EXPLOITING UNLABELED DATA IN CONCEPT DRIFT LEARNING
Jurnal Informatika, 2007 Learning unlabeled data in a drifting environment still receives little attention. This paper presents a concept tracker algorithm for learning concept drift that exploits unlabeled data.
Dwi Hendratmo Widyantoro
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Biofeedback and Anxiety Disorders: A Critical Review of EMG, EEG, and HRV Feedback [PDF]
, 2015 Anxiety disorders are characterized by ongoing and situationally disproportionate fear and anxiety, and the associated significant distress and impairment of normal functioning (American Psychiatric Association, 2013).
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A context‐dependent modulatory role for eIF6 in acquired resistance to vemurafenib in melanoma
FEBS Letters, EarlyView.Acquired resistance to vemurafenib upregulates the translation factor eIF6 in melanoma cells. Silencing eIF6 in resistant cells reduces proliferation and partially restores drug sensitivity, whereas its overexpression increases sensitivity across melanoma lines regardless of BRAF status, via modulation of mTOR, S6K, and MAPK signaling.
George Kyriakopoulos +9 more
wiley +1 more source
Anomaly Detection and Concept Drift Adaptation for Dynamic Systems: A General Method with Practical Implementation Using an Industrial Collaborative Robot. [PDF]
Sensors (Basel), 2023 Kermenov R +3 more
europepmc +1 more source
Metastatic niche shaped by host factors influences disseminated cancer cell fate
FEBS Letters, EarlyView.Metastasis is shaped not only by cancer cells but also by the environments they encounter. This review explores how factors such as aging, diet, the microbiome, lifestyle, and environmental exposures remodel organ‐specific niches in the lung, liver, bone, and brain, influencing where metastatic cells survive, remain dormant, or grow, and ultimately ...
Gwennan Delyth Ward +2 more
wiley +1 more source
DUCAL: A malware concept drift detection and adaptation method based on active learning
Tongxin xuebaoTo address the performance degradation of malware detection models based on deep learning caused by concept drift, a malicious code concept drift detection and adaptation method based on active learning is proposed.
Liu Qiang +3 more
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AML4S: An AutoML Pipeline for Data Streams
Machine Learning and Knowledge ExtractionThe data landscape has changed, as more and more information is produced in the form of continuous data streams instead of stationary datasets. In this context, several online machine learning techniques have been proposed with the aim of automatically ...
Eleftherios Kalaitzidis +3 more
doaj +1 more source
Adversarial concept drift detection under poisoning attacks for robust data stream mining. [PDF]
Mach Learn, 2022 Korycki Ł, Krawczyk B.
europepmc +1 more source
Letting the Finite Vanish: Hegel, Tillich, and Caputo on the Ontological Philosophy of Religion* [PDF]
, 2015 In general, Kant’s critique of metaphysics still holds up, especially for religious metaphysics. This situation does not necessarily debunk the truth of either position, but it has produced, as Lyotard wrote, a “postmodern condition” defined by ...
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