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Entropic minimization of multiple-valued functions

A. Lloris-Ruiz, J.F. Gomez-Lopera, R. Roman-Roldan
[1993] Proceedings of the Twenty-Third International Symposium on Multiple-Valued Logic  
An information theoretic procedure for minimizing multiple-valued switching f u n c t i o n is outlined.  ...  of the f u n c t i o n to be minimized.  ...  An important aspect considered by many authors ([61 and ref. therein) is the minimization of multiple-valued functions.  ... 
doi:10.1109/ismvl.1993.289586 dblp:conf/ismvl/Lloris-RuizGR93 fatcat:rqkh2y7yy5dxdjjlcv7czvtm4q

Use of the Multilayer Fragment Molecular Orbital Method to Predict the Rank Order of Protein–Ligand Binding Affinities: A Case Study Using Tankyrase 2 Inhibitors

Noriaki Okimoto, Takao Otsuka, Yoshinori Hirano, Makoto Taiji
2018 ACS Omega  
Our results show that this computational approach using the MFMO method is a promising tool for predicting the rank order of the binding affinities of inhibitor analogues.  ...  In this study, we have evaluated the ability to rank the binding affinities of tankyrase 2 ligands by combining both MM and QM calculations.  ...  our scoring function could provide more reliable binding affinities by adopting the lowest binding affinity from among multiple energy-minimized structures.  ... 
doi:10.1021/acsomega.8b00175 pmid:31458673 pmcid:PMC6641631 fatcat:u56nzznqrvfxtcen64kqqc33me

Momentum-based Accelerated Mirror Descent Stochastic Approximation for Robust Topology Optimization under Stochastic Loads [article]

Weichen Li, Xiaojia Shelly Zhang
2020 arXiv   pre-print
We derive the AC-MDSA update formula based on ℓ_1-norm with entropy function, which is tailored to the geometry of the feasible domain.  ...  RTO problems involving various types of load uncertainties.  ...  Theoretical and numerical comparisons of the entropic MDSA and SGD are also carried out therein, and show better performance (objective function values and computational time) of the 1 -norm entropic MDSA  ... 
arXiv:2008.13284v1 fatcat:ufedszhwxjbljoc65z64ld356q

Mixture of Experts with Entropic Regularization for Data Classification

Billy Peralta, Ariel Saavedra, Luis Caro, Alvaro Soto
2019 Entropy  
"Mixture-of-experts" is a well-known classification technique; it is a probabilistic model consisting of local expert classifiers weighted by a gate network that is typically based on softmax functions  ...  In this scheme, one data point is influenced by only one expert; as a result, the training process can be misguided in real datasets for which complex data need to be explained by multiple experts.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/e21020190 pmid:33266905 fatcat:yptcupp5j5cujgfk5om2tqqbbi

Entropic Herding [article]

Hiroshi Yamashita, Hideyuki Suzuki, Kazuyuki Aihara
2021 arXiv   pre-print
Entropic herding is derived as the optimization of the target function obtained from the maximum entropy principle.  ...  In this paper, we propose an extension of the herding algorithm, called entropic herding, which generates a sequence of distributions instead of points.  ...  Specifically, entropic herding is based on the minimization of the target function L.  ... 
arXiv:2112.11616v1 fatcat:73mqpov5cff6jjp77d3i3rnbnm

The entropic cost to tie a knot

M Baiesi, E Orlandini, A L Stella
2010 Journal of Statistical Mechanics: Theory and Experiment  
Furthermore, we discover that the mere existence of a knot requires a well defined entropic cost that scales exponentially with its minimal length.  ...  By collecting a rich statistics of configurations with very large values of N we are able to analyse the asymptotic behaviour of the partition function of the problem for different knot types.  ...  MB acknowledges financial support from University of Padua (Progetto di Ateneo no. CPDA083702).  ... 
doi:10.1088/1742-5468/2010/06/p06012 fatcat:6aovuk5oxnc3vehpzvqw6sjuzi

Fusión Sensorial usando medidas Entrópicas de Dependencia

Paul B. Deignan
2011 Revista de Matemática: Teoría y Aplicaciones  
The properties of entropic measures are shown to fit within the Bayesian framework of hierarchical sensor fusion.  ...  As opposed to standard methods of association which rely on measures of central dispersion, entropic measures quantify multivalued relations.  ...  Let N = 1 so that the negative value of the entropic functional is a simple linear combination of logarithmic kernels weighted by their respective arguments.  ... 
doi:10.15517/rmta.v18i2.2099 fatcat:ozobh2aylvdfpgan6i6ji6ntpa

Ground states of stealthy hyperuniform potentials: I. Entropically favored configurations

G. Zhang, F. H. Stillinger, S. Torquato
2015 Physical Review E  
In this paper, we provide details and justifications of the simulation procedure, which involves performing molecular dynamics simulations at sufficiently low temperatures and minimizing the energy of  ...  We report results for the pair correlation functions, structure factors, and Voronoi cell statistics.  ...  This constraint is especially hard to meet when simulating multiple systems at the same χ value across dimensions.  ... 
doi:10.1103/physreve.92.022119 pmid:26382356 fatcat:kuqpgbjr4vcfrl46weepxtqwby

Entropic descriptor based reconstruction of three-dimensional porous microstructures using a single cross-section [article]

D. Frączek, W. Olchawa, R. Piasecki, R. Wiśniowski
2015 arXiv   pre-print
They suggest the entropic method is a promising approach, which offers a kind of compromise between the computational efficiency and the accuracy of the statistical reconstructions.  ...  The simple entropic method to statistical reconstructing of heterogeneous three-dimensional media from a single two-dimensional image is briefly reported.  ...  Simulated annealing At this stage, we employ the MC simulated annealing, which should further minimize the entropic cost function, Eavg(start).  ... 
arXiv:1508.03857v2 fatcat:xednom2jqveqfmwzjx5iy6q5a4

Multi-Way Number Partitioning: an Information-Theoretic View [article]

Niloufar Ahmadypour, Amin Gohari
2020 arXiv   pre-print
The number partitioning problem is the problem of partitioning a given list of numbers into multiple subsets so that the sum of the numbers in each subset are as nearly equal as possible.  ...  We introduce two closely related notions of the "most informative" and "most compressible" partitions. Most informative partitions satisfy a principle of optimality property.  ...  Since the min-entropy is never larger than the Shannon entropy, the maximum value of H ∞ (A) yields a lower bound on the maximum of H(A). 1 Finally, the entropic objective function depends on the entire  ... 
arXiv:2009.02710v1 fatcat:ugjxsy4dqfcgncu57fsqjsd5x4

Cheap robust learning of data anomalies with analytically solvable entropic outlier sparsification

Illia Horenko
2022 Proceedings of the National Academy of Sciences of the United States of America  
EOS dwells on the derived analytic solution of the (weighted) expected loss minimization problem subject to Shannon entropy regularization.  ...  Entropic outlier sparsification (EOS) is proposed as a cheap and robust computational strategy for learning in the presence of data anomalies and outliers.  ...  a scalar-valued loss function measuring a misfit of the data dimension D—in contrast to common regularization techniques instance xt .  ... 
doi:10.1073/pnas.2119659119 pmid:35197293 pmcid:PMC8917346 fatcat:uxsxu2zabbevhhchgio3nk7otm

On a generalized entropic uncertainty relation in the case of the qubit

S Zozor, G M Bosyk, M Portesi
2013 Journal of Physics A: Mathematical and Theoretical  
Moreover, we present an analytical but suboptimal bound for any couple of indices. In all cases, we provide the minimizing states.  ...  We derive a general expression for the tight lower bound of the sum of R\'enyi entropies for any couple of (positive) entropic indices (\alpha,\beta).  ...  (b) Optimal angle θ opt as a function of α > 0.5 for some c. Figure 3 : 3 Plane of entropic indices.  ... 
doi:10.1088/1751-8113/46/46/465301 fatcat:lf2sbhftqvgfbnvweb5gjmrb64

Subgraph centrality and walk-regularity [article]

Eric Horton, Kyle Kloster, Blair D. Sullivan
2019 arXiv   pre-print
To date, only one entropic graph has been identified, with only two witnessing parameter values, raising the question of how many such graphs and parameters exist.  ...  For parameterized measures, we are also interested in which values of the parameter witness this uniformity.  ...  The distribution of entropic values We now consider the set of all entropic values.  ... 
arXiv:1804.05966v3 fatcat:vwbqpvjuozczxaibjlc7v2e77a

Entropic gravity, phase-space noncommutativity and the equivalence principle

Catarina Bastos, Orfeu Bertolami, Nuno Costa Dias, João Nuno Prata
2011 Classical and quantum gravity  
Verlinde's entropic gravity reasoning to a phase-space noncommutativity set-up. This allow us to impose a bound on the product of the noncommutative parameters based on the Equivalence Principle.  ...  The key feature of our analysis is an effective Planck's constant that naturally arises when accounting for the noncommutative features of the phase-space.  ...  Acknowledgments The work of CB is supported by Fundação para a Ciência e a Tecnologia (  ... 
doi:10.1088/0264-9381/28/12/125007 fatcat:dw5pdxn3hvd7rgsed4zyrqngra

Self-organizing Networks of Information Gathering Cognitive Agents [article]

Ahmed M. Alaa, Kartik Ahuja, Mihaela Van der Schaar
2015 arXiv   pre-print
Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant.  ...  We model the formation of a network as a non-cooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost  ...  From Theorem 2 we know that, at NE, the network is generally composed of multiple components and each component is minimally connected.  ... 
arXiv:1503.04768v2 fatcat:6fkwurpz3ja4zcv6gng7jtpog4
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