no code implementations • 1 Feb 2024 • Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad
The query, key, and value are often intertwined and generated within those blocks via a single, shared linear transformation.
no code implementations • 3 Oct 2023 • Mohamed-Bachir Belaid, Jivitesh Sharma, Lei Jiao, Ole-Christoffer Granmo, Per-Arne Andersen, Anis Yazidi
Tsetlin Machines (TMs) have garnered increasing interest for their ability to learn concepts via propositional formulas and their proven efficiency across various application domains.
no code implementations • 17 May 2023 • Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad
The manifold hypothesis posits that high-dimensional data often lies on a lower-dimensional manifold and that utilizing this manifold as the target space yields more efficient representations.
no code implementations • 23 Apr 2023 • Debesh Jha, Ashish Rauniyar, Abhiskek Srivastava, Desta Haileselassie Hagos, Nikhil Kumar Tomar, Vanshali Sharma, Elif Keles, Zheyuan Zhang, Ugur Demir, Ahmet Topcu, Anis Yazidi, Jan Erik Håakegård, Ulas Bagci
Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients.
1 code implementation • 13 Mar 2023 • Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad
Contrastive methods have performed better than generative models in previous state representation learning research.
1 code implementation • 11 Oct 2022 • Thu Nguyen, Rabindra Khadka, Nhan Phan, Anis Yazidi, Pål Halvorsen, Michael A. Riegler
For many use cases, combining information from different datasets can be of interest to improve a machine learning model's performance, especially when the number of samples from at least one of the datasets is small.
1 code implementation • 27 Jul 2022 • Sidney Pontes-Filho, Kristoffer Olsen, Anis Yazidi, Michael A. Riegler, Pål Halvorsen, Stefano Nichele
We evaluate a method to evolve a biologically-inspired artificial neural network that learns from environment reactions named Neuroevolution of Artificial General Intelligence (NAGI), a framework for low-level AGI.
1 code implementation • 30 Jun 2022 • Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad
Transformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks.
no code implementations • 28 Mar 2022 • Ismail Hassan, B. John Oommen, Anis Yazidi
In this paper, we devise a LA with artificial barriers for solving a general form of stochastic bimatrix game.
no code implementations • 2 Mar 2022 • Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad
In this article, we further explore the possibility of replacing priors with noise and sample the noise from a Gaussian distribution to introduce more diversity into this algorithm.
no code implementations • 2 Sep 2021 • Andrea M. Storås, Inga Strümke, Michael A. Riegler, Jakob Grauslund, Hugo L. Hammer, Anis Yazidi, Pål Halvorsen, Kjell G. Gundersen, Tor P. Utheim, Catherine Jackson
Although the term `AI' is commonly used, recent success in its applications to medicine is mainly due to advancements in the sub-field of machine learning, which has been used to automatically classify images and predict medical outcomes.
no code implementations • 28 Jun 2021 • Li Meng, Anis Yazidi, Morten Goodwin, Paal Engelstad
Using the board game Othello, we compare our algorithm with the baseline Q-learning algorithm, which is a combination of Double Q-learning and Dueling Q-learning.
no code implementations • 14 May 2021 • Eirik Molde Bårli, Anis Yazidi, Enrique Herrera Viedma, Hårek Haugerud
Two methods based on the ability of Variational Autoencoders to learn latent representations from network traffic flows are proposed.
1 code implementation • 6 Jan 2021 • Debesh Jha, Anis Yazidi, Michael A. Riegler, Dag Johansen, Håvard D. Johansen, Pål Halvorsen
Deep Neural Networks (DNNs) have become the de-facto standard in computer vision, as well as in many other pattern recognition tasks.
no code implementations • 27 Apr 2020 • Hugo L. Hammer, Anis Yazidi, Michael A. Riegler, Håvard Rue
The MSE is decomposed in tracking variance and bias and novel and efficient procedures to estimate these quantities are presented.
no code implementations • 22 Jan 2020 • Marco A. Pinto-Orellana, Diego C. Nascimento, Peyman Mirtaheri, Rune Jonassen, Anis Yazidi, Hugo L. Hammer
In the current paper, we introduce a parametric data-driven model for functional near-infrared spectroscopy that decomposes a signal into a series of independent, rescaled, time-shifted, hemodynamic basis functions.
1 code implementation • 3 Jul 2019 • Sidney Pontes-Filho, Anis Yazidi, Jianhua Zhang, Hugo Hammer, Gustavo B. M. Mello, Ioanna Sandvig, Gunnar Tufte, Stefano Nichele
The advantages of such implementation are its usage on specialized and optimized deep learning libraries, the capabilities to generalize it to other types of networks and the possibility to evolve cellular automata and other dynamical systems in terms of connectivity, update and learning rules.
no code implementations • 31 Aug 2018 • Bartosz Gembala, Anis Yazidi, Hårek Haugerud, Stefano Nichele
By default, the Linux network stack is not configured for highspeed large file transfer.
no code implementations • 12 Jul 2018 • Erik Aaron Hansen, Stefano Nichele, Anis Yazidi, Hårek Haugerud, Asieh Abolpour Mofrad, Alex Alcocer
Abruptions to the communication infrastructure happens occasionally, where manual dedicated personnel will go out to fix the interruptions, restoring communication abilities.
no code implementations • 23 Jun 2016 • Per-Arne Andersen, Christian Kråkevik, Morten Goodwin, Anis Yazidi
As main contribution of this paper, we propose a a novel Skill-Based Task Selector (SBTS) algorithm which is able to approximate a student's skill level based on his performance and consequently suggest adequate assignments.