Tapani Raiko

Publication Activity (10 Years)

Years Active: 2002-2016
Publications (10 Years): 7

Top Topics

Boltzmann Machines

Supervised Learning

Top Venues

Publications

Matti Lankinen, Hannes Heikinheimo, Pyry Takala, Tapani Raiko, Juha Karhunen
A Character-Word Compositional Neural Language Model for Finnish. CoRR (2016)
Eric Malmi, Pyry Takala, Hannu Toivonen, Tapani Raiko, Aristides Gionis
DopeLearning: A Computational Approach to Rap Lyrics Generation. KDD (2016)
Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. ICML (2016)
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
Ladder Variational Autoencoders. NIPS (2016)
Huiling Wang, Tapani Raiko, Lasse Lensu, Tinghuai Wang, Juha Karhunen
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. ACCV (1) (2016)
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther
How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. CoRR (2016)
Huiling Wang, Tapani Raiko, Lasse Lensu, Tinghuai Wang, Juha Karhunen
Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation. CoRR (2016)
Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko
Semi-supervised Learning with Ladder Networks. NIPS (2015)
Tapani Raiko, Mathias Berglund, Guillaume Alain, Laurent Dinh
Techniques for Learning Binary Stochastic Feedforward Neural Networks. ICLR (Poster) (2015)
Jelena Luketina, Mathias Berglund, Klaus Greff, Tapani Raiko
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters. CoRR (2015)
Antti Rasmus, Harri Valpola, Tapani Raiko
Lateral Connections in Denoising Autoencoders Support Supervised Learning. CoRR (2015)
Mathias Berglund, Tapani Raiko, KyungHyun Cho
Measuring the usefulness of hidden units in Boltzmann machines with mutual information. Neural Networks 64 (2015)
Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series. CoRR (2015)
Tommi Vatanen, Maria Osmala, Tapani Raiko, Krista Lagus, Marko Sysi-Aho, Matej Oresic, Timo Honkela, Harri Lähdesmäki
Self-organization and missing values in SOM and GTM. Neurocomputing 147 (2015)
Antti Rasmus, Harri Valpola, Mikko Honkala, Mathias Berglund, Tapani Raiko
Semi-Supervised Learning with Ladder Network. CoRR (2015)
Eric Malmi, Pyry Takala, Hannu Toivonen, Tapani Raiko, Aristides Gionis
DopeLearning: A Computational Approach to Rap Lyrics Generation. CoRR (2015)
Hannes Schulz, KyungHyun Cho, Tapani Raiko, Sven Behnke
Two-layer contractive encodings for learning stable nonlinear features. Neural Networks 64 (2015)
Antti Rasmus, Tapani Raiko, Harri Valpola
Denoising autoencoder with modulated lateral connections learns invariant representations of natural images. ICLR (Workshop) (2015)
Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen
Bidirectional Recurrent Neural Networks as Generative Models. NIPS (2015)
Mathias Berglund, Tapani Raiko
Stochastic Gradient Estimate Variance in Contrastive Divergence and Persistent Contrastive Divergence. ICLR (Workshop Poster) (2014)
Jaakko Luttinen, Tapani Raiko, Alexander Ilin
Linear State-Space Model with Time-Varying Dynamics. ECML/PKDD (2) (2014)
Tapani Raiko, Li Yao, Kyunghyun Cho, Yoshua Bengio
Iterative Neural Autoregressive Distribution Estimator (NADE-k). CoRR (2014)
Tapani Raiko, Li Yao, KyungHyun Cho, Yoshua Bengio
Iterative Neural Autoregressive Distribution Estimator NADE-k. NIPS (2014)
Mathias Berglund, Tapani Raiko, KyungHyun Cho
Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information. ICONIP (1) (2013)
Jussa Klapuri, Ilari T. Nieminen, Tapani Raiko, Krista Lagus
Variational Bayesian PCA versus k-NN on a Very Sparse Reddit Voting Dataset. IDA (2013)
Sami Keronen, KyungHyun Cho, Tapani Raiko, Alexander Ilin, Kalle J. Palomäki
Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation. ICASSP (2013)
Hannes Schulz, KyungHyun Cho, Tapani Raiko, Sven Behnke
Two-Layer Contractive Encodings with Shortcuts for Semi-supervised Learning. ICONIP (1) (2013)
KyungHyun Cho, Tapani Raiko, Alexander Ilin, Juha Karhunen
A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. ICANN (2013)
KyungHyun Cho, Tapani Raiko, Alexander Ilin
Enhanced Gradient for Training Restricted Boltzmann Machines. Neural Comput. 25 (3) (2013)
Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun
Pushing Stochastic Gradient towards Second-Order Methods - Backpropagation Learning with Transformations in Nonlinearities. ICONIP (1) (2013)
KyungHyun Cho, Tapani Raiko, Alexander Ilin
Gaussian-Bernoulli deep Boltzmann machine. IJCNN (2013)
Tommi Vatanen, Tapani Raiko, Harri Valpola, Yann LeCun
Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities ICLR (Workshop Poster) (2013)
Tele Hao, Tapani Raiko, Alexander Ilin, Juha Karhunen
Gated Boltzmann Machine in Texture Modeling. ICANN (2) (2012)
Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen
Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework CoRR (2012)
Tommi Vatanen, Ilari T. Nieminen, Timo Honkela, Tapani Raiko, Krista Lagus
Controlling Self-Organization and Handling Missing Values in SOM and GTM. WSOM (2012)
Juha Raitio, Tapani Raiko, Timo Honkela
Hybrid Bilinear and Trilinear Models for Exploratory Analysis of Three-Way Poisson Counts. ICANN (2) (2012)
Jaakko Peltonen, Tapani Raiko, Samuel Kaski
Machine learning for signal processing 2010. Neurocomputing 80 (2012)
Kristian Kersting, Tapani Raiko
'Say EM' for Selecting Probabilistic Models for Logical Sequences CoRR (2012)
Tommi Vatanen, Mikael Kuusela, Eric Malmi, Tapani Raiko, Timo Aaltonen, Yoshikazu Nagai
Semi-supervised detection of collective anomalies with an application in high energy particle physics. IJCNN (2012)
António Gusmão, Tapani Raiko
Towards Generalizing the Success of Monte-Carlo Tree Search beyond the Game of Go. ECAI (2012)
KyungHyun Cho, Alexander Ilin, Tapani Raiko
Tikhonov-Type Regularization for Restricted Boltzmann Machines. ICANN (1) (2012)
Roberto Calandra, Tapani Raiko, Marc Peter Deisenroth, Federico Montesino-Pouzols
Learning Deep Belief Networks from Non-stationary Streams. ICANN (2) (2012)
Tapani Raiko, Harri Valpola, Yann LeCun
Deep Learning Made Easier by Linear Transformations in Perceptrons. AISTATS (2012)
KyungHyun Cho, Tapani Raiko, Alexander Ilin
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines. ICML (2011)
Luc De Raedt, Kristian Kersting, Tapani Raiko
Logical Hidden Markov Models CoRR (2011)
KyungHyun Cho, Alexander Ilin, Tapani Raiko
Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines. ICANN (1) (2011)
Ulpu Remes, Kalle J. Palomäki, Tapani Raiko, Antti Honkela, Mikko Kurimo
Missing-Feature Reconstruction With a Bounded Nonlinear State-Space Model. IEEE Signal Process. Lett. 18 (10) (2011)
Katariina Nyberg, Tapani Raiko, Teemu Tiinanen, Eero Hyvönen
Document classification utilising ontologies and relations between documents. MLG@KDD (2010)
Alexander Ilin, Tapani Raiko
Practical Approaches to Principal Component Analysis in the Presence of Missing Values. J. Mach. Learn. Res. 11 (2010)
KyungHyun Cho, Tapani Raiko, Alexander Ilin
Parallel tempering is efficient for learning restricted Boltzmann machines. IJCNN (2010)
Dusan Sovilj, Tapani Raiko, Erkki Oja
Extending Self-Organizing Maps with uncertainty information of probabilistic PCA. IJCNN (2010)
Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. J. Mach. Learn. Res. 11 (2010)
Tapani Raiko, Matti Tornio
Variational Bayesian learning of nonlinear hidden state-space models for model predictive control. Neurocomputing 72 (16-18) (2009)
Jaakko Luttinen, Alexander Ilin, Tapani Raiko
Transformations for variational factor analysis to speed up learning. ESANN (2009)
Mikael Kuusela, Tapani Raiko, Antti Honkela, Juha Karhunen
A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians. IJCNN (2009)
Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen
Building Blocks for Variational Bayesian Learning of Latent Variable Models. J. Mach. Learn. Res. 8 (2007)
Tapani Raiko, Alexander Ilin, Juha Karhunen
Principal Component Analysis for Large Scale Problems with Lots of Missing Values. ECML (2007)
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Karhunen
Natural Conjugate Gradient in Variational Inference. ICONIP (2) (2007)
Tapani Raiko, Alexander Ilin, Juha Karhunen
Principal Component Analysis for Sparse High-Dimensional Data. ICONIP (1) (2007)
Kristian Kersting, Luc De Raedt, Tapani Raiko
Logical Hidden Markov Models. J. Artif. Intell. Res. 25 (2006)
Tapani Raiko, Matti Tornio, Antti Honkela, Juha Karhunen
State Inference in Variational Bayesian Nonlinear State-Space Models. ICA (2006)
Tapani Raiko
Nonlinear Relational Markov Networks with an Application to the Game of Go. ICANN (2) (2005)
Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen
Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. UAI (2005)
Kristian Kersting, Tapani Raiko
"Say EM" for Selecting Probabilistic Models for Logical Sequences. UAI (2005)
Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt
Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models. Pacific Symposium on Biocomputing (2003)
Kristian Kersting, Tapani Raiko, Luc De Raedt
Logical Hidden Markov Models (Extendes abstract). Probabilistic Graphical Models (2002)