Results 31 to 40 of about 560,544 (271)
Randomized Smoothing for Stochastic Optimization
, 2012 We analyze convergence rates of stochastic optimization procedures for non-smooth convex optimization problems. By combining randomized smoothing techniques with accelerated gradient methods, we obtain convergence rates of stochastic optimization ...
Bartlett, Peter L. +2 more
core +3 more sources
Lyapunov-Guided Energy Scheduling and Computation Offloading for Solar-Powered WSN
Applied Sciences, 2023 To satisfy the continuously high energy consumption and high computational capacity requirements for IoT applications, such as video monitoring, we integrate solar harvesting and multi-access edge computing (MEC) technologies to develop a solar-powered ...
Juan Gao, Runze Wu, Jianhong Hao
doaj +1 more source
Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios
Mathematics, 2020 Simheuristics combine metaheuristics with simulation in order to solve the optimization problems with stochastic elements. This paper introduces the concept of fuzzy simheuristics, which extends the simheuristics approach by making use of fuzzy ...
Diego Oliva +5 more
doaj +1 more source
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Inventory Optimization Model of Biomass Power Plant Considering Multiple Uncertainties
Zhongguo dianliThe formulation of inventory optimization strategies for biomass power plants is the basis for ensuring regional power supply. However, the seasonality and demand uncertainty of biofuels have brought great challenges to inventory optimization.
Jinliang ZHANG, Zeping HU
doaj +1 more source
Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization [PDF]
, 2013 In this paper, we present a new stochastic algorithm, namely the stochastic block mirror descent (SBMD) method for solving large-scale nonsmooth and stochastic optimization problems. The basic idea of this algorithm is to incorporate the block-coordinate
Dang, Cong D., Lan, Guanghui
core
Optimal Stochastic Enhancement of Photoionization [PDF]
Physical Review Letters, 2007 The effect of noise on the nonlinear photoionization of an atom due to a femtosecond pulse is investigated in the framework of the stochastic Schr dinger equation. A modest amount of white noise results in an enhancement of the net ionization yield by several orders of magnitude, giving rise to a form of quantum stochastic resonance.
Singh, K., Rost, J.
openaire +4 more sources
Mutant NPM1 in Acute Myeloid Leukemia Initiation and Maintenance
Aging and Cancer, EarlyView.NPM1 mutations drive acute myeloid leukemia by acting as neomorphic transcriptional regulators that cooperate with Menin–MLL and XPO1 to sustain HOX/MEIS1 expression and block differentiation. Targeting these mutant‐specific transcriptional dependencies provides a rational therapeutic strategy for NPM1‐mutated AML.
Yanan Jiang +3 more
wiley +1 more source
Signal Recovery by Stochastic Optimization [PDF]
Automation and Remote Control, 2019 We discuss an approach to signal recovery in Generalized Linear Models (GLM) in which the signal estimation problem is reduced to the problem of solving a stochastic monotone variational inequality (VI). The solution to the stochastic VI can be found in a computationally efficient way, and in the case when the VI is strongly monotone we derive finite ...
Juditsky, Anatoli, B. +1 more
openaire +3 more sources
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source