Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Ignacio Arnaldo"'
Autor:
Ignacio Arnaldo, Kalyan Veeramachaneni
Publikováno v:
ACM SIGKDD Explorations Newsletter. 21:39-47
Although there is a large corpus of research focused on using machine learning to detect cyber threats, the solutions presented are rarely actually adopted in the real world. In this paper, we discuss the challenges that currently limit the adoption
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e61a55164a863a219d596d3048e6d63
https://doi.org/10.1145/3373464.3373472
https://doi.org/10.1145/3373464.3373472
Publikováno v:
IEEE BigData
We present an automated learning system that continuously gathers domain data from open repositories, develops a deep learning model, uses the model to make detections, publishes unreported malicious domains, leverages threat intelligence to label th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67efc484516b8d0441f6e71e7df4a42e
https://doi.org/10.1109/bigdata.2018.8622197
https://doi.org/10.1109/bigdata.2018.8622197
Publikováno v:
IEEE Computational Intelligence Magazine. 10:20-32
We introduce FCUBE, a cloud-based framework that enables machine learning researchers to contribute their learners to its community-shared repository. FCUBE exploits data parallelism in lieu of algorithmic parallelization to allow its users to effici
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66a599e71e5e8ec0f665d022a1878020
https://doi.org/10.1109/mci.2014.2369892
https://doi.org/10.1109/mci.2014.2369892
Publikováno v:
Journal of Grid Computing. 13:391-407
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f3fc5d3c88b8a2b8672c05e0d986c84
https://doi.org/10.1007/s10723-014-9320-9
https://doi.org/10.1007/s10723-014-9320-9
Publikováno v:
GECCO (Companion)
We introduce a real-world job shop scheduling problem where the objective is to minimize configuration costs that depend on the sliding pairwise similarity between two assets ordered one after the other in a processing batch. This implies that our fu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f09f65ecfbf906dcc1a6f5afe2b69586
https://doi.org/10.1145/2908961.2931647
https://doi.org/10.1145/2908961.2931647
Publikováno v:
BigDataSecurity/HPSC/IDS
We present AI2, an analyst-in-the-loop security system where Analyst Intuition (AI) is put together with state-of-the-art machine learning to build a complete end-to-end Artificially Intelligent solution (AI). The system presents four key features: a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6c92690b01fa66425d03f4442a81d15
https://doi.org/10.1109/bigdatasecurity-hpsc-ids.2016.79
https://doi.org/10.1109/bigdatasecurity-hpsc-ids.2016.79
Autor:
Alfredo Cuesta-Infante, José L. Ayala, J. Manuel Colmenar, José L. Risco-Martín, Ignacio Arnaldo
Publikováno v:
Concurrency and Computation: Practice and Experience. 25:1089-1103
The increasing transistor scale integration poses, among others, the thermal-aware floorplanning problem consisting of how to place the hardware components in order to reduce overheating by dissipation. Because of the huge amount of feasible floorpla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef4a58f06ae6f5e2040c5db61abbd332
https://doi.org/10.1002/cpe.2902
https://doi.org/10.1002/cpe.2902
Publikováno v:
GECCO
We introduce Evolutionary Feature Synthesis (EFS), a regression method that generates readable, nonlinear models of small to medium size datasets in seconds. EFS is, to the best of our knowledge, the fastest regression tool based on evolutionary comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c73994d580ff590f8f85c5947d8bd8e
https://doi.org/10.1145/2739480.2754693
https://doi.org/10.1145/2739480.2754693
Publikováno v:
Memetic Computing.
The ultimate aim of Memetic Computing is the fully autonomous solution to complex optimisation problems. For a while now, the Memetic algorithms literature has been moving in the direction of ever increasing generalisation of optimisers initiated by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5b888d7b0f3fe477abd8dbf9c116702
https://doi.org/10.1007/s12293-014-0145-7
https://doi.org/10.1007/s12293-014-0145-7
Publikováno v:
Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation.
It is our great pleasure to welcome you to the first Workshop on Evolutionary Computation for Big Data and Big Learning ECBDL'14 We live in a time of unprecedented access to cheap and vast amounts of computational resources, which is producing a big
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30a94fdcd9721811b04dbb24dba96524
https://doi.org/10.1145/3250292
https://doi.org/10.1145/3250292