no code implementations • 4 May 2024 • Vadim Liventsev, Vivek Kumar, Allmin Pradhap Singh Susaiyah, Zixiu Wu, Ivan Rodin, Asfand Yaar, Simone Baloccu, Marharyta Beraziuk, Sebastiano Battiato, Giovanni Maria Farinella, Aki Härmä, Rim Helaoui, Milan Petkovic, Diego Reforgiato Recupero, Ehud Reiter, Daniele Riboni, Raymond Sterling
The use of machine learning in Healthcare has the potential to improve patient outcomes as well as broaden the reach and affordability of Healthcare.
no code implementations • 24 Jul 2023 • Allmin Susaiyah, Abhinay Pandya, Aki Härmä
We present a novel method for mining opinions from text collections using generative language models trained on data collected from different populations.
no code implementations • 24 Jul 2023 • Allmin Susaiyah, Aki Härmä, Milan Petković
In natural language generation (NLG), insight mining is seen as a data-to-text task, where data is mined for interesting patterns and verbalised into 'insight' statements.
no code implementations • 19 May 2023 • Aki Härmä, Ulf Grossekathöfer, Okke Ouweltjes, Venkata Srikanth Nallanthighal
Virtual Respiratory Belt, VRB, algorithms estimate the belt sensor waveform from speech audio.
no code implementations • 20 Apr 2023 • Vadim Liventsev, Anastasiia Grishina, Aki Härmä, Leon Moonen
Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metrics or human evaluation), but achieve a low or even zero accuracy as measured by unit tests due to small imperfections, such as the wrong input or output format.
no code implementations • 22 Jun 2021 • Ronja Möller, Antonino Furnari, Sebastiano Battiato, Aki Härmä, Giovanni Maria Farinella
This paper is concerned with the navigation aspect of a socially-compliant robot and provides a survey of existing solutions for the relevant areas of research as well as an outlook on possible future directions.
2 code implementations • 8 Feb 2021 • Vadim Liventsev, Aki Härmä, Milan Petković
Automatic programming, the task of generating computer programs compliant with a specification without a human developer, is usually tackled either via genetic programming methods based on mutation and recombination of programs, or via neural language models.
1 code implementation • 23 Jan 2021 • Vadim Liventsev, Aki Härmä, Milan Petković
Most state of the art decision systems based on Reinforcement Learning (RL) are data-driven black-box neural models, where it is often difficult to incorporate expert knowledge into the models or let experts review and validate the learned decision mechanisms.