Results 81 to 90 of about 67,878 (263)
Stochastic Optimization with Optimal Importance Sampling
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
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
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
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
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
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]
Giron AP +6 more
europepmc +1 more source
Stochastic simultaneous optimistic optimization
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
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
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

