Tapani Raiko
Academy Research Fellow at Aalto University School of Business
Schools
- Aalto University School of Business
Links
Biography
Aalto University School of Business
Research on deep learning, which is a novel type of machine learning based on artificial neural networks, applicable to large data analysis tasks such as computer vision or natural language processing.
Peer-reviewed scientific articles
Journal article-refereed, Original researchMeasuring the usefulness of hidden units in Boltzmann machines with mutual information
Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun2015 in NEURAL NETWORKS (PERGAMON-ELSEVIER SCIENCE LTD)ISSN: 0893-6080Two-layer contractive encodings for learning stable nonlinear features
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven2015 in NEURAL NETWORKS (PERGAMON-ELSEVIER SCIENCE LTD)ISSN: 0893-6080Self-organization and missing values in SOM and GTM
Vatanen, T.; Osmala, M.; Raiko, T.; Lagus, K.; Sysi-Aho, M.; Orešič, M.; Honkela, T.; Lähdesmäki, H.2015 in NEUROCOMPUTING (Elsevier Science B.V.)ISSN: 0925-2312Enhanced Gradient for Training Restricted Boltzmann Machines
Cho, K.; Raiko, T.; Ilin, A.2013 in NEURAL COMPUTATION (MIT PRESS)ISSN: 0899-7667Semi-Supervised Anomaly Detection - Towards Model-Independent Searches of New Physics
Kuusela, Mikael; Malmi, Eric; Raiko, Tapani; Vatanen, Tommi2012 in Journal of Physics: Conference Series (IOP Publishing Ltd.)ISSN: 1742-6588Missing-feature reconstruction with a bounded nonlinear state-space model
Remes, Ulpu; Palomäki, Kalle J.; Raiko, Tapani; Honkela, Antti; Kurimo, Mikko2011 in IEEE SIGNAL PROCESSING LETTERS (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC)ISSN: 1070-9908Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Honkela, Antti; Raiko, Tapani; Kuusela, Mikael; Tornio, Matti; Karhunen, Juha2010 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)ISSN: 1532-4435Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2010 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)ISSN: 1532-4435Variational Bayesian learning of nonlinear hidden state-space models for model predictive control
Raiko, Tapani; Tornio, Matti2009 in NEUROCOMPUTING (Elsevier Science B.V.)Building Blocks for Variational Bayesian Learning of Latent Variable Models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2007 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)Logical Hidden Markov Models
Kersting, Kristian; De Raedt, Luc; Raiko, Tapani2006 in JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH (Morgan Kaufmann Publishers, Inc.)ISSN: 1076-9757Book section, Chapters in research booksHow to Pretrain Deep Boltzmann Machines in Two Stages
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2015 ISBN: 978-3-319-09903-3Oscillatory Neural Network for Image Segmentation (Chapter 7) with Biased Competition for Attention
Raiko, Tapani; Valpola, Harri2011 ISBN: 978-1-4614-0163-6ISSN: 0065-2598Conference proceedingsSemi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation
Wang, Huiling ; Raiko, Tapani; Lensu, Lasse; Wang, Tinghuai; Karhunen, Juha2017 in Lecture Notes in Computer Science (SPRINGER)ISBN: 9783319541815ISSN: 0302-9743Ladder Variational Autoencoders
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 in Advances in neural information processing systems (Neural Information Processing Systems Foundation)ISSN: 1049-5258Scalable gradient-based tuning of continuous regularization hyperparameters
Luketina, Jelena; Berglund, Mathias; Greff, Klaus; Raiko, Tapani2016 ISBN: 9781510829008DopeLearning A computational approach to rap lyrics generation
Malmi, Eric; Takala, Pyry; Toivonen, Hannu; Raiko, Tapani; Gionis, Aristides2016 ISBN: 9781450342322Bidirectional recurrent neural networks as generative models
Berglund, Mathias; Raiko, Tapani; Honkala, Mikko; Kärkkäinen, Leo; Vetek, Akos; Karhunen, Juha2015 ISSN: 1049-5258Iterative Neural Autoregressive Distribution Estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua2015 ISSN: 1049-5258Semi-supervised learning with Ladder networks
Rasmus, Antti; Valpola, Harri; Honkala, Mikko; Berglund, Mathias; Raiko, Tapani2015 ISSN: 1049-5258Linear State-Space Model with Time-Varying Dynamics
Luttinen, Jaakko; Raiko, Tapani; Ilin, Alexander2014 ISBN: 978-3-662-44850-2Iterative neural autoregressive distribution estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua2014 Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information
Berglund, Mathias; Raiko, Tapani; Cho, KyungHyun2013 ISBN: 978-3-642-42053-5A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2013 ISBN: 978-3-642-40727-7Gaussian-Bernoulli Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2013 Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation
Keronen, Sami; Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Palomäki, Kalle J.2013 in International Conference on Acoustics Speech and Signal Processing ICASSP (SPRINGER GABLER)ISBN: 978-1-4799-0356-6ISSN: 1520-6149Variational Bayesian PCA versus k-NN on a Very Sparse Reddit Voting Dataset
Klapuri, Jussa; Nieminen, Ilari T.; Raiko, Tapani; Lagus, Krista2013 ISBN: 978-3-642-41397-1Two-Layer Contractive Encodings with Linear Transformation of Perceptrons for Semi-Supervised Learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven2013 ISBN: 978-3-642-42042-9Two-layer contractive encodings with shortcuts for semi-supervised learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven2013 in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (SPRINGER GABLER)ISBN: 9783642420535ISSN: 0302-9743Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities
Vatanen, Tommi; Raiko, Tapani; Valpola, Harri; LeCun, Yann2013 ISBN: 978-3-642-42042-9Controlling Self-Organization and Handling Missing Values in SOM and GTM
Vatanen, Tommi; Nieminen, Ilari T.; Honkela, Timo; Raiko, Tapani; Lagus, Krista2013 ISBN: 978-3-642-35229-4Learning Deep Belief Networks from Non-Stationary Streams
Calandra, R.; Raiko, T.; Pouzols, Montesino2012 ISBN: 978-3-642-33269-2ISSN: 0302-9743Tikhonov-Type Regularization for Restricted Boltzmann Machines
Cho, K.; Ilin, A.; Raiko, T.2012 ISBN: 978-3-642-33268-5ISSN: 0302-9743A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2012 Reinforcement Learning in Real-Time Strategy Games
Raiko, Tapani2012 Towards Generalizing the Success of Monte-Carlo Tree Search beyond the Game of Go
Raiko, Tapani2012 ISBN: 978-1-61499-097-0Deep learning made easier by linear transformations in perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann2012 ISSN: 1532-4435Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts
Raitio, Juha; Raiko, Tapani; Honkela, Timo2012 ISBN: 978-3-642-33265-4ISSN: 0302-9743Semi-Supervised Detection of Collective Anomalies with an Application in High Energy Particle Physics
Vatanen, Tommi; Kuusela, Mikael; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu2012 ISBN: 978-1-4673-1488-6Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines
Cho, KyungHyun; Ilin, Alexander; Raiko, Tapani2011 Gaussian-Bernoulli Deep Boltzmann Machine
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2011 Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2011 Deep Learning Made Easier by Linear Transformations in Perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann2011 Enhanced Gradient for Learning Boltzmann Machines
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Parallel Tempering is Efficient for Learning Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2010 Novelty detection by nonlinear factor analysis for structural health monitoring
Lämsä, Ville; Raiko, Tapani2010 ISBN: 978-1-4244-7875-0ISSN: 1551-2541Document Classification Utilising Ontologies and Relations between Documents
Nyberg, Katariina; Raiko, Tapani; Tiinanen, Teemu; Hyvönen, Eero2010 Oscillatory Neural Network for Image Segmentation with Biased Competition for Attention
Raiko, Tapani; Valpola, Harri2010 Extending Self-Organizing Maps with Uncertainty Information of Probabilistic PCA
Sovilj, Dusan; Raiko, Tapani; Oja, Erkki2010 Binary Principal Component Analysis in the Netflix Collaborative Filtering Task
Kozma, Laszlo; Ilin, Alexander; Raiko, Tapani2009 A Gradient-Based Algorithm Competitive with Variational Bayesian EM for Mixture of Gaussians
Kuusela, Mikael; Raiko, Tapani; Honkela, Antti; Karhunen, Juha2009 Transformations for Variational Factor Analysis to Speed up Learning
Luttinen, Jaakko; Ilin, Alexander; Raiko, Tapani2009 Learning mixture models - courseware for finite mixture distributions of multivariate Bernoulli distributions
Hollmén, Jaakko; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2008 Variational Inference and Learning for Continuous-Time Nonlinear State-Space Models
Honkela, Antti; Harva, Markus; Raiko, Tapani; Karhunen, Juha2008 Macadamia: Master's Programme in Machine Learning and Data Mining
Raiko, Tapani; Puolamäki, Kai; Karhunen, Juha; Hollmén, Jaakko; Honkela, Antti; Kaski, Samuel; Mannila, Heikki; Oja, Erkki; Simula, Olli2008 Principal Component Analysis for Sparse High-Dimensional Data
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2008 Application of UCT Search to the Connection Games of Hex, Y, *Star, and Renkula!
Raiko, Tapani; Peltonen, Jaakko2008 Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2007 State Inference in Variational Bayesian Nonlinear State-Space Models
Raiko, Tapani; Tornio, Matti; Honkela, Antti; Karhunen, Juha2006 ISBN: 3-540-32630-8ISSN: 0302-9743Higher order statistics in play-out analysis
Raiko, Tapani2006 ISBN: 952-5677-00-1ISSN: 1238-4658Variational Bayesian Approach for Nonlinear Identification and Control
Tornio, Matti; Raiko, Tapani2006 Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework
Harva, M.; Raiko, T.; Honkela, A.; Valpola, H.; Karhunen, J.2005 'Say EM' for Selecting Probabilistic Models for Logical Sequences
Kersting, K.; Raiko, T.2005 Learning Nonlinear State-Space Models for Control
Raiko, T.; Tornio, M.2005 Nonlinear Relational Markov Networks with an Application to the Game of Go
Raiko, T.2005 Partially Observed Values
Raiko, Tapani2004 The Go-Playing Program Called Go81
Raiko, Tapani2004 A Structural GEM for Learning Logical Hidden Markov Models
Kersting, K.; Raiko, T.; De Raedt, L.2003 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models
Kersting, K.; Raiko, T.; Kramer, S.; De Raedt, L.2003 Missing Values in Hierarchical Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.; Östman, T.; Karhunen, J.2003 Logical Hidden Markov Models (Extended Abstract)
Kersting, K.; Raiko, Tapani; De Raedt, L.2002 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models (Extended abstract)
Kersting, K.; Raiko, Tapani; Kramer, S.; De Raedt, L.2002 Bayesian Learning of Logical Hidden Markov Models
Raiko, Tapani; Kersting, K.; Karhunen, J.; De Raedt, L.2002 Constructing Graphical Models for Bayesian Ensemble Learning from Simple Building Blocks
Valpola, Harri; Raiko, T.; Karhunen, J.2002 Building Blocks for Hierarchical Latent Variable Models
Valpola, Harri; Raiko, T.; Karhunen, J.2001 Non-refereed scientific articles
Book sectionUnsupervised Deep Learning: A Short Review
Karhunen, J.; Raiko, T.; Cho, K.2015 ISBN: 9780128028063Unrefereed conference proceedingsAdvances in Training Restricted Boltzmann Machines
Cho, K.; Raiko, Tapani; Karhunen, Juha2012 ISBN: 978-3-642-34155-7Scientific books (monographs)
Book (editor)Neurocomputing, Special Issue on Machine Learning for Signal Processing 2010, 80:1-128
Peltonen, Jaakko; Raiko, Tapani; Kaski, Samuel2012 ISSN: 0925-2312AI and Machine Consciousness, Proceedings of the 13th Finnish Artificial Intelligence Conference (STeP 2008)
Raiko, Tapani; Haikonen, Pentti; Väyrynen, Jaakko2008 Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006)
Honkela, Timo; Raiko, Tapani; Kortela, Jukka; Valpola, Harri2006 ISBN: 952-5677-00-1Developments in Artificial Intelligence and the Semantic Web - Proceedings of the 12th Finnish AI Conference STeP 2006.Finland, October 26-27, 2006
Hyvönen, Eero; Kauppinen, Tomi; Kortela, Jukka; Laukkanen, Mikko; Raiko, Tapani; Viljanen, Kim2006 ISBN: 952-5677-02-8Publications intended for professional communities
Article in professional journalJonglöörauksen matematiikka
Raiko, Tapani2013 in Arpakannus (Finnish Artificial Intelligence Society)ISSN: 0783-3121Sudoku ihmisen ja koneen ratkaisemana
Raiko, Tapani2009 in Arpakannus, Magazine of the Finnish Artificial Intelligence Society (Finnish Artificial Intelligence Society)Article in professional conference proceedingsUnderstanding Regularization by Virtual Adversarial Training, Ladder Networks and Others
Abbas, Mudassar; Kivinen, Jyri; Raiko, Tapani2016 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Pekka; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2015 Published development or research reportHow to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.2001 Audiovisual material, ICT software
ICT programs or applicationsBayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.2003
Measuring the usefulness of hidden units in Boltzmann machines with mutual information
Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun
2015 in NEURAL NETWORKS (PERGAMON-ELSEVIER SCIENCE LTD)ISSN: 0893-6080
Two-layer contractive encodings for learning stable nonlinear features
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven
2015 in NEURAL NETWORKS (PERGAMON-ELSEVIER SCIENCE LTD)ISSN: 0893-6080
Self-organization and missing values in SOM and GTM
Vatanen, T.; Osmala, M.; Raiko, T.; Lagus, K.; Sysi-Aho, M.; Orešič, M.; Honkela, T.; Lähdesmäki, H.
2015 in NEUROCOMPUTING (Elsevier Science B.V.)ISSN: 0925-2312
Enhanced Gradient for Training Restricted Boltzmann Machines
Cho, K.; Raiko, T.; Ilin, A.
2013 in NEURAL COMPUTATION (MIT PRESS)ISSN: 0899-7667
Semi-Supervised Anomaly Detection - Towards Model-Independent Searches of New Physics
Kuusela, Mikael; Malmi, Eric; Raiko, Tapani; Vatanen, Tommi
2012 in Journal of Physics: Conference Series (IOP Publishing Ltd.)ISSN: 1742-6588
Missing-feature reconstruction with a bounded nonlinear state-space model
Remes, Ulpu; Palomäki, Kalle J.; Raiko, Tapani; Honkela, Antti; Kurimo, Mikko
2011 in IEEE SIGNAL PROCESSING LETTERS (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC)ISSN: 1070-9908
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Honkela, Antti; Raiko, Tapani; Kuusela, Mikael; Tornio, Matti; Karhunen, Juha
2010 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)ISSN: 1532-4435
Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani
2010 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)ISSN: 1532-4435
Variational Bayesian learning of nonlinear hidden state-space models for model predictive control
Raiko, Tapani; Tornio, Matti
2009 in NEUROCOMPUTING (Elsevier Science B.V.)Building Blocks for Variational Bayesian Learning of Latent Variable Models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha
2007 in JOURNAL OF MACHINE LEARNING RESEARCH (MICROTOME PUBL)Logical Hidden Markov Models
Kersting, Kristian; De Raedt, Luc; Raiko, Tapani
2006 in JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH (Morgan Kaufmann Publishers, Inc.)ISSN: 1076-9757
How to Pretrain Deep Boltzmann Machines in Two Stages
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha
2015 ISBN: 978-3-319-09903-3
Oscillatory Neural Network for Image Segmentation (Chapter 7) with Biased Competition for Attention
Raiko, Tapani; Valpola, Harri
2011 ISBN: 978-1-4614-0163-6
ISSN: 0065-2598
Conference proceedingsSemi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation
Wang, Huiling ; Raiko, Tapani; Lensu, Lasse; Wang, Tinghuai; Karhunen, Juha2017 in Lecture Notes in Computer Science (SPRINGER)ISBN: 9783319541815ISSN: 0302-9743Ladder Variational Autoencoders
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 in Advances in neural information processing systems (Neural Information Processing Systems Foundation)ISSN: 1049-5258Scalable gradient-based tuning of continuous regularization hyperparameters
Luketina, Jelena; Berglund, Mathias; Greff, Klaus; Raiko, Tapani2016 ISBN: 9781510829008DopeLearning A computational approach to rap lyrics generation
Malmi, Eric; Takala, Pyry; Toivonen, Hannu; Raiko, Tapani; Gionis, Aristides2016 ISBN: 9781450342322Bidirectional recurrent neural networks as generative models
Berglund, Mathias; Raiko, Tapani; Honkala, Mikko; Kärkkäinen, Leo; Vetek, Akos; Karhunen, Juha2015 ISSN: 1049-5258Iterative Neural Autoregressive Distribution Estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua2015 ISSN: 1049-5258Semi-supervised learning with Ladder networks
Rasmus, Antti; Valpola, Harri; Honkala, Mikko; Berglund, Mathias; Raiko, Tapani2015 ISSN: 1049-5258Linear State-Space Model with Time-Varying Dynamics
Luttinen, Jaakko; Raiko, Tapani; Ilin, Alexander2014 ISBN: 978-3-662-44850-2Iterative neural autoregressive distribution estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua2014 Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information
Berglund, Mathias; Raiko, Tapani; Cho, KyungHyun2013 ISBN: 978-3-642-42053-5A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2013 ISBN: 978-3-642-40727-7Gaussian-Bernoulli Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2013 Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation
Keronen, Sami; Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Palomäki, Kalle J.2013 in International Conference on Acoustics Speech and Signal Processing ICASSP (SPRINGER GABLER)ISBN: 978-1-4799-0356-6ISSN: 1520-6149Variational Bayesian PCA versus k-NN on a Very Sparse Reddit Voting Dataset
Klapuri, Jussa; Nieminen, Ilari T.; Raiko, Tapani; Lagus, Krista2013 ISBN: 978-3-642-41397-1Two-Layer Contractive Encodings with Linear Transformation of Perceptrons for Semi-Supervised Learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven2013 ISBN: 978-3-642-42042-9Two-layer contractive encodings with shortcuts for semi-supervised learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven2013 in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (SPRINGER GABLER)ISBN: 9783642420535ISSN: 0302-9743Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities
Vatanen, Tommi; Raiko, Tapani; Valpola, Harri; LeCun, Yann2013 ISBN: 978-3-642-42042-9Controlling Self-Organization and Handling Missing Values in SOM and GTM
Vatanen, Tommi; Nieminen, Ilari T.; Honkela, Timo; Raiko, Tapani; Lagus, Krista2013 ISBN: 978-3-642-35229-4Learning Deep Belief Networks from Non-Stationary Streams
Calandra, R.; Raiko, T.; Pouzols, Montesino2012 ISBN: 978-3-642-33269-2ISSN: 0302-9743Tikhonov-Type Regularization for Restricted Boltzmann Machines
Cho, K.; Ilin, A.; Raiko, T.2012 ISBN: 978-3-642-33268-5ISSN: 0302-9743A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2012 Reinforcement Learning in Real-Time Strategy Games
Raiko, Tapani2012 Towards Generalizing the Success of Monte-Carlo Tree Search beyond the Game of Go
Raiko, Tapani2012 ISBN: 978-1-61499-097-0Deep learning made easier by linear transformations in perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann2012 ISSN: 1532-4435Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts
Raitio, Juha; Raiko, Tapani; Honkela, Timo2012 ISBN: 978-3-642-33265-4ISSN: 0302-9743Semi-Supervised Detection of Collective Anomalies with an Application in High Energy Particle Physics
Vatanen, Tommi; Kuusela, Mikael; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu2012 ISBN: 978-1-4673-1488-6Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines
Cho, KyungHyun; Ilin, Alexander; Raiko, Tapani2011 Gaussian-Bernoulli Deep Boltzmann Machine
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2011 Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2011 Deep Learning Made Easier by Linear Transformations in Perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann2011 Enhanced Gradient for Learning Boltzmann Machines
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Parallel Tempering is Efficient for Learning Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander2010 Novelty detection by nonlinear factor analysis for structural health monitoring
Lämsä, Ville; Raiko, Tapani2010 ISBN: 978-1-4244-7875-0ISSN: 1551-2541Document Classification Utilising Ontologies and Relations between Documents
Nyberg, Katariina; Raiko, Tapani; Tiinanen, Teemu; Hyvönen, Eero2010 Oscillatory Neural Network for Image Segmentation with Biased Competition for Attention
Raiko, Tapani; Valpola, Harri2010 Extending Self-Organizing Maps with Uncertainty Information of Probabilistic PCA
Sovilj, Dusan; Raiko, Tapani; Oja, Erkki2010 Binary Principal Component Analysis in the Netflix Collaborative Filtering Task
Kozma, Laszlo; Ilin, Alexander; Raiko, Tapani2009 A Gradient-Based Algorithm Competitive with Variational Bayesian EM for Mixture of Gaussians
Kuusela, Mikael; Raiko, Tapani; Honkela, Antti; Karhunen, Juha2009 Transformations for Variational Factor Analysis to Speed up Learning
Luttinen, Jaakko; Ilin, Alexander; Raiko, Tapani2009 Learning mixture models - courseware for finite mixture distributions of multivariate Bernoulli distributions
Hollmén, Jaakko; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2008 Variational Inference and Learning for Continuous-Time Nonlinear State-Space Models
Honkela, Antti; Harva, Markus; Raiko, Tapani; Karhunen, Juha2008 Macadamia: Master's Programme in Machine Learning and Data Mining
Raiko, Tapani; Puolamäki, Kai; Karhunen, Juha; Hollmén, Jaakko; Honkela, Antti; Kaski, Samuel; Mannila, Heikki; Oja, Erkki; Simula, Olli2008 Principal Component Analysis for Sparse High-Dimensional Data
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2008 Application of UCT Search to the Connection Games of Hex, Y, *Star, and Renkula!
Raiko, Tapani; Peltonen, Jaakko2008 Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha2007 State Inference in Variational Bayesian Nonlinear State-Space Models
Raiko, Tapani; Tornio, Matti; Honkela, Antti; Karhunen, Juha2006 ISBN: 3-540-32630-8ISSN: 0302-9743Higher order statistics in play-out analysis
Raiko, Tapani2006 ISBN: 952-5677-00-1ISSN: 1238-4658Variational Bayesian Approach for Nonlinear Identification and Control
Tornio, Matti; Raiko, Tapani2006 Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework
Harva, M.; Raiko, T.; Honkela, A.; Valpola, H.; Karhunen, J.2005 'Say EM' for Selecting Probabilistic Models for Logical Sequences
Kersting, K.; Raiko, T.2005 Learning Nonlinear State-Space Models for Control
Raiko, T.; Tornio, M.2005 Nonlinear Relational Markov Networks with an Application to the Game of Go
Raiko, T.2005 Partially Observed Values
Raiko, Tapani2004 The Go-Playing Program Called Go81
Raiko, Tapani2004 A Structural GEM for Learning Logical Hidden Markov Models
Kersting, K.; Raiko, T.; De Raedt, L.2003 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models
Kersting, K.; Raiko, T.; Kramer, S.; De Raedt, L.2003 Missing Values in Hierarchical Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.; Östman, T.; Karhunen, J.2003 Logical Hidden Markov Models (Extended Abstract)
Kersting, K.; Raiko, Tapani; De Raedt, L.2002 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models (Extended abstract)
Kersting, K.; Raiko, Tapani; Kramer, S.; De Raedt, L.2002 Bayesian Learning of Logical Hidden Markov Models
Raiko, Tapani; Kersting, K.; Karhunen, J.; De Raedt, L.2002 Constructing Graphical Models for Bayesian Ensemble Learning from Simple Building Blocks
Valpola, Harri; Raiko, T.; Karhunen, J.2002 Building Blocks for Hierarchical Latent Variable Models
Valpola, Harri; Raiko, T.; Karhunen, J.2001 Non-refereed scientific articles
Book sectionUnsupervised Deep Learning: A Short Review
Karhunen, J.; Raiko, T.; Cho, K.2015 ISBN: 9780128028063Unrefereed conference proceedingsAdvances in Training Restricted Boltzmann Machines
Cho, K.; Raiko, Tapani; Karhunen, Juha2012 ISBN: 978-3-642-34155-7Scientific books (monographs)
Book (editor)Neurocomputing, Special Issue on Machine Learning for Signal Processing 2010, 80:1-128
Peltonen, Jaakko; Raiko, Tapani; Kaski, Samuel2012 ISSN: 0925-2312AI and Machine Consciousness, Proceedings of the 13th Finnish Artificial Intelligence Conference (STeP 2008)
Raiko, Tapani; Haikonen, Pentti; Väyrynen, Jaakko2008 Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006)
Honkela, Timo; Raiko, Tapani; Kortela, Jukka; Valpola, Harri2006 ISBN: 952-5677-00-1Developments in Artificial Intelligence and the Semantic Web - Proceedings of the 12th Finnish AI Conference STeP 2006.Finland, October 26-27, 2006
Hyvönen, Eero; Kauppinen, Tomi; Kortela, Jukka; Laukkanen, Mikko; Raiko, Tapani; Viljanen, Kim2006 ISBN: 952-5677-02-8Publications intended for professional communities
Article in professional journalJonglöörauksen matematiikka
Raiko, Tapani2013 in Arpakannus (Finnish Artificial Intelligence Society)ISSN: 0783-3121Sudoku ihmisen ja koneen ratkaisemana
Raiko, Tapani2009 in Arpakannus, Magazine of the Finnish Artificial Intelligence Society (Finnish Artificial Intelligence Society)Article in professional conference proceedingsUnderstanding Regularization by Virtual Adversarial Training, Ladder Networks and Others
Abbas, Mudassar; Kivinen, Jyri; Raiko, Tapani2016 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Pekka; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2015 Published development or research reportHow to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.2001 Audiovisual material, ICT software
ICT programs or applicationsBayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.2003
Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation
Wang, Huiling ; Raiko, Tapani; Lensu, Lasse; Wang, Tinghuai; Karhunen, Juha
2017 in Lecture Notes in Computer Science (SPRINGER)ISBN: 9783319541815
ISSN: 0302-9743
Ladder Variational Autoencoders
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole
2016 in Advances in neural information processing systems (Neural Information Processing Systems Foundation)ISSN: 1049-5258
Scalable gradient-based tuning of continuous regularization hyperparameters
Luketina, Jelena; Berglund, Mathias; Greff, Klaus; Raiko, Tapani
2016 ISBN: 9781510829008
DopeLearning A computational approach to rap lyrics generation
Malmi, Eric; Takala, Pyry; Toivonen, Hannu; Raiko, Tapani; Gionis, Aristides
2016 ISBN: 9781450342322
Bidirectional recurrent neural networks as generative models
Berglund, Mathias; Raiko, Tapani; Honkala, Mikko; Kärkkäinen, Leo; Vetek, Akos; Karhunen, Juha
2015 ISSN: 1049-5258
Iterative Neural Autoregressive Distribution Estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua
2015 ISSN: 1049-5258
Semi-supervised learning with Ladder networks
Rasmus, Antti; Valpola, Harri; Honkala, Mikko; Berglund, Mathias; Raiko, Tapani
2015 ISSN: 1049-5258
Linear State-Space Model with Time-Varying Dynamics
Luttinen, Jaakko; Raiko, Tapani; Ilin, Alexander
2014 ISBN: 978-3-662-44850-2
Iterative neural autoregressive distribution estimator (NADE-k)
Raiko, Tapani; Yao, Li; Cho, KyungHyun; Bengio, Yoshua
2014 Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information
Berglund, Mathias; Raiko, Tapani; Cho, KyungHyun
2013 ISBN: 978-3-642-42053-5
A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha
2013 ISBN: 978-3-642-40727-7
Gaussian-Bernoulli Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander
2013 Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation
Keronen, Sami; Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Palomäki, Kalle J.
2013 in International Conference on Acoustics Speech and Signal Processing ICASSP (SPRINGER GABLER)ISBN: 978-1-4799-0356-6
ISSN: 1520-6149
Variational Bayesian PCA versus k-NN on a Very Sparse Reddit Voting Dataset
Klapuri, Jussa; Nieminen, Ilari T.; Raiko, Tapani; Lagus, Krista
2013 ISBN: 978-3-642-41397-1
Two-Layer Contractive Encodings with Linear Transformation of Perceptrons for Semi-Supervised Learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven
2013 ISBN: 978-3-642-42042-9
Two-layer contractive encodings with shortcuts for semi-supervised learning
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven
2013 in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (SPRINGER GABLER)ISBN: 9783642420535
ISSN: 0302-9743
Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities
Vatanen, Tommi; Raiko, Tapani; Valpola, Harri; LeCun, Yann
2013 ISBN: 978-3-642-42042-9
Controlling Self-Organization and Handling Missing Values in SOM and GTM
Vatanen, Tommi; Nieminen, Ilari T.; Honkela, Timo; Raiko, Tapani; Lagus, Krista
2013 ISBN: 978-3-642-35229-4
Learning Deep Belief Networks from Non-Stationary Streams
Calandra, R.; Raiko, T.; Pouzols, Montesino
2012 ISBN: 978-3-642-33269-2
ISSN: 0302-9743
Tikhonov-Type Regularization for Restricted Boltzmann Machines
Cho, K.; Ilin, A.; Raiko, T.
2012 ISBN: 978-3-642-33268-5
ISSN: 0302-9743
A Two-stage Pretraining Algorithm for Deep Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander; Karhunen, Juha
2012 Reinforcement Learning in Real-Time Strategy Games
Raiko, Tapani
2012 Towards Generalizing the Success of Monte-Carlo Tree Search beyond the Game of Go
Raiko, Tapani
2012 ISBN: 978-1-61499-097-0
Deep learning made easier by linear transformations in perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann
2012 ISSN: 1532-4435
Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts
Raitio, Juha; Raiko, Tapani; Honkela, Timo
2012 ISBN: 978-3-642-33265-4
ISSN: 0302-9743
Semi-Supervised Detection of Collective Anomalies with an Application in High Energy Particle Physics
Vatanen, Tommi; Kuusela, Mikael; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu
2012 ISBN: 978-1-4673-1488-6
Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines
Cho, KyungHyun; Ilin, Alexander; Raiko, Tapani
2011 Gaussian-Bernoulli Deep Boltzmann Machine
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander
2011 Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander
2011 Deep Learning Made Easier by Linear Transformations in Perceptrons
Raiko, Tapani; Valpola, Harri; LeCun, Yann
2011 Enhanced Gradient for Learning Boltzmann Machines
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander
2011 Parallel Tempering is Efficient for Learning Restricted Boltzmann Machines
Cho, KyungHyun; Raiko, Tapani; Ilin, Alexander
2010 Novelty detection by nonlinear factor analysis for structural health monitoring
Lämsä, Ville; Raiko, Tapani
2010 ISBN: 978-1-4244-7875-0
ISSN: 1551-2541
Document Classification Utilising Ontologies and Relations between Documents
Nyberg, Katariina; Raiko, Tapani; Tiinanen, Teemu; Hyvönen, Eero
2010 Oscillatory Neural Network for Image Segmentation with Biased Competition for Attention
Raiko, Tapani; Valpola, Harri
2010 Extending Self-Organizing Maps with Uncertainty Information of Probabilistic PCA
Sovilj, Dusan; Raiko, Tapani; Oja, Erkki
2010 Binary Principal Component Analysis in the Netflix Collaborative Filtering Task
Kozma, Laszlo; Ilin, Alexander; Raiko, Tapani
2009 A Gradient-Based Algorithm Competitive with Variational Bayesian EM for Mixture of Gaussians
Kuusela, Mikael; Raiko, Tapani; Honkela, Antti; Karhunen, Juha
2009 Transformations for Variational Factor Analysis to Speed up Learning
Luttinen, Jaakko; Ilin, Alexander; Raiko, Tapani
2009 Learning mixture models - courseware for finite mixture distributions of multivariate Bernoulli distributions
Hollmén, Jaakko; Raiko, Tapani
2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha
2008 Variational Inference and Learning for Continuous-Time Nonlinear State-Space Models
Honkela, Antti; Harva, Markus; Raiko, Tapani; Karhunen, Juha
2008 Macadamia: Master's Programme in Machine Learning and Data Mining
Raiko, Tapani; Puolamäki, Kai; Karhunen, Juha; Hollmén, Jaakko; Honkela, Antti; Kaski, Samuel; Mannila, Heikki; Oja, Erkki; Simula, Olli
2008 Principal Component Analysis for Sparse High-Dimensional Data
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha
2008 Application of UCT Search to the Connection Games of Hex, Y, *Star, and Renkula!
Raiko, Tapani; Peltonen, Jaakko
2008 Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Raiko, Tapani; Ilin, Alexander; Karhunen, Juha
2007 State Inference in Variational Bayesian Nonlinear State-Space Models
Raiko, Tapani; Tornio, Matti; Honkela, Antti; Karhunen, Juha
2006 ISBN: 3-540-32630-8
ISSN: 0302-9743
Higher order statistics in play-out analysis
Raiko, Tapani
2006 ISBN: 952-5677-00-1
ISSN: 1238-4658
Variational Bayesian Approach for Nonlinear Identification and Control
Tornio, Matti; Raiko, Tapani
2006 Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework
Harva, M.; Raiko, T.; Honkela, A.; Valpola, H.; Karhunen, J.
2005 'Say EM' for Selecting Probabilistic Models for Logical Sequences
Kersting, K.; Raiko, T.
2005 Learning Nonlinear State-Space Models for Control
Raiko, T.; Tornio, M.
2005 Nonlinear Relational Markov Networks with an Application to the Game of Go
Raiko, T.
2005 Partially Observed Values
Raiko, Tapani
2004 The Go-Playing Program Called Go81
Raiko, Tapani
2004 A Structural GEM for Learning Logical Hidden Markov Models
Kersting, K.; Raiko, T.; De Raedt, L.
2003 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models
Kersting, K.; Raiko, T.; Kramer, S.; De Raedt, L.
2003 Missing Values in Hierarchical Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.; Östman, T.; Karhunen, J.
2003 Logical Hidden Markov Models (Extended Abstract)
Kersting, K.; Raiko, Tapani; De Raedt, L.
2002 Towards Discovering Structural Signatures of Protein Folds based on Logical Hidden Markov Models (Extended abstract)
Kersting, K.; Raiko, Tapani; Kramer, S.; De Raedt, L.
2002 Bayesian Learning of Logical Hidden Markov Models
Raiko, Tapani; Kersting, K.; Karhunen, J.; De Raedt, L.
2002 Constructing Graphical Models for Bayesian Ensemble Learning from Simple Building Blocks
Valpola, Harri; Raiko, T.; Karhunen, J.
2002 Building Blocks for Hierarchical Latent Variable Models
Valpola, Harri; Raiko, T.; Karhunen, J.
2001 Unsupervised Deep Learning: A Short Review
Karhunen, J.; Raiko, T.; Cho, K.
2015 ISBN: 9780128028063
Unrefereed conference proceedingsAdvances in Training Restricted Boltzmann Machines
Cho, K.; Raiko, Tapani; Karhunen, Juha2012 ISBN: 978-3-642-34155-7Scientific books (monographs)
Book (editor)Neurocomputing, Special Issue on Machine Learning for Signal Processing 2010, 80:1-128
Peltonen, Jaakko; Raiko, Tapani; Kaski, Samuel2012 ISSN: 0925-2312AI and Machine Consciousness, Proceedings of the 13th Finnish Artificial Intelligence Conference (STeP 2008)
Raiko, Tapani; Haikonen, Pentti; Väyrynen, Jaakko2008 Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006)
Honkela, Timo; Raiko, Tapani; Kortela, Jukka; Valpola, Harri2006 ISBN: 952-5677-00-1Developments in Artificial Intelligence and the Semantic Web - Proceedings of the 12th Finnish AI Conference STeP 2006.Finland, October 26-27, 2006
Hyvönen, Eero; Kauppinen, Tomi; Kortela, Jukka; Laukkanen, Mikko; Raiko, Tapani; Viljanen, Kim2006 ISBN: 952-5677-02-8Publications intended for professional communities
Article in professional journalJonglöörauksen matematiikka
Raiko, Tapani2013 in Arpakannus (Finnish Artificial Intelligence Society)ISSN: 0783-3121Sudoku ihmisen ja koneen ratkaisemana
Raiko, Tapani2009 in Arpakannus, Magazine of the Finnish Artificial Intelligence Society (Finnish Artificial Intelligence Society)Article in professional conference proceedingsUnderstanding Regularization by Virtual Adversarial Training, Ladder Networks and Others
Abbas, Mudassar; Kivinen, Jyri; Raiko, Tapani2016 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Pekka; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2015 Published development or research reportHow to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.2001 Audiovisual material, ICT software
ICT programs or applicationsBayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.2003
Advances in Training Restricted Boltzmann Machines
Cho, K.; Raiko, Tapani; Karhunen, Juha
2012 ISBN: 978-3-642-34155-7
Neurocomputing, Special Issue on Machine Learning for Signal Processing 2010, 80:1-128
Peltonen, Jaakko; Raiko, Tapani; Kaski, Samuel
2012 ISSN: 0925-2312
AI and Machine Consciousness, Proceedings of the 13th Finnish Artificial Intelligence Conference (STeP 2008)
Raiko, Tapani; Haikonen, Pentti; Väyrynen, Jaakko
2008 Proceedings of the Ninth Scandinavian Conference on Artificial Intelligence (SCAI 2006)
Honkela, Timo; Raiko, Tapani; Kortela, Jukka; Valpola, Harri
2006 ISBN: 952-5677-00-1
Developments in Artificial Intelligence and the Semantic Web - Proceedings of the 12th Finnish AI Conference STeP 2006.Finland, October 26-27, 2006
Hyvönen, Eero; Kauppinen, Tomi; Kortela, Jukka; Laukkanen, Mikko; Raiko, Tapani; Viljanen, Kim
2006 ISBN: 952-5677-02-8
Publications intended for professional communities
Article in professional journalJonglöörauksen matematiikka
Raiko, Tapani2013 in Arpakannus (Finnish Artificial Intelligence Society)ISSN: 0783-3121Sudoku ihmisen ja koneen ratkaisemana
Raiko, Tapani2009 in Arpakannus, Magazine of the Finnish Artificial Intelligence Society (Finnish Artificial Intelligence Society)Article in professional conference proceedingsUnderstanding Regularization by Virtual Adversarial Training, Ladder Networks and Others
Abbas, Mudassar; Kivinen, Jyri; Raiko, Tapani2016 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Pekka; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2015 Published development or research reportHow to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.2001 Audiovisual material, ICT software
ICT programs or applicationsBayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.2003
Jonglöörauksen matematiikka
Raiko, Tapani
2013 in Arpakannus (Finnish Artificial Intelligence Society)ISSN: 0783-3121
Sudoku ihmisen ja koneen ratkaisemana
Raiko, Tapani
2009 in Arpakannus, Magazine of the Finnish Artificial Intelligence Society (Finnish Artificial Intelligence Society)Understanding Regularization by Virtual Adversarial Training, Ladder Networks and Others
Abbas, Mudassar; Kivinen, Jyri; Raiko, Tapani
2016 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Pekka; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent
2015 Published development or research reportHow to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.2001 Audiovisual material, ICT software
ICT programs or applicationsBayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.2003
How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks
Kaae Sønderby, Casper; Raiko, Tapani; Maaløe, Lars; Kaae Sønderby, Søren; Winther, Ole
2016 Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Luketina, Jelena; Berglund, Mathias; Raiko, Tapani
2015 Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence
Berglund, Mathias; Raiko, Tapani
2014 Techniques for Learning Binary Stochastic Feedforward Neural Networks
Raiko, Tapani; Berglund, Mathias; Alain, Guillaume; Dinh, Laurent
2014 Derivations of the Enhanced Gradient for the Boltzmann Machine
Raiko, Tapani; Cho, KyungHyun; Ilin, Alexander
2011 Practical Approaches to Principal Component Analysis in the Presence of Missing Values
Ilin, Alexander; Raiko, Tapani
2008 Natural Conjugate Gradient in Variational Inference
Honkela, Antti; Tornio, Matti; Raiko, Tapani; Karhunen, Juha
2007 Building blocks for variational Bayesian learning of latent variable models
Raiko, Tapani; Valpola, Harri; Harva, Markus; Karhunen, Juha
2006 Missing Values in Nonlinear Factor Analysis
Raiko, Tapani; Valpola, H.
2001 Bayes Blocks Software Library
Valpola, H.; Honkela, A.; Harva, M.; Ilin, A.; Raiko, T.; Östman, T.
2003 Videos
Tapani Raiko, Aalto University - Visual Forum 2015
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