8,559 research outputs found
Neural Networks Architecture Evaluation in a Quantum Computer
In this work, we propose a quantum algorithm to evaluate neural networks
architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The
proposed algorithm is based on a quantum associative memory and the learning
algorithm for artificial neural networks. Unlike conventional algorithms for
evaluating neural network architectures, QNNAE does not depend on
initialization of weights. The proposed algorithm has a binary output and
results in 0 with probability proportional to the performance of the network.
And its computational cost is equal to the computational cost to train a neural
network
Semantic distillation: a method for clustering objects by their contextual specificity
Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence,
Springer-Verla
Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network
Bibliographic analysis considers the author's research areas, the citation
network and the paper content among other things. In this paper, we combine
these three in a topic model that produces a bibliographic model of authors,
topics and documents, using a nonparametric extension of a combination of the
Poisson mixed-topic link model and the author-topic model. This gives rise to
the Citation Network Topic Model (CNTM). We propose a novel and efficient
inference algorithm for the CNTM to explore subsets of research publications
from CiteSeerX. The publication datasets are organised into three corpora,
totalling to about 168k publications with about 62k authors. The queried
datasets are made available online. In three publicly available corpora in
addition to the queried datasets, our proposed model demonstrates an improved
performance in both model fitting and document clustering, compared to several
baselines. Moreover, our model allows extraction of additional useful knowledge
from the corpora, such as the visualisation of the author-topics network.
Additionally, we propose a simple method to incorporate supervision into topic
modelling to achieve further improvement on the clustering task.Comment: Preprint for Journal Machine Learnin
Probabilistic Quantum Memories
Typical address-oriented computer memories cannot recognize incomplete or
noisy information. Associative (content-addressable) memories solve this
problem but suffer from severe capacity shortages. I propose a model of a
quantum memory that solves both problems. The storage capacity is exponential
in the number of qbits and thus optimal. The retrieval mechanism for incomplete
or noisy inputs is probabilistic, with postselection of the measurement result.
The output is determined by a probability distribution on the memory which is
peaked around the stored patterns closest in Hamming distance to the input.Comment: Revised version to appear in Phys. Rev. Let
Storage and retrieval of vector beams of light in a multiple-degree-of-freedom quantum memory
The full structuration of light in the transverse plane, including intensity,
phase and polarization, holds the promise of unprecedented capabilities for
applications in classical optics as well as in quantum optics and information
sciences. Harnessing special topologies can lead to enhanced focusing, data
multiplexing or advanced sensing and metrology. Here we experimentally
demonstrate the storage of such spatio-polarization-patterned beams into an
optical memory. A set of vectorial vortex modes is generated via liquid crystal
cell with topological charge in the optic axis distribution, and preservation
of the phase and polarization singularities is demonstrated after retrieval, at
the single-photon level. The realized multiple-degree-of-freedom memory can
find applications in classical data processing but also in quantum network
scenarios where structured states have been shown to provide promising
attributes, such as rotational invariance
Nanoinformatics: developing new computing applications for nanomedicine
Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others
Mapping Subsets of Scholarly Information
We illustrate the use of machine learning techniques to analyze, structure,
maintain, and evolve a large online corpus of academic literature. An emerging
field of research can be identified as part of an existing corpus, permitting
the implementation of a more coherent community structure for its
practitioners.Comment: 10 pages, 4 figures, presented at Arthur M. Sackler Colloquium on
"Mapping Knowledge Domains", 9--11 May 2003, Beckman Center, Irvine, CA,
proceedings to appear in PNA
A Neural Network Classifier for the COI Barcode Gene
Mitochondrial Cytochrome C Oxidase subunit I (CO I â to be read as âsee â oh oneâ) is a 658 base pair region in the gene encoding that is proposed as standard barcode for animals. Meaning, the CO I is a special region found in animal DNA that is studied to identify the species of the animal. Currently, there is an implementation of an algorithm called ARBitrator which identifies and extracts these CO I sequences from enormous genes database called GenBank. The ARBitrator is good at extracting the CO I sequences that have better specificity and accuracy as compared to other existing algorithms for CO I sequence identification[1][2]. Now, this project aims at training a neural network to learn the features of the CO I sequences extracted by ARBitrator, so that this neural network can be used in future to further recognize CO I sequences. Effectively, we are aiming to successfully design, train, and use a deep learning neural network to learn to recognize CO I sequences in a supervised way. This is the first time that a neural network is explored and used for this purpose
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