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In the first part, I shall present a new way to construct highly stiff stable schemes. Traditional time discretization schemes are usually based on Taylor expansions at $t_{n+\beta}$ with $\beta\in [0...
Modern neural networks are usually over-parameterized—the number of parameters exceeds the number of training data. In this case the loss functions tend to have many (or even infinite) global minima, ...
The Simulation Optimization track focuses on algorithms that can be coupled with computer simulations to locate specific input parameter values for the simulation that maximize or minimize a simulatio...
Locating the boundary parameters of pupil and iris and segmenting the noise free iris portion are the most challenging phases of an automated iris recognition system. In this paper, we have presented ...
This OptMAS workshop invites works from different strands of the multi-agent systems community that pertain to the design of algorithms, models, and techniques to deal with multi-agent optimization pr...
Wireless communication networks composed of devices that can harvest energy from nature will lead to the green future of wireless, as energy harvesting offers the possibility of perpetual network oper...
Establishing low-carbon, efficient, safe and sustainable energy utilization mode to meet national economic and social development and environmental requirements is an important issue that should be so...
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
Traditionally storage has not been part of a programming model’s semantics and is added only as an I/O library interface.
The optimization of short sequences of loop-free, fixed-point assembly code sequences is an important problem in highperformance computing. However, the competing constraints of transformation correct...
The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (G...
Background: Basic fibroblast growth factor (bFGF) is a member of a highly conserved superfamily of proteins that are involved in cell proliferation, differentiation, and migration. Objectives: The ob...
We study several stochastic combinatorial problems, includ-ing the expected utility maximization problem, the stochas-tic knapsack problem and the stochastic bin packing prob-lem. A common technical c...
In this paper, we investigate the power of online learning in stochastic network optimization with unknown system statistics a priori. We are interested in understanding how information and learning c...
We consider the stochastic geometry model where the location of each node is a random point in a given metric space,or the existence of each node is uncertain. We study the problem-s of computing the ...

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