582 citations · 1.2k across the 18 of their papers we have counts for
18 papers
A Character-Word Compositional Neural Language Model for Finnish
Matti Lankinen, Hannes Heikinheimo, Pyry Takala +2
Inspired by recent research, we explore ways to model the highly morphological Finnish language at the level of characters while maintaining the performance of word-level models. W…
Semi-Supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation
Huiling Wang, Tapani Raiko, Lasse Lensu +2
Deep convolutional neural networks (CNNs) have been immensely successful in many high-level computer vision tasks given large labeled datasets. However, for video semantic object s…
Ladder Variational Autoencoders
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe +2
Variational Autoencoders are powerful models for unsupervised learning. However deep models with several layers of dependent stochastic variables are difficult to train which limit…
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Jelena Luketina, Mathias Berglund, Klaus Greff +1
Hyperparameter selection generally relies on running multiple full training trials, with selection based on validation set performance. We propose a gradient-based approach for loc…
Semi-Supervised Learning with Ladder Networks
Antti Rasmus, Harri Valpola, Mikko Honkala +2
We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised c…
DopeLearning: A Computational Approach to Rap Lyrics Generation
Eric Malmi, Pyry Takala, Hannu Toivonen +2
Writing rap lyrics requires both creativity to construct a meaningful, interesting story and lyrical skills to produce complex rhyme patterns, which form the cornerstone of good fl…