User profiles for N. Flann
Nicholas S. FlannAssociate Professor of Computer Science, Utah State University Verified email at usu.edu Cited by 2984 |
Parallel genetic simulated annealing: a massively parallel SIMD algorithm
… A block error correction code can be represented as a threetuple, (n, M, d), where n is the
number of bits in each word in a code; M is the number of words in the code; and d is the …
number of bits in each word in a code; M is the number of words in the code; and d is the …
Biocellion : accelerating computer simulation of multicellular biological system models
Motivation: Biological system behaviors are often the outcome of complex interactions among
a large number of cells and their biotic and abiotic environment. Computational biologists …
a large number of cells and their biotic and abiotic environment. Computational biologists …
A six-wheeled omnidirectional autonomous mobile robot
… Flat, connecting the graph through a node N. The Hill-Toe object will start the command
sequence for the edge leaving node N and entering the hill with a spin-in-place command to cor- …
sequence for the edge leaving node N and entering the hill with a spin-in-place command to cor- …
Explanation-based learning and reinforcement learning: A unified view
TG Dietterich, NS Flann - Machine Learning, 1997 - Springer
… In our case, the number of rectangles will be n/ρ, where n is the total number of states in the
state space. The number of visible line segments cut cannot exceed 2ρ. So the time to insert …
state space. The number of visible line segments cut cannot exceed 2ρ. So the time to insert …
[HTML][HTML] Deep reinforcement learning stock market trading, utilizing a CNN with candlestick images
Billions of dollars are traded automatically in the stock market every day, including algorithms
that use neural networks, but there are still questions regarding how neural networks trade. …
that use neural networks, but there are still questions regarding how neural networks trade. …
[PS][PS] Genetic simulated annealing for scheduling data-dependent tasks in heterogeneous environments
… Given: • a set of n tasks which are interdependent and may require transfer of data between
them, denoted as … For the scheduling problem defined in Section 1, the goal is to find an …
them, denoted as … For the scheduling problem defined in Section 1, the goal is to find an …
deepHPI: a comprehensive deep learning platform for accurate prediction and visualization of host–pathogen protein–protein interactions
… *N*1 representation of an amino acid sequence is the input of the network, where M is the
length of the amino acid sequence and N … a dynamic value, which depends on the value of N. …
length of the amino acid sequence and N … a dynamic value, which depends on the value of N. …
A study of explanation-based methods for inductive learning
NS Flann, TG Dietterich - Machine Learning, 1989 - Springer
… Elsewhere, [Flann, 1989], we describe the logical language it employs and the … n that
required less-than-or-equal-to m training examples to obtain correct performance. The quantity n/…
required less-than-or-equal-to m training examples to obtain correct performance. The quantity n/…
Parallel simulated annealing and genetic algorithms: a space of hybrid methods
H Chen, NS Flann - International Conference on Parallel Problem Solving …, 1994 - Springer
… Temperature was then lowered every n function evaluations, where n was set to equal the
population size. The cooling schedule was geometric, where T/+t = aT/ and a set such that the …
population size. The cooling schedule was geometric, where T/+t = aT/ and a set such that the …
Fast design optimization method utilizing a combination of artificial neural networks and genetic algorithms for dynamic inductive power transfer systems
… where n is the number of nodes on the output layer (n = 90), Y is the normalized output
parameters of FEM, and ˆY is the normalized predicted output parameters. Nodes on each hidden …
parameters of FEM, and ˆY is the normalized predicted output parameters. Nodes on each hidden …