Zobrazeno 1 - 10
of 767
pro vyhledávání: '"Yazidi, Anis"'
Electroencephalography (EEG) data provides a non-invasive method for researchers and clinicians to observe brain activity in real time. The integration of deep learning techniques with EEG data has significantly improved the ability to identify meani
Externí odkaz:
http://arxiv.org/abs/2409.17815
The expanding research on manifold-based self-supervised learning (SSL) builds on the manifold hypothesis, which suggests that the inherent complexity of high-dimensional data can be unraveled through lower-dimensional manifold embeddings. Capitalizi
Externí odkaz:
http://arxiv.org/abs/2405.13848
Vision Transformers implement multi-head self-attention via stacking multiple attention blocks. The query, key, and value are often intertwined and generated within those blocks via a single, shared linear transformation. This paper explores the conc
Externí odkaz:
http://arxiv.org/abs/2402.00534
Autor:
Belaid, Mohamed-Bachir, Sharma, Jivitesh, Jiao, Lei, Granmo, Ole-Christoffer, Andersen, Per-Arne, Yazidi, Anis
Tsetlin Machines (TMs) have garnered increasing interest for their ability to learn concepts via propositional formulas and their proven efficiency across various application domains. Despite this, the convergence proof for the TMs, particularly for
Externí odkaz:
http://arxiv.org/abs/2310.02005
Publikováno v:
ICLR 2024
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. While numerous traditional manifold-based techniques exis
Externí odkaz:
http://arxiv.org/abs/2305.10267
Autor:
Jha, Debesh, Rauniyar, Ashish, Srivastava, Abhiskek, Hagos, Desta Haileselassie, Tomar, Nikhil Kumar, Sharma, Vanshali, Keles, Elif, Zhang, Zheyuan, Demir, Ugur, Topcu, Ahmet, Yazidi, Anis, Håakegård, Jan Erik, Bagci, Ulas
Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by mat
Externí odkaz:
http://arxiv.org/abs/2304.11530
State representation learning aims to capture latent factors of an environment. Contrastive methods have performed better than generative models in previous state representation learning research. Although some researchers realize the connections bet
Externí odkaz:
http://arxiv.org/abs/2303.07437
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. However, a potential challenge i
Externí odkaz:
http://arxiv.org/abs/2210.05165
Autor:
Pontes-Filho, Sidney, Olsen, Kristoffer, Yazidi, Anis, Riegler, Michael A., Halvorsen, Pål, Nichele, Stefano
In this work, we argue that the search for Artificial General Intelligence (AGI) should start from a much lower level than human-level intelligence. The circumstances of intelligent behavior in nature resulted from an organism interacting with its su
Externí odkaz:
http://arxiv.org/abs/2207.13583
Transformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, there have been efforts to adapt transformers to visual tasks of machin
Externí odkaz:
http://arxiv.org/abs/2206.15269