Balázs Hidasi

53 Followers

16 SlideShares 0 Clipboards 53 Followers 4 Folgens

16 SlideShares 0 Clipboards 53 Followers 4 Folgens

I'm a machine learning researcher with a wide interest in the field of machine learning and data mining. My current focus topics are deep learning, recommender systems and collaborative filtering; earlier I worked on model based time series classification. Currently I am the Head of Data Mining and Research at Gravity R&D, a Budapest (Hungary) based recommendation service provider company. I lead a small team of data scientists and work on my own recommendation systems related research. I actively publish the results of my research at scientific conferences and journals. I am an active participant in the EU FP7 funded CrowdRec project that aims at developing the new generation of recomm...

recommender systems context-awareness implicit feedback data mining machine learning deep learning factorization context adatbányászat gépi tanulás shifttree tensor factorization matrix factorization idősor osztályozás döntési fa session-based recommendation recurrent neural network negative sampling loss function gated recurrent unit recurrent neural networks neural networks summer school tutorial feature extraction phd thesis startup safary preference modeling scalability continuous context overview crowdrec research kollaboratív szűrés ajánlórendszer kontextus vezéreltség inicializálás tenzor faktorizáció kontextus mátrix faktorizáció item-to-item recommendation itals alternating least squares initialization classification decision tree time series

ShiftTree: model based time series classifier (ECML/PKDD 2011 presentation)

Vor 9 Jahren • 723 Aufrufe

ShiftTree: model alapú idősor-osztályozó (ML@BP előadás, 2012)

Vor 9 Jahren • 353 Aufrufe

ShiftTree: model alapú idősor-osztályozó (VK 2009 előadás)

Vor 9 Jahren • 322 Aufrufe

Initialization of matrix factorization (CaRR 2012 presentation)

Vor 9 Jahren • 733 Aufrufe

iTALS: implicit tensor factorization for context-aware recommendations (ECML/PKDD 2012 presentation)

Vor 9 Jahren • 635 Aufrufe

Context-aware similarities within the factorization framework (CaRR 2013 presentation)

Vor 9 Jahren • 1176 Aufrufe

Az implicit ajánlási probléma és néhány megoldása (BME TMIT szeminárium előadás, 2012)

Vor 9 Jahren • 382 Aufrufe

Utilizing additional information in factorization methods (research overview, April 2014)

Vor 8 Jahren • 625 Aufrufe

Approximate modeling of continuous context in factorization algorithms (CaRR14 presentation)

Vor 8 Jahren • 1363 Aufrufe

Context-aware preference modeling with factorization

Vor 7 Jahren • 1656 Aufrufe

Deep learning: the future of recommendations

Vor 6 Jahren • 15060 Aufrufe

Deep learning to the rescue - solving long standing problems of recommender systems

Vor 6 Jahren • 13548 Aufrufe

Context aware factorization methods for implicit feedback based recommendation problems (HUN)

Vor 6 Jahren • 523 Aufrufe

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations

Vor 6 Jahren • 2263 Aufrufe

Deep Learning in Recommender Systems - RecSys Summer School 2017

Vor 5 Jahren • 11044 Aufrufe

GRU4Rec v2 - Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

Vor 4 Jahren • 3033 Aufrufe

Deep Learning for Recommender Systems RecSys2017 Tutorial

Alexandros Karatzoglou • Vor 5 Jahren

Deep Learning for Recommender Systems - Budapest RecSys Meetup

Alexandros Karatzoglou • Vor 6 Jahren

Aktivität
Info

ShiftTree: model based time series classifier (ECML/PKDD 2011 presentation)

Vor 9 Jahren • 723 Aufrufe

ShiftTree: model alapú idősor-osztályozó (ML@BP előadás, 2012)

Vor 9 Jahren • 353 Aufrufe

ShiftTree: model alapú idősor-osztályozó (VK 2009 előadás)

Vor 9 Jahren • 322 Aufrufe

Initialization of matrix factorization (CaRR 2012 presentation)

Vor 9 Jahren • 733 Aufrufe

iTALS: implicit tensor factorization for context-aware recommendations (ECML/PKDD 2012 presentation)

Vor 9 Jahren • 635 Aufrufe

Context-aware similarities within the factorization framework (CaRR 2013 presentation)

Vor 9 Jahren • 1176 Aufrufe

Az implicit ajánlási probléma és néhány megoldása (BME TMIT szeminárium előadás, 2012)

Vor 9 Jahren • 382 Aufrufe

Utilizing additional information in factorization methods (research overview, April 2014)

Vor 8 Jahren • 625 Aufrufe

Approximate modeling of continuous context in factorization algorithms (CaRR14 presentation)

Vor 8 Jahren • 1363 Aufrufe

Context-aware preference modeling with factorization

Vor 7 Jahren • 1656 Aufrufe

Deep learning: the future of recommendations

Vor 6 Jahren • 15060 Aufrufe

Deep learning to the rescue - solving long standing problems of recommender systems

Vor 6 Jahren • 13548 Aufrufe

Context aware factorization methods for implicit feedback based recommendation problems (HUN)

Vor 6 Jahren • 523 Aufrufe

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations

Vor 6 Jahren • 2263 Aufrufe

Deep Learning in Recommender Systems - RecSys Summer School 2017

Vor 5 Jahren • 11044 Aufrufe

GRU4Rec v2 - Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

Vor 4 Jahren • 3033 Aufrufe

Deep Learning for Recommender Systems RecSys2017 Tutorial

Alexandros Karatzoglou • Vor 5 Jahren

Deep Learning for Recommender Systems - Budapest RecSys Meetup

Alexandros Karatzoglou • Vor 6 Jahren

I'm a machine learning researcher with a wide interest in the field of machine learning and data mining. My current focus topics are deep learning, recommender systems and collaborative filtering; earlier I worked on model based time series classification. Currently I am the Head of Data Mining and Research at Gravity R&D, a Budapest (Hungary) based recommendation service provider company. I lead a small team of data scientists and work on my own recommendation systems related research. I actively publish the results of my research at scientific conferences and journals. I am an active participant in the EU FP7 funded CrowdRec project that aims at developing the new generation of recomm...

recommender systems context-awareness implicit feedback data mining machine learning deep learning factorization context adatbányászat gépi tanulás shifttree tensor factorization matrix factorization idősor osztályozás döntési fa session-based recommendation recurrent neural network negative sampling loss function gated recurrent unit recurrent neural networks neural networks summer school tutorial feature extraction phd thesis startup safary preference modeling scalability continuous context overview crowdrec research kollaboratív szűrés ajánlórendszer kontextus vezéreltség inicializálás tenzor faktorizáció kontextus mátrix faktorizáció item-to-item recommendation itals alternating least squares initialization classification decision tree time series