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35,004 | Memcomputing with membrane memcapacitive systems | cs.ET | We show theoretically that networks of membrane memcapacitive systems --
capacitors with memory made out of membrane materials -- can be used to perform
a complete set of logic gates in a massively parallel way by simply changing
the external input amplitudes, but not the topology of the network. This
polymorphism is a... | computer science |
35,005 | A Fast Hybrid Primal Heuristic for Multiband Robust Capacitated Network
Design with Multiple Time Periods | math.OC | We investigate the Robust Multiperiod Network Design Problem, a
generalization of the Capacitated Network Design Problem (CNDP) that, besides
establishing flow routing and network capacity installation as in a canonical
CNDP, also considers a planning horizon made up of multiple time periods and
protection against fluc... | computer science |
35,006 | Trade-Offs in Exploiting Body Morphology for Control: from Simple Bodies
and Model-Based Control to Complex Bodies with Model-Free Distributed Control
Schemes | cs.RO | Tailoring the design of robot bodies for control purposes is implicitly
performed by engineers, however, a methodology or set of tools is largely
absent and optimization of morphology (shape, material properties of robot
bodies, etc.) is lagging behind the development of controllers. This has become
even more prominent... | computer science |
35,007 | Scalability and Optimization Strategies for GPU Enhanced Neural Networks
(GeNN) | cs.DC | Simulation of spiking neural networks has been traditionally done on
high-performance supercomputers or large-scale clusters. Utilizing the parallel
nature of neural network computation algorithms, GeNN (GPU Enhanced Neural
Network) provides a simulation environment that performs on General Purpose
NVIDIA GPUs with a c... | computer science |
35,008 | The inductive theory of natural selection: summary and synthesis | cs.NE | The theory of natural selection has two forms. Deductive theory describes how
populations change over time. One starts with an initial population and some
rules for change. From those assumptions, one calculates the future state of
the population. Deductive theory predicts how populations adapt to
environmental challen... | computer science |
35,009 | Optimization of Reliability of Network of Given Connectivity using
Genetic Algorithm | cs.NE | Reliability is one of the important measures of how well the system meets its
design objective, and mathematically is the probability that a system will
perform satisfactorily for at least a given period of time. When the system is
described by a connected network of N components (nodes) and their L connection
(links),... | computer science |
35,010 | Spread Unary Coding | cs.NE | Unary coding is useful but it is redundant in its standard form. Unary coding
can also be seen as spatial coding where the value of the number is determined
by its place in an array. Motivated by biological finding that several neurons
in the vicinity represent the same number, we propose a variant of unary
numeration ... | computer science |
35,011 | Hierarchical Composition of Memristive Networks for Real-Time Computing | cs.ET | Advances in materials science have led to physical instantiations of
self-assembled networks of memristive devices and demonstrations of their
computational capability through reservoir computing. Reservoir computing is an
approach that takes advantage of collective system dynamics for real-time
computing. A dynamical ... | computer science |
35,012 | Incorporating Road Networks into Territory Design | math.OC | Given a set of basic areas, the territory design problem asks to create a
predefined number of territories, each containing at least one basic area, such
that an objective function is optimized. Desired properties of territories
often include a reasonable balance, compact form, contiguity and small average
journey time... | computer science |
35,013 | Programs as Polypeptides | cs.NE | We describe a visual programming language for defining behaviors manifested
by reified actors in a 2D virtual world that can be compiled into programs
comprised of sequences of combinators that are themselves reified as actors.
This makes it possible to build programs that build programs from components of
a few fixed ... | computer science |
35,014 | A Scheme for Molecular Computation of Maximum Likelihood Estimators for
Log-Linear Models | cs.NE | We propose a novel molecular computing scheme for statistical inference. We
focus on the much-studied statistical inference problem of computing maximum
likelihood estimators for log-linear models. Our scheme takes log-linear models
to reaction systems, and the observed data to initial conditions, so that the
correspon... | computer science |
35,015 | Distributed Recurrent Neural Forward Models with Synaptic Adaptation for
Complex Behaviors of Walking Robots | cs.NE | Walking animals, like stick insects, cockroaches or ants, demonstrate a
fascinating range of locomotive abilities and complex behaviors. The locomotive
behaviors can consist of a variety of walking patterns along with adaptation
that allow the animals to deal with changes in environmental conditions, like
uneven terrai... | computer science |
35,016 | Quantitative evaluation of the performance of discrete-time reservoir
computers in the forecasting, filtering, and reconstruction of stochastic
stationary signals | cs.ET | This paper extends the notion of information processing capacity for
non-independent input signals in the context of reservoir computing (RC). The
presence of input autocorrelation makes worthwhile the treatment of forecasting
and filtering problems for which we explicitly compute this generalized
capacity as a functio... | computer science |
35,017 | Particle Swarm Optimization for Weighted Sum Rate Maximization in MIMO
Broadcast Channels | cs.IT | In this paper, we investigate the downlink multiple-input-multipleoutput
(MIMO) broadcast channels in which a base transceiver station (BTS) broadcasts
multiple data streams to K MIMO mobile stations (MSs) simultaneously. In order
to maximize the weighted sum-rate (WSR) of the system subject to the
transmitted power co... | computer science |
35,018 | Financial Market Modeling with Quantum Neural Networks | cs.NE | Econophysics has developed as a research field that applies the formalism of
Statistical Mechanics and Quantum Mechanics to address Economics and Finance
problems. The branch of Econophysics that applies of Quantum Theory to
Economics and Finance is called Quantum Econophysics. In Finance, Quantum
Econophysics' contrib... | computer science |
35,019 | Using Genetic Algorithms to Benchmark the Cloud | cs.DC | This paper presents a novel application of Genetic Algorithms(GAs) to
quantify the performance of Platform as a Service (PaaS), a cloud service model
that plays a critical role in both industry and academia. While Cloud
benchmarks are not new, in this novel concept, the authors use a GA to take
advantage of the elastic... | computer science |
35,020 | Continuous parameter working memory in a balanced chaotic neural network | cs.NE | It has been proposed that neural noise in the cortex arises from chaotic
dynamics in the balanced state: in this model of cortical dynamics, the
excitatory and inhibitory inputs to each neuron approximately cancel, and
activity is driven by fluctuations of the synaptic inputs around their mean. It
remains unclear wheth... | computer science |
35,021 | Pure and Hybrid Evolutionary Computing in Global Optimization of
Chemical Structures: from Atoms and Molecules to Clusters and Crystals | cs.NE | The growth of evolutionary computing (EC) methods in the exploration of
complex potential energy landscapes of atomic and molecular clusters, as well
as crystals over the last decade or so is reviewed. The trend of growth
indicates that pure as well as hybrid evolutionary computing techniques in
conjunction of DFT has ... | computer science |
35,022 | Finding Near-Optimal Independent Sets at Scale | cs.DS | The independent set problem is NP-hard and particularly difficult to solve in
large sparse graphs. In this work, we develop an advanced evolutionary
algorithm, which incorporates kernelization techniques to compute large
independent sets in huge sparse networks. A recent exact algorithm has shown
that large networks ca... | computer science |
35,023 | Single Memristor Logic Gates: From NOT to a Full Adder | cs.ET | Memristors have been suggested as a novel route to neuromorphic computing
based on the similarity between them and neurons (specifically synapses and ion
pumps). The d.c. action of the memristor is a current spike which imparts a
short-term memory to the device. Here it is demonstrated that this short-term
memory works... | computer science |
35,024 | Limiting fitness distributions in evolutionary dynamics | cs.NE | Darwinian evolution can be modeled in general terms as a flow in the space of
fitness (i.e. reproductive rate) distributions. In the diffusion approximation,
Tsimring et al. have showed that this flow admits "fitness wave" solutions:
Gaussian-shape fitness distributions moving towards higher fitness values at
constant ... | computer science |
35,025 | Toward Biochemical Probabilistic Computation | cs.ET | Living organisms survive and multiply even though they have uncertain and
incomplete information about their environment and imperfect models to predict
the consequences of their actions. Bayesian models have been proposed to face
this challenge. Indeed, Bayesian inference is a way to do optimal reasoning
when only unc... | computer science |
35,026 | A biologically constrained model of the whole basal ganglia addressing
the paradoxes of connections and selection | cs.NE | The basal ganglia nuclei form a complex network of nuclei often assumed to
perform selection, yet their individual roles and how they influence each other
is still largely unclear. In particular, the ties between the external and
internal parts of the globus pallidus are paradoxical, as anatomical data
suggest a potent... | computer science |
35,027 | Stochastic Interpretation of Quasi-periodic Event-based Systems | cs.NE | Many networks used in machine learning and as models of biological neural
networks make use of stochastic neurons or neuron-like units. We show that
stochastic artificial neurons can be realized on silicon chips by exploiting
the quasi-periodic behavior of mismatched analog oscillators to approximate the
neuron's stoch... | computer science |
35,028 | Inferring Gene Regulatory Network Using An Evolutionary Multi-Objective
Method | cs.CE | Inference of gene regulatory networks (GRNs) based on experimental data is a
challenging task in bioinformatics. In this paper, we present a bi-objective
minimization model (BoMM) for inference of GRNs, where one objective is the
fitting error of derivatives, and the other is the number of connections in the
network. T... | computer science |
35,029 | Differential Evolution with Event-Triggered Impulsive Control | cs.NE | Differential evolution (DE) is a simple but powerful evolutionary algorithm,
which has been widely and successfully used in various areas. In this paper, an
event-triggered impulsive control scheme (ETI) is introduced to improve the
performance of DE. Impulsive control, the concept of which derives from control
theory,... | computer science |
35,030 | Interacting Behavior and Emerging Complexity | cs.NE | Can we quantify the change of complexity throughout evolutionary processes?
We attempt to address this question through an empirical approach. In very
general terms, we simulate two simple organisms on a computer that compete over
limited available resources. We implement Global Rules that determine the
interaction bet... | computer science |
35,031 | A single hidden layer feedforward network with only one neuron in the
hidden layer can approximate any univariate function | cs.NE | The possibility of approximating a continuous function on a compact subset of
the real line by a feedforward single hidden layer neural network with a
sigmoidal activation function has been studied in many papers. Such networks
can approximate an arbitrary continuous function provided that an unlimited
number of neuron... | computer science |
35,032 | Scalability in Neural Control of Musculoskeletal Robots | cs.RO | Anthropomimetic robots are robots that sense, behave, interact and feel like
humans. By this definition, anthropomimetic robots require human-like physical
hardware and actuation, but also brain-like control and sensing. The most
self-evident realization to meet those requirements would be a human-like
musculoskeletal ... | computer science |
35,033 | An Evolutionary Strategy based on Partial Imitation for Solving
Optimization Problems | cs.NE | In this work we introduce an evolutionary strategy to solve combinatorial
optimization tasks, i.e. problems characterized by a discrete search space. In
particular, we focus on the Traveling Salesman Problem (TSP), i.e. a famous
problem whose search space grows exponentially, increasing the number of
cities, up to beco... | computer science |
35,034 | Evolving Boolean Regulatory Networks with Variable Gene Expression Times | cs.NE | The time taken for gene expression varies not least because proteins vary in
length considerably. This paper uses an abstract, tuneable Boolean regulatory
network model to explore gene expression time variation. In particular, it is
shown how non-uniform expression times can emerge under certain conditions
through simu... | computer science |
35,035 | Performance Localisation | cs.SE | Performance becomes an issue particularly when execution cost hinders the
functionality of a program. Typically a profiler can be used to find program
code execution which represents a large portion of the overall execution cost
of a program. Pinpointing where a performance issue exists provides a starting
point for tr... | computer science |
35,036 | A Discontinuous Neural Network for Non-Negative Sparse Approximation | cs.NE | This paper investigates a discontinuous neural network which is used as a
model of the mammalian olfactory system and can more generally be applied to
solve non-negative sparse approximation problems. By inherently limiting the
systems integrators to having non-negative outputs, the system function becomes
discontinuou... | computer science |
35,037 | Analyzing coevolutionary games with dynamic fitness landscapes | cs.GT | Coevolutionary games cast players that may change their strategies as well as
their networks of interaction. In this paper a framework is introduced for
describing coevolutionary game dynamics by landscape models. It is shown that
coevolutionary games invoke dynamic landscapes. Numerical experiments are shown
for a pri... | computer science |
35,038 | Boda-RTC: Productive Generation of Portable, Efficient Code for
Convolutional Neural Networks on Mobile Computing Platforms | cs.DC | The popularity of neural networks (NNs) spans academia, industry, and popular
culture. In particular, convolutional neural networks (CNNs) have been applied
to many image based machine learning tasks and have yielded strong results. The
availability of hardware/software systems for efficient training and deployment
of ... | computer science |
35,039 | Collective Decision Dynamics in Group Evacuation: Behavioral Experiment
and Machine Learning Models | cs.NE | Identifying factors that affect human decision making and quantifying their
influence remain essential and challenging tasks for the design and
implementation of social and technological communication systems. We report
results of a behavioral experiment involving decision making in the face of an
impending natural dis... | computer science |
35,040 | Minimum cost polygon overlay with rectangular shape stock panels | cs.NE | Minimum Cost Polygon Overlay (MCPO) is a unique two-dimensional optimization
problem that involves the task of covering a polygon shaped area with a series
of rectangular shaped panels. This has a number of applications in the
construction industry. This work examines the MCPO problem in order to
construct a model that... | computer science |
35,041 | Multi-Objective Design of State Feedback Controllers Using Reinforced
Quantum-Behaved Particle Swarm Optimization | cs.NE | In this paper, a novel and generic multi-objective design paradigm is
proposed which utilizes quantum-behaved PSO(QPSO) for deciding the optimal
configuration of the LQR controller for a given problem considering a set of
competing objectives. There are three main contributions introduced in this
paper as follows. (1) ... | computer science |
35,042 | Escaping Local Optima using Crossover with Emergent or Reinforced
Diversity | cs.NE | Population diversity is essential for avoiding premature convergence in
Genetic Algorithms (GAs) and for the effective use of crossover. Yet the
dynamics of how diversity emerges in populations are not well understood. We
use rigorous runtime analysis to gain insight into population dynamics and GA
performance for the ... | computer science |
35,043 | Drift Analysis and Evolutionary Algorithms Revisited | math.CO | One of the easiest randomized greedy optimization algorithms is the following
evolutionary algorithm which aims at maximizing a boolean function $f:\{0,1\}^n
\to {\mathbb R}$. The algorithm starts with a random search point $\xi \in
\{0,1\}^n$, and in each round it flips each bit of $\xi$ with probability $c/n$
indepen... | computer science |
35,044 | Dopamine modulation of prefrontal delay activity-reverberatory activity
and sharpness of tuning curves | cs.NE | Recent electrophysiological experiments have shown that dopamine (D1)
modulation of pyramidal cells in prefrontal cortex reduces spike frequency
adaptation and enhances NMDA transmission. Using four models, from
multicompartmental to integrate and fire, we examine the effects of these
modulations on sustained (delay) a... | computer science |
35,045 | Simulation of an Optional Strategy in the Prisoner's Dilemma in Spatial
and Non-spatial Environments | cs.GT | This paper presents research comparing the effects of different environments
on the outcome of an extended Prisoner's Dilemma, in which agents have the
option to abstain from playing the game. We consider three different pure
strategies: cooperation, defection and abstinence. We adopt an evolutionary
game theoretic app... | computer science |
35,046 | Evolutionary Approaches to Optimization Problems in Chimera Topologies | cs.NE | Chimera graphs define the topology of one of the first commercially available
quantum computers. A variety of optimization problems have been mapped to this
topology to evaluate the behavior of quantum enhanced optimization heuristics
in relation to other optimizers, being able to efficiently solve problems
classically... | computer science |
35,047 | Neural Networks and Chaos: Construction, Evaluation of Chaotic Networks,
and Prediction of Chaos with Multilayer Feedforward Networks | cs.NE | Many research works deal with chaotic neural networks for various fields of
application. Unfortunately, up to now these networks are usually claimed to be
chaotic without any mathematical proof. The purpose of this paper is to
establish, based on a rigorous theoretical framework, an equivalence between
chaotic iteratio... | computer science |
35,048 | Applying Topological Persistence in Convolutional Neural Network for
Music Audio Signals | cs.NE | Recent years have witnessed an increased interest in the application of
persistent homology, a topological tool for data analysis, to machine learning
problems. Persistent homology is known for its ability to numerically
characterize the shapes of spaces induced by features or functions. On the
other hand, deep neural ... | computer science |
35,049 | Magnetic skyrmion-based synaptic devices | cs.ET | Magnetic skyrmions are promising candidates for next-generation information
carriers, owing to their small size, topological stability, and ultralow
depinning current density. A wide variety of skyrmionic device concepts and
prototypes have been proposed, highlighting their potential applications. Here,
we report on a ... | computer science |
35,050 | The Optional Prisoner's Dilemma in a Spatial Environment: Coevolving
Game Strategy and Link Weights | cs.NE | In this paper, the Optional Prisoner's Dilemma game in a spatial environment,
with coevolutionary rules for both the strategy and network links between
agents, is studied. Using a Monte Carlo simulation approach, a number of
experiments are performed to identify favourable configurations of the
environment for the emer... | computer science |
35,051 | Using CMA-ES for tuning coupled PID controllers within models of
combustion engines | cs.SY | Proportional integral derivative (PID) controllers are important and widely
used tools in system control. Tuning of the controller gains is a laborious
task, especially for complex systems such as combustion engines. To minimize
the time of an engineer for tuning of the gains in a simulation software, we
propose to for... | computer science |
35,052 | Quantum Neural Machine Learning - Backpropagation and Dynamics | cs.NE | The current work addresses quantum machine learning in the context of Quantum
Artificial Neural Networks such that the networks' processing is divided in two
stages: the learning stage, where the network converges to a specific quantum
circuit, and the backpropagation stage where the network effectively works as a
self... | computer science |
35,053 | Multi-Output Artificial Neural Network for Storm Surge Prediction in
North Carolina | cs.NE | During hurricane seasons, emergency managers and other decision makers need
accurate and `on-time' information on potential storm surge impacts. Fully
dynamical computer models, such as the ADCIRC tide, storm surge, and wind-wave
model take several hours to complete a forecast when configured at high spatial
resolution... | computer science |
35,054 | Training a Probabilistic Graphical Model with Resistive Switching
Electronic Synapses | cs.NE | Current large scale implementations of deep learning and data mining require
thousands of processors, massive amounts of off-chip memory, and consume
gigajoules of energy. Emerging memory technologies such as nanoscale
two-terminal resistive switching memory devices offer a compact, scalable and
low power alternative t... | computer science |
35,055 | Superconducting optoelectronic circuits for neuromorphic computing | cs.NE | Neural networks have proven effective for solving many difficult
computational problems. Implementing complex neural networks in software is
very computationally expensive. To explore the limits of information
processing, it will be necessary to implement new hardware platforms with large
numbers of neurons, each with ... | computer science |
35,056 | Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing
Winner-Take-All Networks | cs.NE | We initiate a line of investigation into biological neural networks from an
algorithmic perspective. We develop a simplified but biologically plausible
model for distributed computation in stochastic spiking neural networks and
study tradeoffs between computation time and network complexity in this model.
Our aim is to... | computer science |
35,057 | Operational calculus on programming spaces | cs.FL | In this paper we develop operational calculus on programming spaces that
generalizes existing approaches to automatic differentiation of computer
programs and provides a rigorous framework for program analysis through
calculus.
We present an abstract computing machine that models automatically
differentiable computer... | computer science |
35,058 | Neuromorphic Silicon Photonic Networks | cs.NE | Photonic systems for high-performance information processing have attracted
renewed interest. Neuromorphic silicon photonics has the potential to integrate
processing functions that vastly exceed the capabilities of electronics. We
report first observations of a recurrent silicon photonic neural network, in
which conne... | computer science |
35,059 | A Metaprogramming and Autotuning Framework for Deploying Deep Learning
Applications | cs.NE | In recent years, deep neural networks (DNNs), have yielded strong results on
a wide range of applications. Graphics Processing Units (GPUs) have been one
key enabling factor leading to the current popularity of DNNs. However, despite
increasing hardware flexibility and software programming toolchain maturity,
high effi... | computer science |
35,060 | dMath: Distributed Linear Algebra for DL | cs.DC | The paper presents a parallel math library, dMath, that demonstrates leading
scaling when using intranode, internode, and hybrid-parallelism for deep
learning (DL). dMath provides easy-to-use distributed primitives and a variety
of domain-specific algorithms including matrix multiplication, convolutions,
and others all... | computer science |
35,061 | Dynamic landscape models of coevolutionary games | cs.NE | Players of coevolutionary games may update not only their strategies but also
their networks of interaction. Based on interpreting the payoff of players as
fitness, dynamic landscape models are proposed. The modeling procedure is
carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use
either birt... | computer science |
35,062 | Fractional Order Load-Frequency Control of Interconnected Power Systems
Using Chaotic Multi-objective Optimization | math.OC | Fractional order proportional-integral-derivative (FOPID) controllers are
designed for load frequency control (LFC) of two interconnected power systems.
Conflicting time domain design objectives are considered in a multi objective
optimization (MOO) based design framework to design the gains and the
fractional differ-i... | computer science |
35,063 | Source localization in an ocean waveguide using supervised machine
learning | cs.NE | Source localization in ocean acoustics is posed as a machine learning problem
in which data-driven methods learn source ranges directly from observed
acoustic data. The pressure received by a vertical linear array is preprocessed
by constructing a normalized sample covariance matrix (SCM) and used as the
input. Three m... | computer science |
35,064 | Scaling Properties of Human Brain Functional Networks | cs.NE | We investigate scaling properties of human brain functional networks in the
resting-state. Analyzing network degree distributions, we statistically test
whether their tails scale as power-law or not. Initial studies, based on
least-squares fitting, were shown to be inadequate for precise estimation of
power-law distrib... | computer science |
35,065 | Distributed Evolutionary k-way Node Separators | cs.NE | Computing high quality node separators in large graphs is necessary for a
variety of applications, ranging from divide-and-conquer algorithms to VLSI
design. In this work, we present a novel distributed evolutionary algorithm
tackling the k-way node separator problem. A key component of our contribution
includes new k-... | computer science |
35,066 | Differential Evolution for Quantum Robust Control: Algorithm,
Applications and Experiments | cs.NE | Robust control design for quantum systems has been recognized as a key task
in quantum information technology, molecular chemistry and atomic physics. In
this paper, an improved differential evolution algorithm of msMS_DE is proposed
to search robust fields for various quantum control problems. In msMS_DE,
multiple sam... | computer science |
35,067 | The Causal Role of Astrocytes in Slow-Wave Rhythmogenesis: A
Computational Modelling Study | cs.NE | Finding the origin of slow and infra-slow oscillations could reveal or
explain brain mechanisms in health and disease. Here, we present a
biophysically constrained computational model of a neural network where the
inclusion of astrocytes introduced slow and infra-slow-oscillations, through
two distinct mechanisms. Spec... | computer science |
35,068 | Control of the Correlation of Spontaneous Neuron Activity in Biological
and Noise-activated CMOS Artificial Neural Microcircuits | cs.NE | There are several indications that brain is organized not on a basis of
individual unreliable neurons, but on a micro-circuital scale providing Lego
blocks employed to create complex architectures. At such an intermediate scale,
the firing activity in the microcircuits is governed by collective effects
emerging by the ... | computer science |
35,069 | A norm knockout method on indirect reciprocity to reveal indispensable
norms | cs.MA | Although various norms for reciprocity-based cooperation have been suggested
that are evolutionarily stable against invasion from free riders, the process
of alternation of norms and the role of diversified norms remain unclear in the
evolution of cooperation. We clarify the co-evolutionary dynamics of norms and
cooper... | computer science |
35,070 | Non-Associative Learning Representation in the Nervous System of the
Nematode Caenorhabditis elegans | cs.NE | Caenorhabditis elegans (C. elegans) illustrated remarkable behavioral
plasticities including complex non-associative and associative learning
representations. Understanding the principles of such mechanisms presumably
leads to constructive inspirations for the design of efficient learning
algorithms. In the present stu... | computer science |
35,071 | Approximating Optimization Problems using EAs on Scale-Free Networks | cs.DS | It has been experimentally observed that real-world networks follow certain
topological properties, such as small-world, power-law etc. To study these
networks, many random graph models, such as Preferential Attachment, have been
proposed.
In this paper, we consider the deterministic properties which capture
power-la... | computer science |
35,072 | A fast ILP-based Heuristic for the robust design of Body Wireless Sensor
Networks | math.OC | We consider the problem of optimally designing a body wireless sensor
network, while taking into account the uncertainty of data generation of
biosensors. Since the related min-max robustness Integer Linear Programming
(ILP) problem can be difficult to solve even for state-of-the-art commercial
optimization solvers, we... | computer science |
35,073 | A hybrid CPU-GPU parallelization scheme of variable neighborhood search
for inventory optimization problems | cs.NE | In this paper, we study various parallelization schemes for the Variable
Neighborhood Search (VNS) metaheuristic on a CPU-GPU system via OpenMP and
OpenACC. A hybrid parallel VNS method is applied to recent benchmark problem
instances for the multi-product dynamic lot sizing problem with product returns
and recovery, w... | computer science |
35,074 | A hybrid exact-ACO algorithm for the joint scheduling, power and cluster
assignment in cooperative wireless networks | math.OC | Base station cooperation (BSC) has recently arisen as a promising way to
increase the capacity of a wireless network. Implementing BSC adds a new design
dimension to the classical wireless network design problem: how to define the
subset of base stations (clusters) that coordinate to serve a user. Though the
problem of... | computer science |
35,075 | A hybrid primal heuristic for Robust Multiperiod Network Design | math.OC | We investigate the Robust Multiperiod Network Design Problem, a
generalization of the classical Capacitated Network Design Problem that
additionally considers multiple design periods and provides solutions protected
against traffic uncertainty. Given the intrinsic difficulty of the problem,
which proves challenging eve... | computer science |
35,076 | An evolutionary strategy for DeltaE - E identification | cs.NE | In this article we present an automatic method for charge and mass
identification of charged nuclear fragments produced in heavy ion collisions at
intermediate energies. The algorithm combines a generative model of DeltaE - E
relation and a Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES). The
CMA-ES is a st... | computer science |
35,077 | Neuro-RAM Unit with Applications to Similarity Testing and Compression
in Spiking Neural Networks | cs.NE | We study distributed algorithms implemented in a simplified biologically
inspired model for stochastic spiking neural networks. We focus on tradeoffs
between computation time and network complexity, along with the role of
randomness in efficient neural computation.
It is widely accepted that neural computation is inh... | computer science |
35,078 | Information Bottleneck in Control Tasks with Recurrent Spiking Neural
Networks | cs.NE | The nervous system encodes continuous information from the environment in the
form of discrete spikes, and then decodes these to produce smooth motor
actions. Understanding how spikes integrate, represent, and process information
to produce behavior is one of the greatest challenges in neuroscience.
Information theory ... | computer science |
35,079 | Deep Learning Methods for Improved Decoding of Linear Codes | cs.IT | The problem of low complexity, close to optimal, channel decoding of linear
codes with short to moderate block length is considered. It is shown that deep
learning methods can be used to improve a standard belief propagation decoder,
despite the large example space. Similar improvements are obtained for the
min-sum alg... | computer science |
35,080 | A Minimal Developmental Model Can Increase Evolvability in Soft Robots | cs.NE | Different subsystems of organisms adapt over many time scales, such as rapid
changes in the nervous system (learning), slower morphological and neurological
change over the lifetime of the organism (postnatal development), and change
over many generations (evolution). Much work has focused on instantiating
learning or ... | computer science |
35,081 | Modeling Musical Context with Word2vec | cs.SD | We present a semantic vector space model for capturing complex polyphonic
musical context. A word2vec model based on a skip-gram representation with
negative sampling was used to model slices of music from a dataset of
Beethoven's piano sonatas. A visualization of the reduced vector space using
t-distributed stochastic... | computer science |
35,082 | Toward Inverse Control of Physics-Based Sound Synthesis | cs.SD | Long Short-Term Memory networks (LSTMs) can be trained to realize inverse
control of physics-based sound synthesizers. Physics-based sound synthesizers
simulate the laws of physics to produce output sound according to input gesture
signals. When a user's gestures are measured in real time, she or he can use
them to con... | computer science |
35,083 | Chord Label Personalization through Deep Learning of Integrated Harmonic
Interval-based Representations | cs.SD | The increasing accuracy of automatic chord estimation systems, the
availability of vast amounts of heterogeneous reference annotations, and
insights from annotator subjectivity research make chord label personalization
increasingly important. Nevertheless, automatic chord estimation systems are
historically exclusively... | computer science |
35,084 | Vision-based Detection of Acoustic Timed Events: a Case Study on
Clarinet Note Onsets | cs.NE | Acoustic events often have a visual counterpart. Knowledge of visual
information can aid the understanding of complex auditory scenes, even when
only a stereo mixdown is available in the audio domain, \eg identifying which
musicians are playing in large musical ensembles. In this paper, we consider a
vision-based appro... | computer science |
35,085 | Talking Drums: Generating drum grooves with neural networks | cs.SD | Presented is a method of generating a full drum kit part for a provided
kick-drum sequence. A sequence to sequence neural network model used in natural
language translation was adopted to encode multiple musical styles and an
online survey was developed to test different techniques for sampling the
output of the softma... | computer science |
35,086 | Comparing Information-Theoretic Measures of Complexity in Boltzmann
Machines | cs.IT | In the past three decades, many theoretical measures of complexity have been
proposed to help understand complex systems. In this work, for the first time,
we place these measures on a level playing field, to explore the qualitative
similarities and differences between them, and their shortcomings.
Specifically, using ... | computer science |
35,087 | Spectral Modes of Network Dynamics Reveal Increased Informational
Complexity Near Criticality | cs.NE | What does the informational complexity of dynamical networked systems tell us
about intrinsic mechanisms and functions of these complex systems? Recent
complexity measures such as integrated information have sought to
operationalize this problem taking a whole-versus-parts perspective, wherein
one explicitly computes t... | computer science |
35,088 | A multi-agent reinforcement learning model of common-pool resource
appropriation | cs.MA | Humanity faces numerous problems of common-pool resource appropriation. This
class of multi-agent social dilemma includes the problems of ensuring
sustainable use of fresh water, common fisheries, grazing pastures, and
irrigation systems. Abstract models of common-pool resource appropriation based
on non-cooperative ga... | computer science |
35,089 | Speaker Diarization using Deep Recurrent Convolutional Neural Networks
for Speaker Embeddings | cs.SD | In this paper we propose a new method of speaker diarization that employs a
deep learning architecture to learn speaker embeddings. In contrast to the
traditional approaches that build their speaker embeddings using manually
hand-crafted spectral features, we propose to train for this purpose a
recurrent convolutional ... | computer science |
35,090 | On the approximation by single hidden layer feedforward neural networks
with fixed weights | cs.NE | Feedforward neural networks have wide applicability in various disciplines of
science due to their universal approximation property. Some authors have shown
that single hidden layer feedforward neural networks (SLFNs) with fixed weights
still possess the universal approximation property provided that approximated
funct... | computer science |
35,091 | Adaptive Plant Propagation Algorithm for Solving Economic Load Dispatch
Problem | cs.CE | Optimization problems in design engineering are complex by nature, often
because of the involvement of critical objective functions accompanied by a
number of rigid constraints associated with the products involved. One such
problem is Economic Load Dispatch (ED) problem which focuses on the
optimization of the fuel co... | computer science |
35,092 | Algorithmically probable mutations reproduce aspects of evolution such
as convergence rate, genetic memory, modularity, diversity explosions, and
mass extinction | cs.NE | Natural selection explains how life has evolved over millions of years from
more primitive forms. The speed at which this happens, however, has sometimes
defied explanations based on random (uniformly distributed) mutations. Here we
investigate the application of algorithmic mutations (no recombination) to
binary matri... | computer science |
35,093 | AutoPerf: A Generalized Zero-Positive Learning System to Detect Software
Performance Anomalies | cs.SE | In this paper, we present AutoPerf, a generalized software performance
anomaly detection system. AutoPerf uses autoencoders, an unsupervised learning
technique, and hardware performance counters to learn the performance
signatures of parallel programs. It then uses this knowledge to identify when
newer versions of the ... | computer science |
35,094 | Spiking neurons with short-term synaptic plasticity form superior
generative networks | cs.NE | Spiking networks that perform probabilistic inference have been proposed both
as models of cortical computation and as candidates for solving problems in
machine learning. However, the evidence for spike-based computation being in
any way superior to non-spiking alternatives remains scarce. We propose that
short-term p... | computer science |
35,095 | Reservoir Computing using Stochastic p-Bits | cs.ET | We present a general hardware framework for building networks that directly
implement Reservoir Computing, a popular software method for implementing and
training Recurrent Neural Networks and are particularly suited for temporal
inferencing and pattern recognition. We provide a specific example of a
candidate hardware... | computer science |
35,096 | A graphical, scalable and intuitive method for the placement and the
connection of biological cells | cs.NE | We introduce a graphical method originating from the computer graphics domain
that is used for the arbitrary and intuitive placement of cells over a
two-dimensional manifold. Using a bitmap image as input, where the color
indicates the identity of the different structures and the alpha channel
indicates the local cell ... | computer science |
35,097 | Adversarial Domain Adaptation for Identifying Phase Transitions | cs.NE | The identification of phases of matter is a challenging task, especially in
quantum mechanics, where the complexity of the ground state appears to grow
exponentially with the size of the system. We address this problem with
state-of-the-art deep learning techniques: adversarial domain adaptation. We
derive the phase di... | computer science |
35,098 | Does Phase Matter For Monaural Source Separation? | cs.SD | The "cocktail party" problem of fully separating multiple sources from a
single channel audio waveform remains unsolved. Current biological
understanding of neural encoding suggests that phase information is preserved
and utilized at every stage of the auditory pathway. However, current
computational approaches primari... | computer science |
35,099 | Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep
Neural Networks | math.NA | The mathematical problem for Electrical Impedance Tomography (EIT) is a
highly nonlinear ill-posed inverse problem requiring carefully designed
reconstruction procedures to ensure reliable image generation. D-bar methods
are based on a rigorous mathematical analysis and provide robust direct
reconstructions by using a ... | computer science |
35,100 | A Further Analysis of The Role of Heterogeneity in Coevolutionary
Spatial Games | cs.GT | Heterogeneity has been studied as one of the most common explanations of the
puzzle of cooperation in social dilemmas. A large number of papers have been
published discussing the effects of increasing heterogeneity in structured
populations of agents, where it has been established that heterogeneity may
favour cooperat... | computer science |
35,101 | RoboJam: A Musical Mixture Density Network for Collaborative Touchscreen
Interaction | cs.HC | RoboJam is a machine-learning system for generating music that assists users
of a touchscreen music app by performing responses to their short
improvisations. This system uses a recurrent artificial neural network to
generate sequences of touchscreen interactions and absolute timings, rather
than high-level musical not... | computer science |
35,102 | Reconstruction of Electrical Impedance Tomography Using Fish School
Search, Non-Blind Search, and Genetic Algorithm | cs.NE | Electrical Impedance Tomography (EIT) is a noninvasive imaging technique that
does not use ionizing radiation, with application both in environmental
sciences and in health. Image reconstruction is performed by solving an inverse
problem and ill-posed. Evolutionary Computation and Swarm Intelligence have
become a sourc... | computer science |
35,103 | NEURAghe: Exploiting CPU-FPGA Synergies for Efficient and Flexible CNN
Inference Acceleration on Zynq SoCs | cs.NE | Deep convolutional neural networks (CNNs) obtain outstanding results in tasks
that require human-level understanding of data, like image or speech
recognition. However, their computational load is significant, motivating the
development of CNN-specialized accelerators. This work presents NEURAghe, a
flexible and effici... | computer science |
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