Jozef Jirásek, Robert Novotny, Jana Pribolová, Veronika Vaneková, Peter Vojtás:
Knowledge Processing for Web Search - An Integrated Model and Experiments. Scalable Comput. Pract. Exp. 9(1) (2008) - [c10]Alan Eckhardt, Tomás Horváth, Dusan Maruscák, Robert Novotny, Peter Vojtás:
Uncertainty Issues and Algorithms in Automating Process Connecting Web and User. URSW (LNCS Vol.) 2008: 207-223 - 2007
- [c9]Peter Gurský, Tomás Horváth, Jozef Jirásek, Stanislav Krajci, Robert Novotny, Veronika Vaneková, Peter Vojtás:
Knowledge Processing for Web Search - An Integrated Model. IDC 2007: 96-104 - [c8]Alan Eckhardt, Tomás Horváth, Dusan Maruscák, Robert Novotny, Peter Vojtás:
Uncertainty Issues in Automating Process Connecting Web and User. URSW 2007 - [c7]Alan Eckhardt, Tomás Horváth, Peter Vojtás:
Learning Different User Profile Annotated Rules for Fuzzy Preference Top-k Querying. SUM 2007: 116-130 - [c6]Alan Eckhardt, Tomás Horváth, Peter Vojtás:
PHASES: A User Profile Learning Approach for Web Search. Web Intelligence 2007: 780-783 - 2006
- [c5]Tomás Horváth, Peter Vojtás:
Induction of Fuzzy and Annotated Logic Programs. ILP 2006: 260-274 - [c4]Tomás Horváth, Peter Vojtás:
Ordinal Classification with Monotonicity Constraints. ICDM 2006: 217-225 - [c3]Peter Gurský, Tomás Horváth, Robert Novotny, Veronika Vaneková, Peter Vojtás:
UPRE: User Preference Based Search System. Web Intelligence 2006: 841-844 - 2004
- [j1]Peter Vojtás, Tomás Horváth, Stanislav Krajci, Rastislav Lencses:
An ILP model for a monotone graded classification problem. Kybernetika 40(3): 317-332 (2004) - [c2]Tomás Horváth, Peter Vojtás:
Fuzzy Induction via Generalized Annotated Programs. Fuzzy Days 2004: 419-433 - [c1]Tomás Horváth, Frantisek Sudzina, Peter Vojtás:
Mining Rules from Monotone Classification Measuring Impact of Information Systems on Business Competitiveness. BASYS 2004: 451-458
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last updated on 2024-08-23 19:29 CEST by the dblp team
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