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Retrieval-based learning

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https://www.readbyqxmd.com/read/28092544/discriminative-multi-view-interactive-image-re-ranking
#1
Jun Li, Chang Xu, Wankou Yang, Changyin Sun, Dacheng Tao
-Given unreliable visual patterns and insufficient query information, content-based image retrieval (CBIR) is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose Discriminative Multi-view INTeractive Image Re-ranking (DMINTIR), which integrates User Relevance Feedback (URF) capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities...
January 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28080119/the-role-of-episodic-context-in-retrieval-practice-effects
#2
Joshua W Whiffen, Jeffrey D Karpicke
The episodic context account of retrieval-based learning proposes that retrieval enhances subsequent retention because people must think back to and reinstate a prior learning context. Three experiments directly tested this central assumption of the context account. Subjects studied word lists and then either restudied the words under intentional learning conditions or made list discrimination judgments by indicating which list each word had occurred in originally. Subjects in both conditions experienced all items for the same amount of time, but subjects in the list discrimination condition were required to retrieve details about the original episodic context in which the words had occurred...
January 12, 2017: Journal of Experimental Psychology. Learning, Memory, and Cognition
https://www.readbyqxmd.com/read/28077707/organization-of-the-claustrum-to-entorhinal-cortical-connection-in-mice
#3
Takuma Kitanishi, Naoki Matsuo
: The claustrum, a subcortical structure situated between the insular cortex and striatum, is reciprocally connected with almost all neocortical regions. Based on this connectivity, the claustrum has been postulated to integrate multisensory information and, in turn, coordinate widespread cortical activity. Although studies have identified how sensory information is mapped onto the claustrum, the function of individual topographically arranged claustro-cortical pathways has been little explored...
January 11, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28055940/deep-nonlinear-metric-learning-for-3-d-shape-retrieval
#4
Jin Xie, Guoxian Dai, Fan Zhu, Ling Shao, Yi Fang
Effective 3-D shape retrieval is an important problem in 3-D shape analysis. Recently, feature learning-based shape retrieval methods have been widely studied, where the distance metrics between 3-D shape descriptors are usually hand-crafted. In this paper, motivated by the fact that deep neural network has the good ability to model nonlinearity, we propose to learn an effective nonlinear distance metric between 3-D shape descriptors for retrieval. First, the locality-constrained linear coding method is employed to encode each vertex on the shape and the encoding coefficient histogram is formed as the global 3-D shape descriptor to represent the shape...
December 28, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28055923/supervised-discrete-hashing-with-relaxation
#5
Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan
Data-dependent hashing has recently attracted attention due to being able to support efficient retrieval and storage of high-dimensional data, such as documents, images, and videos. In this paper, we propose a novel learning-based hashing method called ''supervised discrete hashing with relaxation'' (SDHR) based on ''supervised discrete hashing'' (SDH). SDH uses ordinary least squares regression and traditional zero-one matrix encoding of class label information as the regression target (code words), thus fixing the regression target...
December 29, 2016: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28046074/robust-real-time-music-transcription-with-a-compositional-hierarchical-model
#6
Matevž Pesek, Aleš Leonardis, Matija Marolt
The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e...
2017: PloS One
https://www.readbyqxmd.com/read/28043955/structural-cerebellar-correlates-of-cognitive-and-motor-dysfunctions-in-cerebellar-degeneration
#7
Kalyani Kansal, Zhen Yang, Ann M Fishman, Haris I Sair, Sarah H Ying, Bruno M Jedynak, Jerry L Prince, Chiadi U Onyike
Detailed mapping of clinical dysfunctions to the cerebellar lobules in disease populations is necessary to establish the functional significance of lobules implicated in cognitive and motor functions in normal subjects. This study constitutes the first quantitative examination of the lobular correlates of a broad range of cognitive and motor phenomena in cerebellar disease. We analysed cross-sectional data from 72 cases with cerebellar disease and 36 controls without cerebellar disease. Cerebellar lobule volumes were derived from a graph-cut based segmentation algorithm...
January 2, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28034788/an-unsupervised-machine-learning-model-for-discovering-latent-infectious-diseases-using-social-media-data
#8
Sunghoon Lim, Conrad S Tucker, Soundar Kumara
INTRODUCTION: The authors of this work propose an unsupervised machine learning model that has the ability to identify real-world latent infectious diseases by mining social media data. In this study, a latent infectious disease is defined as a communicable disease that has not yet been formalized by national public health institutes and explicitly communicated to the general public. Most existing approaches to modeling infectious-disease-related knowledge discovery through social media networks are top-down approaches that are based on already known information, such as the names of diseases and their symptoms...
December 26, 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28033004/machine-learning-methods-to-predict-density-functional-theory-b3lyp-energies-of-homo-and-lumo-orbitals
#9
Florbela Pereira, Kaixia Xiao, Diogo A R S Latino, Chengcheng Wu, Qingyou Zhang, Joao Aires-de-Sousa
Machine learning algorithms were explored for the fast estimation of HOMO and LUMO orbital energies calculated by DFT B3LYP, on the basis of molecular descriptors exclusively based on connectivity. The whole project involved the retrieval and generation of molecular structures, quantum chemical calculations for a database with >111 000 structures, development of new molecular descriptors, and training/validation of machine learning models. Several machine learning algorithms were screened, and an applicability domain was defined based on Euclidean distances to the training set...
December 29, 2016: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28026753/weakly-supervised-image-annotation-and-segmentation-with-objects-and-attributes
#10
Zhiyuan Shi, Yongxin Yang, Timothy Hospedales, Tao Xiang
We propose to model complex visual scenes using a non-parametric Bayesian model learned from weakly labelled images abundant on media sharing sites such as Flickr. Given weak image-level annotations of objects and attributes without locations or associations between them, our model aims to learn the appearance of object and attribute classes as well as their association on each object instance. Once learned, given an image, our model can be deployed to tackle a number of vision problems in a joint and coherent manner, including recognising objects in the scene (automatic object annotation), describing objects using their attributes (attribute prediction and association), and localising and delineating the objects (object detection and semantic segmentation)...
December 26, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28000308/implementation-of-an-e-learning-module-improves-the-consistency-in-the-histopathological-diagnosis-of-sessile-serrated-lesions-within-a-nationwide-population-screening-program
#11
Joep E G IJspeert, Ariana Madani, Lucy I H Overbeek, Evelien Dekker, Iris D Nagtegaal
BACKGROUND: Distinguishing premalignant sessile serrated lesions (SSL) from hyperplastic polyps (HP) is difficult for pathologists in daily practice. We aimed to evaluate nationwide variability within histopathology laboratories in the frequency of diagnosing SSL as compared to HP within the Dutch population based screening program for colorectal cancer (CRC) and to assess the effect of an e-learning module on interlaboratory consistency. METHODS: Data were retrieved from the Dutch Pathology Registry (PALGA) from start of the nationwide population screening program, January 2014, until December 2015...
December 21, 2016: Histopathology
https://www.readbyqxmd.com/read/27980117/the-caudate-nucleus-mediates-learning-of-stimulus-control-state-associations
#12
Yu-Chin Chiu, Jiefeng Jiang, Tobias Egner
: A longstanding dichotomy in cognitive psychology and neuroscience pits controlled, top-down driven against associative, bottom-up driven behavior, where cognitive control processes allow us to override well-learned stimulus-response (S-R) associations. By contrast, some recent studies have raised the intriguing possibility of an integration between associative and controlled processing in the form of stimulus-control state (S-C) associations, the learned linkage of specific stimuli to particular control states, such as high attentional selectivity...
December 15, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27964803/web-video-mining-supported-workflow-modeling-for-laparoscopic-surgeries
#13
Rui Liu, Xiaoli Zhang, Hao Zhang
MOTIVATION: As quality assurance is of strong concern in advanced surgeries, intelligent surgical systems are expected to have knowledge such as the knowledge of the surgical workflow model (SWM) to support their intuitive cooperation with surgeons. For generating a robust and reliable SWM, a large amount of training data is required. However, training data collected by physically recording surgery operations is often limited and data collection is time-consuming and labor-intensive, severely influencing knowledge scalability of the surgical systems...
November 2016: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/27933668/the-role-of-the-hippocampus-in-generalizing-configural-relationships
#14
Sam C Berens, Chris M Bird
The hippocampus has been implicated in integrating information across separate events in support of mnemonic generalizations. These generalizations may be underpinned by processes at both encoding (linking similar information across events) and retrieval ("on-the-fly" generalization). However, the relative contribution of the hippocampus to encoding- and retrieval-based generalizations is poorly understood. Using fMRI in humans, we investigated the hippocampal role in gradually learning a set of spatial discriminations and subsequently generalizing them in an acquired equivalence task...
December 9, 2016: Hippocampus
https://www.readbyqxmd.com/read/27928709/the-gabaergic-system-in-prefrontal-cortex-and-hippocampus-modulates-context-related-extinction-learning-and-renewal-in-humans
#15
Silke Lissek, Anne Golisch, Benjamin Glaubitz, Martin Tegenthoff
Context-related extinction learning and renewal in humans is mediated by hippocampal and prefrontal regions. Renewal is defined as the reoccurrence of an extinguished response if the contexts present during extinction learning and recall differ. Animal studies implicate hippocampal γ-aminobutyric acid (GABA) A receptors in extinction and renewal. However, human studies on GABAergic mechanisms in extinction learning are lacking. In this fMRI study, we therefore investigated the role of the GABAergic system in context-related extinction learning and renewal...
December 7, 2016: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/27924347/preprocessing-structured-clinical-data-for-predictive-modeling-and-decision-support-a-roadmap-to-tackle-the-challenges
#16
José Carlos Ferrão, Mónica Duarte Oliveira, Filipe Janela, Henrique M G Martins
BACKGROUND: EHR systems have high potential to improve healthcare delivery and management. Although structured EHR data generates information in machine-readable formats, their use for decision support still poses technical challenges for researchers due to the need to preprocess and convert data into a matrix format. During our research, we observed that clinical informatics literature does not provide guidance for researchers on how to build this matrix while avoiding potential pitfalls...
December 7, 2016: Applied Clinical Informatics
https://www.readbyqxmd.com/read/27922638/enhancing-dopaminergic-signaling-and-histone-acetylation-promotes-long-term-rescue-of-deficient-fear-extinction
#17
N Whittle, V Maurer, C Murphy, J Rainer, D Bindreither, M Hauschild, A Scharinger, M Oberhauser, T Keil, C Brehm, T Valovka, J Striessnig, N Singewald
Extinction-based exposure therapy is used to treat anxiety- and trauma-related disorders; however, there is the need to improve its limited efficacy in individuals with impaired fear extinction learning and to promote greater protection against return-of-fear phenomena. Here, using 129S1/SvImJ mice, which display impaired fear extinction acquisition and extinction consolidation, we revealed that persistent and context-independent rescue of deficient fear extinction in these mice was associated with enhanced expression of dopamine-related genes, such as dopamine D1 (Drd1a) and -D2 (Drd2) receptor genes in the medial prefrontal cortex (mPFC) and amygdala, but not hippocampus...
December 6, 2016: Translational Psychiatry
https://www.readbyqxmd.com/read/27920965/an-evaluation-of-the-impact-of-supervision-intensity-supervisor-qualifications-and-caseload-on-outcomes-in-the-treatment-of-autism-spectrum-disorder
#18
Dennis R Dixon, Erik Linstead, Doreen Granpeesheh, Marlena N Novack, Ryan French, Elizabeth Stevens, Laura Stevens, Alva Powell
Ample research has shown the benefits of intensive applied behavior analysis (ABA) treatment for autism spectrum disorder (ASD); research that investigates the role of treatment supervision, however, is limited. The present study examined the relationship between mastery of learning objectives and supervision hours, supervisor credentials, years of experience, and caseload in a large sample of children with ASD (N = 638). These data were retrieved from a large archival database of children with ASD receiving community-based ABA services...
December 2016: Behavior Analysis in Practice
https://www.readbyqxmd.com/read/27919371/a-machine-learning-based-framework-to-identify-type-2-diabetes-through-electronic-health-records
#19
Tao Zheng, Wei Xie, Liling Xu, Xiaoying He, Ya Zhang, Mingrong You, Gong Yang, You Chen
OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide association study (PheWAS), more cases (T2DM subjects) and controls (subjects without T2DM) are required to be identified (e.g., via Electronic Health Records (EHR)). However, existing expert based identification algorithms often suffer in a low recall rate and could miss a large number of valuable samples under conservative filtering standards...
January 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/27916028/-structured-training-strategy-for-robot-surgery
#20
H Q Xi, K C Zhang, B Wei, L Chen
With surgical strategy progresses towarding to precision and minimally invasive surgery, the Da Vinci robotic surgical system comes into being. Compared with conventional surgery, the Da Vinci robotic surgical system enjoys several advantages including clear operation field, flexibility and tremor filtration.Normative operation plays an important role in translating such advantages into clinical benefits.Training physicians systematically and comprehensively is very important. Compared with conventional training strategy, multi-modal simulation training is more preferred for the Da Vinci robotic surgical system training...
December 1, 2016: Zhonghua Wai Ke za Zhi [Chinese Journal of Surgery]
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