Results 81 to 90 of about 67,878 (263)

Stochastic Optimization with Optimal Importance Sampling

open access: yesCoRR
Importance Sampling (IS) is a widely used variance reduction technique for enhancing the efficiency of Monte Carlo methods, particularly in rare-event simulation and related applications. Despite its effectiveness, the performance of IS is highly sensitive to the choice of the proposal distribution and often requires stochastic calibration.
Liviu Aolaritei   +3 more
openaire   +2 more sources

Accelerating Stochastic Composition Optimization

open access: yesJ. Mach. Learn. Res., 2016
Consider the stochastic composition optimization problem where the objective is a composition of two expected-value functions. We propose a new stochastic first-order method, namely the accelerated stochastic compositional proximal gradient (ASC-PG) method, which updates based on queries to the sampling oracle using two different timescales. The ASC-PG
Mengdi Wang 0001   +2 more
openaire   +5 more sources

3D Printing Innovations in Polymeric Porous and Patterned Architecture

open access: yesAdvanced Functional Materials, EarlyView.
Polymeric foams occupy a unique structural space between dense solids and open networks, where engineered void fraction governs mechanical compliance, thermal resistance, and mass transport. Additive manufacturing now enables precise spatial control over cellular architecture, unlocking designer foam structures across applications spanning crash ...
Dhanush Patil   +13 more
wiley   +1 more source

Test data sets for calibration of stochastic and fractional stochastic volatility models

open access: yesData in Brief, 2016
Data for calibration and out-of-sample error testing of option pricing models are provided alongside data obtained from optimization procedures in ''On calibration of stochastic and fractional stochastic volatility models'' [1].
Jan Pospíšil, Tomáš Sobotka
doaj   +1 more source

Template‐Confined Synthesis of Shape‐Engineered Single‐Crystal Gold Microplates in Lithographically‐Defined Polymeric Patterns

open access: yesAdvanced Functional Materials, EarlyView.
Single‐crystal gold microplates are high‐performance nanomaterials with an impressive wafer‐based application space. Progress has, however, been tempered by an inability to exert synthetic control over microplate size, shape, and positioning. In this work, control over these parameters is demonstrated using a seed‐mediated synthesis that both confines ...
Debasish Panda   +9 more
wiley   +1 more source

Electro‐Steric Ion Confinement in Polyelectrolyte Networks for Robust Nonvolatile Artificial Synapse

open access: yesAdvanced Functional Materials, EarlyView.
Polyelectrolyte stoichiometry governs ion transport and retention in electrolyte‐gated synaptic transistors. A PSS‐rich network creates electro‐steric ion confinement that suppresses ion back‐diffusion and stabilizes channel doping, enabling robust nonvolatile synaptic memory, linear weight updates, and low‐energy operation.
Donghwa Lee   +9 more
wiley   +1 more source

Developmental changes in exploration resemble stochastic optimization. [PDF]

open access: yesNat Hum Behav, 2023
Giron AP   +6 more
europepmc   +1 more source

Stochastic simultaneous optimistic optimization

open access: yes, 2013
Published in International Conference on Machine Learning (ICML 2013)
Valko, Michal   +2 more
openaire   +4 more sources

Solution‐Processed Thin‐Film Transistors With Tunable Temporal Dynamics for Neuromorphic Computing

open access: yesAdvanced Functional Materials, EarlyView.
Solution‐processed CNT and CNT/P3HT ion‐gated transistors exhibit materials‐defined synaptic timescales: fast CNT devices for high‐frequency spiking and slow hybrid devices for temporal integration. Embedding these dynamics into coupled reservoir‐computing and spiking neural network simulations reveals that a Hybrid‐Reservoir / CNT‐SNN architecture ...
Kevin Schnittker   +5 more
wiley   +1 more source

Distributionally Robust Optimization Adaptive Event‐Triggered SMPC for DC‐DC Converters Subject to Unknown Disturbances and DoS Attacks

open access: yesIET Power Electronics
In this paper, we present adaptive event‐triggered distributionally robust optimization stochastic model predictive control (AET‐DROSMPC) applied to DC‐DC converters subject to unknown disturbances and denial of service (DoS) attacks.
Yadong Chen, Peng Cheng
doaj   +1 more source

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