Szedmak, Sandor

12 publications

MLJ 2024 Scalable Variable Selection for Two-View Learning Tasks with Projection Operators Sándor Szedmák, Riikka Huusari, Tat Hong Duong Le, Juho Rousu

JAIR 2020 Using Machine Learning for Decreasing State Uncertainty in Planning Senka Krivic, Michael Cashmore, Daniele Magazzeni, Sándor Szedmák, Justus H. Piater

IJCAI 2017 Decreasing Uncertainty in Planning with State Prediction Senka Krivic, Michael Cashmore, Daniele Magazzeni, Bram Ridder, Sándor Szedmák, Justus H. Piater

MLJ 2016 Learning Undirected Graphical Models Using Persistent Sequential Monte Carlo Hanchen Xiong, Sándor Szedmák, Justus H. Piater

ACML 2014 Towards Maximum Likelihood: Learning Undirected Graphical Models Using Persistent Sequential Monte Carlo Hanchen Xiong, Sandor Szedmak, Justus Piater

IJCAI 2013 Homogeneity Analysis for Object-Action Relation Reasoning in Kitchen Scenarios Hanchen Xiong, Sándor Szedmák, Justus H. Piater

JMLR 2011 Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation Yizhao Ni, Craig Saunders, Sandor Szedmak, Mahesan Niranjan

ICCVW 2009 Learning to Rank Images from Eye Movements Kitsuchart Pasupa, Craig Saunders, Sándor Szedmák, Arto Klami, Samuel Kaski, Steve R. Gunn

JMLR 2006 Kernel-Based Learning of Hierarchical Multilabel Classification Models Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-Taylor

ICML 2005 Learning Hierarchical Multi-Category Text Classification Models Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor

NeurIPS 2005 Two View Learning: SVM-2K, Theory and Practice Jason Farquhar, David Hardoon, Hongying Meng, John S. Shawe-taylor, Sándor Szedmák

NeCo 2004 Canonical Correlation Analysis: An Overview with Application to Learning Methods David R. Hardoon, Sándor Szedmák, John Shawe-Taylor