Mikael Kågebäck

According to our database, Mikael Kågebäck authored at least 9 papers between 2014 and 2018.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2018

DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning.

Mikael Kågebäck, Devdatt P. Dubhashi, Asad B. Sayeed

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017

Disentangled Representations for Manipulation of Sentiment in Text.

Maria Larsson, Amanda Nilsson, Mikael Kågebäck

CoRR, 2017

Query-Based Abstractive Summarization Using Neural Networks.

Johan Hasselqvist, Niklas Helmertz, Mikael Kågebäck

CoRR, 2017

2016

Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence.

Emilio Jorge, Mikael Kågebäck, Emil Gustavsson

CoRR, 2016

Word Sense Disambiguation using a Bidirectional LSTM.

Mikael Kågebäck, Hans Salomonsson

Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon, 2016

2015

Visions and open challenges for a knowledge-based culturomics.

Nina Tahmasebi, Lars Borin, Gabriele Capannini, Devdatt P. Dubhashi, Peter Exner, Markus Forsberg, Gerhard Gossen, Fredrik D. Johansson, Richard Johansson, Mikael Kågebäck, Olof Mogren, Pierre Nugues, Thomas Risse

Int. J. Digit. Libr., 2015

Extractive Summarization by Aggregating Multiple Similarities.

Olof Mogren, Mikael Kågebäck, Devdatt P. Dubhashi

Proceedings of the Recent Advances in Natural Language Processing, 2015

Neural context embeddings for automatic discovery of word senses.

Mikael Kågebäck, Fredrik D. Johansson, Richard Johansson, Devdatt P. Dubhashi

Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, 2015

2014

Extractive Summarization using Continuous Vector Space Models.

Mikael Kågebäck, Olof Mogren, Nina Tahmasebi, Devdatt P. Dubhashi

Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality, 2014