Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Dutra, Ines"'
Semantic segmentation is a fundamental computer vision task with a vast number of applications. State of the art methods increasingly rely on deep learning models, known to incorrectly estimate uncertainty and being overconfident in predictions, espe
Externí odkaz:
http://arxiv.org/abs/2407.12609
The Abstraction and Reasoning Corpus (ARC) is a general artificial intelligence benchmark that is currently unsolvable by any Machine Learning method, including Large Language Models (LLMs). It demands strong generalization and reasoning capabilities
Externí odkaz:
http://arxiv.org/abs/2405.06399
Intrusion Tolerant Systems (ITSs) are a necessary component for cyber-services/infrastructures. Additionally, as cyberattacks follow a multi-domain attack surface, a similar defensive approach should be applied, namely, the use of an evolving multi-d
Externí odkaz:
http://arxiv.org/abs/2311.09449
Autonomous driving has become one of the most popular research topics within Artificial Intelligence. An autonomous vehicle is understood as a system that combines perception, decision-making, planning, and control. All of those tasks require that th
Externí odkaz:
http://arxiv.org/abs/2305.19421
Six years after the seminal paper on FAIR was published, researchers still struggle to understand how to implement FAIR. For many researchers FAIR promises long-term benefits for near-term effort, requires skills not yet acquired, and is one more thi
Externí odkaz:
http://arxiv.org/abs/2301.10236
Motivation: Traditional computational cluster schedulers are based on user inputs and run time needs request for memory and CPU, not IO. Heavily IO bound task run times, like ones seen in many big data and bioinformatics problems, are dependent on th
Externí odkaz:
http://arxiv.org/abs/1812.09537
Quantum computers are different from binary digital electronic computers based on transistors. Common digital computing encodes the data into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation us
Externí odkaz:
http://arxiv.org/abs/1808.08429
Publikováno v:
SAC '15 Proceedings of the 30th Annual ACM Symposium on Applied Computing Pages 879-884 ACM New York, NY, USA
We describe GPU implementations of the matrix recommender algorithms CCD++ and ALS. We compare the processing time and predictive ability of the GPU implementations with existing multi-core versions of the same algorithms. Results on the GPU are bett
Externí odkaz:
http://arxiv.org/abs/1511.02433
Probabilistic Inductive Logic Programming (PILP) is a rel- atively unexplored area of Statistical Relational Learning which extends classic Inductive Logic Programming (ILP). This work introduces SkILL, a Stochastic Inductive Logic Learner, which tak
Externí odkaz:
http://arxiv.org/abs/1506.00893
Autor:
Almeida, Ezilda, Ferreira, Pedro, Vinhoza, Tiago, Dutra, Inês, Li, Jingwei, Wu, Yirong, Burnside, Elizabeth
Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be auto
Externí odkaz:
http://arxiv.org/abs/1406.2395