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A Stochastic Attention CNN Model for Rumor Stance Classification

Na Bai, Zhixiao Wang, Fanrong Meng
2020 IEEE Access  
simulate casual online reading habits and to extract course-grained features such as phrase features.  ...  After the convolutional layer, fine-grained features such as keywords can be extracted by a pooling layer.  ...  model should be a textual information graining process from coarse to fine granularity.  ... 
doi:10.1109/access.2020.2990770 fatcat:b2okeocg7feejgd7lvksywsom4

Privileged Features Distillation at Taobao Recommendations [article]

Chen Xu, Quan Li, Junfeng Ge, Jinyang Gao, Xiaoyong Yang, Changhua Pei, Fei Sun, Jian Wu, Hanxiao Sun, Wenwu Ou
2020 arXiv   pre-print
Knowledge distilled from the more accurate teacher is transferred to the student to improve its accuracy. During serving, only the student part is extracted and it relies on no privileged features.  ...  ., click-through rate (CTR) at coarse-grained ranking and CVR at fine-grained ranking.  ...  PFD also differs from the original learning using privileged information (LUPI) [24] , where the teacher only processes the privileged features. teacher model.  ... 
arXiv:1907.05171v2 fatcat:y4a5swvuxze37jjjppejwarwqm

Literacy effects on language and vision: Emergent effects from an amodal shared resource (ASR) computational model

Alastair C. Smith, Padraic Monaghan, Falk Huettig
2014 Cognitive Psychology  
journal homepag e: www.elsevier.com/locate/co gpsych phonological representations in the model simulated the high/low literacy effects on phonological processing, suggesting that literacy has a focused  ...  effect in changing the grain-size of phonological mappings.  ...  The visual layer (80 units) simulates the extraction of visual information from up to four locations in the visual field. The layer is divided into four 20 unit slots.  ... 
doi:10.1016/j.cogpsych.2014.07.002 pmid:25171049 fatcat:t3vsytncnfgf3bsn2qh3nprgfe

Robust Event Classification Using Imperfect Real-world PMU Data [article]

Yunchuan Liu, Lei Yang, Amir Ghasemkhani, Hanif Livani, Virgilio A. Centeno, Pin-Yu Chen, Junshan Zhang
2021 arXiv   pre-print
method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different  ...  To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction  ...  Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or  ... 
arXiv:2110.10128v1 fatcat:a5j57evosfemxnqqqifn2xvbi4

Holographic renormalization with machine learning

Eric Howard
2020 Figshare  
If the RBM is properly trained, the hidden units learn to extract useful features from training data.  ...  As a neural network extracts features from complex data, its mapping to the Renormalization group can help with identify features in complex quantum many-body problems.  ... 
doi:10.6084/m9.figshare.12619067 fatcat:fkffc22zubaincnnnglznbpbqm

From Scilab to multicore embedded systems: Algorithms and methodologies

George Goulas, Panayiotis Alefragis, Nikolaos S. Voros, Christos Valouxis, Christos Gogos, Nikolaos Kavvadias, Grigoris Dimitroulakos, Kostas Masselos, Diana Goehringer, Steven Derrien, Daniel Menard, Olivier Sentieys (+8 others)
2012 2012 International Conference on Embedded Computer Systems (SAMOS)  
There is an increasing need for tools and methodologies to narrow the entry gap for non-experts in parallel software development as well as to streamline the work for experts.  ...  The ALMA parallelization approach in a nutshell attempts to manage the complexity of the task by alternating focus between very localized and holistic view program optimization strategies.  ...  Such distinction is possible due to the controllably detailed event logging features of the simulator. V. ALGORITHMS FOR THE FRONT END A.  ... 
doi:10.1109/samos.2012.6404184 dblp:conf/samos/GoulasAVVGKDMGDMSHSOBRSKM12 fatcat:ldkdwbhc5batjfkzi6vphfvxbq

Coarse-graining Molecular Systems by Spectral Matching [article]

Feliks Nüske, Lorenzo Boninsegna, Cecilia Clementi
2019 arXiv   pre-print
Simul. (2011), we present a general framework, called spectral matching, which directly targets the generator's leading eigenvalue equations when learning parameters for coarse-grained models.  ...  For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale systems become computationally tractable.  ...  Several approaches have been proposed to design coarse-grained models for large molecular systems that either reproduce structural features of fine-grained (atomistic) models (bottom-up) [1] [2] [3] [  ... 
arXiv:1904.07177v1 fatcat:ojjef5nntjdvpejmefgg7un5j4

Holographic Renormalization with Machine learning [article]

Eric Howard
2018 arXiv   pre-print
We show that deep learning algorithms that use an RG-like scheme to learn relevant features from data could help to understand the nature of the holographic entanglement entropy and the holographic principle  ...  Using deep learning methods mapped to a genuine field theory, we develop a mechanism capable to identify relevant degrees of freedom and induce scale invariance without prior knowledge about a system.  ...  If the RBM is properly trained, the hidden units learn to extract useful features from training data.  ... 
arXiv:1803.11056v2 fatcat:s7aliw7vtnaprivmapcbopdw4a

WiFiMod: Transformer-based Indoor Human Mobility Modeling using Passive Sensing [article]

Amee Trivedi, Kate Silverstein, Emma Strubell, Mohit Iyyer, Prashant Shenoy
2021 arXiv   pre-print
WiFiMod takes as input enterprise WiFi system logs to extract human mobility trajectories from smartphone digital traces.  ...  Modeling human mobility has a wide range of applications from urban planning to simulations of disease spread.  ...  Moreover, indoor mobility displays a complex sequential periodicity correlated to the macro, outdoor or coarse grained, features of mobility.  ... 
arXiv:2104.09835v3 fatcat:pg7zbyxkcrevxickb2it2ww2kq

Machine learning for molecular simulation [article]

Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller, Cecilia Clementi
2019 Annual review of physical chemistry (Print)   pre-print
Here we review recent ML methods for molecular simulation, with particular focus on (deep) neural networks for the prediction of quantum-mechanical energies and forces, coarse-grained molecular dynamics  ...  , the extraction of free energy surfaces and kinetics and generative network approaches to sample molecular equilibrium structures and compute thermodynamics.  ...  Acknowledgements We gratefully acknowledge funding from European Commission (ERC CoG 772230 "ScaleCell" to F.N. and ERC-CoG grant BeStMo to A.T.  ... 
doi:10.1146/annurev-physchem-042018-052331 pmid:32092281 arXiv:1911.02792v1 fatcat:oknrozbbxbcn7albpgo42rzwee

A Compact and Discriminative Feature Based on Auditory Summary Statistics for Acoustic Scene Classification

Hongwei Song, Jiqing Han, Shiwen Deng
2018 Interspeech 2018  
The inspiration comes from a recent neuroscience study, which shows the human auditory system tends to perceive sound textures through time-averaged statistics.  ...  One of the biggest challenges of acoustic scene classification (ASC) is to find proper features to better represent and characterize environmental sounds.  ...  Feature Extraction The feature extraction process is shown in Figure 1 .  ... 
doi:10.21437/interspeech.2018-1299 dblp:conf/interspeech/SongHD18 fatcat:xq723nilw5g6tm372fgbwkynzy

Use of neuro fuzzy network with hybrid intelligent optimization techniques for weight determination in parallel Job scheduling

S.V. Sudha
2012 Scientific Research and Essays  
This paper is concerned with the performance tuning of the fuzzy logic controller (FLC) used for the process grain sized scheduling of parallel jobs.  ...  The fuzzy logic controller uses Mamdani model for classifying the scheduling class and found that the error rate is high during the defuzzification and need to tune the fuzzy controller to reduce the error  ...  Coarse grain With coarse Grain, there is synchronization among processes, but at a very gross level.  ... 
doi:10.5897/sre11.2148 fatcat:b76strdq65gubn6s5swho3ol6m

Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-agent Trajectories

Tharindu Fernando, Sridha Sridharan, Clinton Fookes, Simon Denman
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
It can be seen that is difficult to extract any high level understanding, or infer tactical information from the hand-crafted feature.  ...  models to generate the final event prediction.  ... 
doi:10.1109/cvprw.2018.00224 dblp:conf/cvpr/FernandoSFD18 fatcat:wipm7p7afvhvfnidk3j4wtzm3u

Coarse-grained variables for particle-based models: diffusion maps and animal swarming simulations

Ping Liu, Hannah R. Safford, Iain D. Couzin, Ioannis G. Kevrekidis
2014 Computational Particle Mechanics  
Our computational data-driven coarse-graining approach extracts two coarse (collective) variables from the detailed particle-based simulations, and helps formulate a low-dimensional stochastic differential  ...  As microscopic (e.g. atomistic, stochastic, agentbased, particle-based) simulations become increasingly prevalent in the modeling of complex systems, so does the need to systematically coarse-grain the  ...  space in order to extract the effective SDE from particle simulation bursts. Mean exit time computation through the coarse-grained model.  ... 
doi:10.1007/s40571-014-0030-7 fatcat:pzkcsegfjfagxijccz6lynec2m

Learning developmental mode dynamics from single-cell trajectories [article]

Nicolas Romeo, Alasdair Hastewell, Alexander Mietke, Jörn Dunkel
2021 arXiv   pre-print
framework for learning quantitative continuum models from single-cell imaging data.  ...  Due to its generic conceptual foundation, we expect that mode-based model learning can help advance the quantitative biophysical understanding of a wide range of developmental structure formation processes  ...  ., 2018) for providing us access to HPC resources. This work was supported by a MathWorks Science Fellowship (N.R. and A.D.H), a Longterm Fellowship from the  ... 
arXiv:2103.08130v2 fatcat:evlhp4gcuve6joqwz6j4ycmt4e
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