Sándor Szedmák

Orcid: 0000-0003-1469-2215

According to our database1, Sándor Szedmák authored at least 61 papers between 2004 and 2024.

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Bibliography

2024
Protein function prediction through multi-view multi-label latent tensor reconstruction.
BMC Bioinform., December, 2024

Scalable variable selection for two-view learning tasks with projection operators.
Mach. Learn., June, 2024

2023
Personalized Learning Systems for Computer Science Students: Analyzing and Predicting Learning Behaviors Using Programming Error Data.
Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023

2022
Strain design optimization using reinforcement learning.
PLoS Comput. Biol., 2022

2021
Modeling drug combination effects via latent tensor reconstruction.
Bioinform., 2021

2020
Using Machine Learning for Decreasing State Uncertainty in Planning.
J. Artif. Intell. Res., 2020

A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction.
CoRR, 2020

2018
Integrating multi-purpose natural language understanding, robot's memory, and symbolic planning for task execution in humanoid robots.
Robotics Auton. Syst., 2018

Learning with multiple pairwise kernels for drug bioactivity prediction.
Bioinform., 2018

Liquid-chromatography retention order prediction for metabolite identification.
Bioinform., 2018

2017
Utilising Kronecker Decomposition and Tensor-based Multi-view Learning to predict where people are looking in images.
Neurocomputing, 2017

Decreasing Uncertainty in Planning with State Prediction.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Initial State Prediction in Planning.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Learning undirected graphical models using persistent sequential Monte Carlo.
Mach. Learn., 2016

Hierarchical Haptic Manipulation for Complex Skill Learning.
CoRR, 2016

Robotic playing for hierarchical complex skill learning.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning.
Proceedings of the Discovery Science - 19th International Conference, 2016

Kronecker Decomposition for Image Classification.
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2016

2015
Scalable, accurate image annotation with joint SVMs and output kernels.
Neurocomputing, 2015

Diversity priors for learning early visual features.
Frontiers Comput. Neurosci., 2015

SCurV: A 3D descriptor for object classification.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Using structural bootstrapping for object substitution in robotic executions of human-like manipulation tasks.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Learning to Predict Where People Look with Tensor-Based Multi-view Learning.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Reactive, task-specific object manipulation by metric reinforcement learning.
Proceedings of the International Conference on Advanced Robotics, 2015

Learning missing edges via kernels in partially-known graphs.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

IIS at ImageCLEF 2015: Multi-label Classification Task.
Proceedings of the Working Notes of CLEF 2015, 2015

Can Computer Vision Problems Benefit from Structured Hierarchical Classification?
Proceedings of the Computer Analysis of Images and Patterns, 2015

Multi-label Object Categorization Using Histograms of Global Relations.
Proceedings of the 2015 International Conference on 3D Vision, 2015

2014
Complex affordance learning based on basic affordances.
Proceedings of the 2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014

Knowledge propagation and relation learning for predicting action effects.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

Bootstrapping paired-object affordance learning with learned single-affordance features.
Proceedings of the 4th International Conference on Development and Learning and on Epigenetic Robotics, 2014

Towards Sparsity and Selectivity: Bayesian Learning of Restricted Boltzmann Machine for Early Visual Features.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Joint SVM for Accurate and Fast Image Tagging.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013
Homogeneity analysis for object-action relation reasoning in kitchen scenarios.
Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems, 2013

3D Object Class Geometry Modeling with Spatial Latent Dirichlet Markov Random Fields.
Proceedings of the Pattern Recognition - 35th German Conference, 2013

Efficient, General Point Cloud Registration with Kernel Feature Maps.
Proceedings of the Tenth Conference on Computer and Robot Vision, 2013

A Study of Point Cloud Registration with Probability Product Kernel Functions.
Proceedings of the 2013 International Conference on 3D Vision, 2013

2012
Kernel-Mapping Recommender system algorithms.
Inf. Sci., 2012

2011
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation.
J. Mach. Learn. Res., 2011

Incremental Kernel Mapping Algorithms for Scalable Recommender Systems.
Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011

2010
The application of structured learning in natural language processing.
Mach. Transl., 2010

Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Reaction Kernels - Structured Output Prediction Approaches for Novel Enzyme Function.
Proceedings of the BIOINFORMATICS 2010, 2010

Structured Output Prediction of Novel Enzyme Function with Reaction Kernels.
Proceedings of the Biomedical Engineering Systems and Technologies, 2010

2009
Learning to rank images from eye movements.
Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

Large-margin structural prediction via linear programming.
Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

Large scale maximum margin regression based, structural learning approach to phrase translations.
Proceedings of the Workshop on Statistical Multilingual Analysis for Retrieval and Translation, 2009

Handling phrase reorderings for machine translation.
Proceedings of the ACL 2009, 2009

2007
Synthesis of maximum margin and multiview learning using unlabeled data.
Neurocomputing, 2007

Kernel Regression Based Machine Translation.
Proceedings of the Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, 2007

A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning.
Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006
Kernel-Based Learning of Hierarchical Multilabel Classification Models.
J. Mach. Learn. Res., 2006

A Correlation Approach for Automatic Image Annotation.
Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006

2005
Two view learning: SVM-2K, Theory and Practice.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005


Learning hierarchical multi-category text classification models.
Proceedings of the Machine Learning, 2005

2004
Canonical Correlation Analysis: An Overview with Application to Learning Methods.
Neural Comput., 2004

Saturated systems of homogeneous boxes and the logical analysis of numerical data.
Discret. Appl. Math., 2004

Pareto-optimal patterns in logical analysis of data.
Discret. Appl. Math., 2004

Support Vector Machine to Synthesise Kernels.
Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004


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