Results 41 to 50 of about 569 (214)
Distributionally Robust Language Modeling [PDF]
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019 Language models are generally trained on data spanning a wide range of topics (e.g., news, reviews, fiction), but they might be applied to an a priori unknown target distribution (e.g., restaurant reviews). In this paper, we first show that training on text outside the test distribution can degrade test performance when using standard maximum ...
Yonatan Oren +3 more
openaire +2 more sources
International Journal of Electrical Power & Energy SystemsThe widespread integration of renewable energy sources (RESs) has presented significant challenges in deregulated power markets. The inherent uncertainty of RES poses challenges for clearing cross-temporal and cross-regional transactions, manifesting as ...
Yuhan Huang +6 more
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Distributionally Robust Data Join
CoRR, 2022 Suppose we are given two datasets: a labeled dataset and unlabeled dataset which also has additional auxiliary features not present in the first dataset. What is the most principled way to use these datasets together to construct a predictor? The answer should depend upon whether these datasets are generated by the same or different distributions over ...
Awasthi, Pranjal +2 more
openaire +4 more sources
Energy Reports, 2023 To avoid the problem of insufficient flexibility of the power grid along the cz railway due to source-load fluctuations, a distributionally robust optimization method considering flexibility is proposed in this paper.
Jiawei Liu +5 more
doaj +1 more source
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
DronesThis paper addresses the cooperative task assignment problem for heterogeneous unmanned aerial vehicles with time windows considering uncertain fuel consumption. In the scenario where probabilistic fuel consumption exists and its distribution needs to be
Zhichao Gao +4 more
doaj +1 more source
Energy Reports, 2023 This paper proposes a distributed data-driven distributionally robust volt/var control (DDDR-VVC) approach which schedules on-load-tap changer (OLTC), capacitor banks (CBs) and Photovoltaic (PV) inverters coordinately.
Peishuai Li +4 more
doaj +1 more source
Calpain small subunit homodimerization is robust and calcium‐independent
FEBS Letters, EarlyView.Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy +4 more
wiley +1 more source
Distributionally Robust Optimization with Polynomial Robust Constraints
Journal of Global Optimization25 ...
Jiawang Nie, Suhan Zhong
openaire +3 more sources