Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Wicker, Jörg"'
Publikováno v:
Artif Intell Rev 57, 296 (2024)
Aspect-based sentiment analysis (ABSA) is a fine-grained type of sentiment analysis that identifies aspects and their associated opinions from a given text. With the surge of digital opinionated text data, ABSA gained increasing popularity for its ab
Externí odkaz:
http://arxiv.org/abs/2311.10777
The performance of machine learning models depends on the quality of the underlying data. Malicious actors can attack the model by poisoning the training data. Current detectors are tied to either specific data types, models, or attacks, and therefor
Externí odkaz:
http://arxiv.org/abs/2310.16224
Machine learning models are increasingly used in fields that require high reliability such as cybersecurity. However, these models remain vulnerable to various attacks, among which the adversarial label-flipping attack poses significant threats. In l
Externí odkaz:
http://arxiv.org/abs/2310.10744
Autor:
Pullar-Strecker, Zac, Chang, Xinglong, Brydon, Liam, Ziogas, Ioannis, Dost, Katharina, Wicker, Jörg
Running complex sets of machine learning experiments is challenging and time-consuming due to the lack of a unified framework. This leaves researchers forced to spend time implementing necessary features such as parallelization, caching, and checkpoi
Externí odkaz:
http://arxiv.org/abs/2304.09175
In Simultaneous Localization and Mapping (SLAM), Loop Closure Detection (LCD) is essential to minimize drift when recognizing previously visited places. Visual Bag-of-Words (vBoW) has been an LCD algorithm of choice for many state-of-the-art SLAM sys
Externí odkaz:
http://arxiv.org/abs/2209.11894
SymbioLCD: Ensemble-Based Loop Closure Detection using CNN-Extracted Objects and Visual Bag-of-Words
Loop closure detection is an essential tool of Simultaneous Localization and Mapping (SLAM) to minimize drift in its localization. Many state-of-the-art loop closure detection (LCD) algorithms use visual Bag-of-Words (vBoW), which is robust against p
Externí odkaz:
http://arxiv.org/abs/2110.11491
Active learning allows machine learning models to be trained using fewer labels while retaining similar performance to traditional supervised learning. An active learner selects the most informative data points, requests their labels, and retrains it
Externí odkaz:
http://arxiv.org/abs/2110.03802
Autor:
Chang, Xinglong, Dost, Katharina, Zhao, Kaiqi, Demontis, Ambra, Roli, Fabio, Dobbie, Gill, Wicker, Jörg
Publikováno v:
PAKDD,2023,3-14
Adversarial defenses protect machine learning models from adversarial attacks, but are often tailored to one type of model or attack. The lack of information on unknown potential attacks makes detecting adversarial examples challenging. Additionally,
Externí odkaz:
http://arxiv.org/abs/2105.00495
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Akademický článek
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