1,363 research outputs found
Limit theorems for functionals of long memory linear processes with infinite variance
Let be a long memory linear process in which the
coefficients are regularly varying and innovations are independent and
identically distributed and belong to the domain of attraction of an
-stable law with . Then, for any integrable and
square integrable function on , under certain mild conditions,
we establish the asymptotic distributions of the partial sum as tends to
infinity
DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops
Recommendation models trained on the user feedback collected from deployed
recommendation systems are commonly biased. User feedback is considerably
affected by the exposure mechanism, as users only provide feedback on the items
exposed to them and passively ignore the unexposed items, thus producing
numerous false negative samples. Inevitably, biases caused by such user
feedback are inherited by new models and amplified via feedback loops.
Moreover, the presence of false negative samples makes negative sampling
difficult and introduces spurious information in the user preference modeling
process of the model. Recent work has investigated the negative impact of
feedback loops and unknown exposure mechanisms on recommendation quality and
user experience, essentially treating them as independent factors and ignoring
their cross-effects. To address these issues, we deeply analyze the data
exposure mechanism from the perspective of data iteration and feedback loops
with the Missing Not At Random (\textbf{MNAR}) assumption, theoretically
demonstrating the existence of an available stabilization factor in the
transformation of the exposure mechanism under the feedback loops. We further
propose Dynamic Personalized Ranking (\textbf{DPR}), an unbiased algorithm that
uses dynamic re-weighting to mitigate the cross-effects of exposure mechanisms
and feedback loops without additional information. Furthermore, we design a
plugin named Universal Anti-False Negative (\textbf{UFN}) to mitigate the
negative impact of the false negative problem. We demonstrate theoretically
that our approach mitigates the negative effects of feedback loops and unknown
exposure mechanisms. Experimental results on real-world datasets demonstrate
that models using DPR can better handle bias accumulation and the universality
of UFN in mainstream loss methods
Case studies of two related Chinese patients with Carney complex presenting with extensive cardiac myxomas and PRKAR1A gene mutation of c.491_492delTG
Future cereal production in China: Modelling the interaction of climate change, water availability and socio-economic scenarios. The Impacts of Climate Change on Chinese Agriculture – Phase II Final Report
Effect of combined sedation using multiple drugs on inflammatory cytokines in patients with acute respiratory distress syndrome
The innate immune response plays an important role in the pathophysiology of acute respiratory distress syndrome (ARDS); however, no drug has been proven to be beneficial in the management of ARDS. Therefore, the aim of this study was to investigate the effects of using combined sedatives on systemic inflammatory responses in patients with ARDS. A total of 90 patients with ARDS and an intubation time of > 120 h were randomly divided into the propofol group (group P), midazolam group (group M), and combined sedation group (group U). Patients in groups P and M were sedated with propofol and midazolam, respectively, whereas patients in group U were sedated with a combination of propofol, midazolam, and dexmedetomidine. The dosage of sedatives and vasoactive drugs, duration of mechanical ventilation, and incidence of sedative adverse reactions were documented. The dosage of sedatives and vasoactive drugs, as well as the incidence of sedative adverse reactions in group U, was significantly lower than those in groups P and M. Similarly, the duration of mechanical ventilation in group U was significantly shorter than that in groups P and M. Hence, inducing sedation through a combination of multiple drugs can significantly reduce their adverse effects, improve their sedative effect, inhibit systemic inflammatory responses, and improve oxygenation in patients with ARDS
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