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Unsupervised Statistical Learning of Higher-Order Spatial Structures from Visual Scenes

József Fiser, Richard N. Aslin
2001 Psychological Science  
•The process of learning the co-occurrences between objects has been linked to higher order representations in the visual cortex (Logothetis & Sheinberg 1996) .  ...  •There is no direct evidence of visual statistical learning on eye movement changes.  ... 
doi:10.1111/1467-9280.00392 pmid:11760138 fatcat:iiil7lhnn5hkpdhfylbwd5zqiq

Multi-Task Learning with High-Order Statistics for X-vector based Text-Independent Speaker Verification [article]

Lanhua You, Wu Guo, Lirong Dai, Jun Du
2019 arXiv   pre-print
- and higher-order statistics of the original input utterance.  ...  The proposed training strategy aggregates both the supervised and unsupervised learning into one framework to make the speaker embeddings more discriminative and robust.  ...  Multi-task learning with high-order statistics High-order statistics Higher-order statistics can be used in estimation of the shape of unimodal distributions and have been applied to many tasks [14,  ... 
arXiv:1903.12058v2 fatcat:dlreitygybhtrhnjtpyotdjp2m

Multi-Task Learning with High-Order Statistics for x-Vector Based Text-Independent Speaker Verification

Lanhua You, Wu Guo, Li-Rong Dai, Jun Du
2019 Interspeech 2019  
higher-order statistics of the original input utterance.  ...  The proposed training strategy aggregates both the supervised and unsupervised learning into one framework to make the speaker embeddings more discriminative and robust.  ...  High-order statistics Higher-order statistics can be used in estimation of the shape of unimodal distributions and have been applied to many tasks [14, 15, 16] .  ... 
doi:10.21437/interspeech.2019-2264 dblp:conf/interspeech/YouGDD19 fatcat:h3igss5kf5dkxbjnj5hleiq42i

Learning multiview face subspaces and facial pose estimation using independent component analysis

S.Z. Li, XiaoGuang Lu, Xinwen Hou, Xianhua Peng, Qiansheng Cheng
2005 IEEE Transactions on Image Processing  
of multiview examples and the learning is done in an unsupervised way with view-unlabeled data.  ...  ICA, its variants, namely independent subspace analysis (ISA) and topographic independent component analysis (TICA), take into account higher order statistics needed for object view characterization.  ...  Such variations are related to higher order statistics.  ... 
doi:10.1109/tip.2005.847295 pmid:15971770 fatcat:w7qbp76dcne3ne6m232a3a5r3u

HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation [article]

Chao Chen, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua
2019 arXiv   pre-print
In this work, we explore the benefits of using higher-order statistics (mainly refer to third-order and fourth-order statistics) for domain matching.  ...  Minimizing the discrepancy of feature distributions between different domains is one of the most promising directions in unsupervised domain adaptation.  ...  Higher-order Statistics The statistics higher than firstorder has been success fully used in many classical and deep learning methods [9, 19, 30, 22, 12] .  ... 
arXiv:1912.11976v1 fatcat:aa5k34pqgrhxrazxzutpxkytvm

HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation

Chao Chen, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin, Xian-sheng Hua
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Moreover, HoMM (order≥ 3) is expected to perform fine-grained domain alignment as higher-order statistics can approximate more complex, non-Gaussian distributions.  ...  Minimizing the discrepancy of feature distributions between different domains is one of the most promising directions in unsupervised domain adaptation.  ...  Higher-order Statistics The statistics higher than first-order has been successfully used in many classical and deep learn-ing methods (De Lathauwer, Castaing, and Cardoso 2007; Koniusz et al. 2016; Gou  ... 
doi:10.1609/aaai.v34i04.5745 fatcat:geowmlfwjrgtdklzqzu3lsbhjm

Generating adaptive and robust filter sets using an unsupervised learning framework

Mohit Prabhushankar, Dogancan Temel, Ghassan AlRegib
2017 2017 IEEE International Conference on Image Processing (ICIP)  
In this paper, we introduce an adaptive unsupervised learning framework, which utilizes natural images to train filter sets.  ...  Based on experiments, we show that the filter responses span a set in which a monotonicity-based metric can measure both the perceptual dissimilarity of natural images and the similarity of texture images  ...  ZCA whitening is a decorrelating procedure that removes the first and the second order statistics of input data and forces the ensuing learning stage to capture higher order statistics.  ... 
doi:10.1109/icip.2017.8296841 dblp:conf/icip/PrabhushankarTA17 fatcat:4yw775ikqnf2recsbgikurxdta

Unsupervised Learning of P NP P Word Combinations [chapter]

Sofía N. Galicia-Haro, Alexander Gelbukh
2005 Lecture Notes in Computer Science  
We evaluate the possibility to learn, in an unsupervised manner, a list of idiomatic word combinations of the type preposition + noun phrase + preposition (P NP P), namely, such groups with three or more  ...  simple forms that behave as a whole lexical unit and have semantic and syntactic properties not deducible from the corresponding properties of each simple form, e.g., by means of, in order to, in front  ...  Unsupervised Learning of P NP P Word Combinations.  ... 
doi:10.1007/978-3-540-30586-6_37 fatcat:zxaiekakzbfjzgkn5imogvgmj4

Student Behavior and Performance in Unsupervised Online Quizzes: A Case of Computer Organization Course

Norliza Katuk, Universiti Utara Malaysia, Malaysia,
2019 International Journal of Advanced Trends in Computer Science and Engineering  
Unsupervised online quizzes have been used widely by higher learning institutions as an activity in a blended learning model and found to be a valuable formative assessment tool for students to self-assess  ...  The results of the study suggested that students who frequently access to printed references, access to digital references, and have peer discussion during online quiz taking obtained higher marks for  ...  RESULTS AND DISCUSSIONS The data of the study were analyzed using IBM SPSS Statistics Version 25.  ... 
doi:10.30534/ijatcse/2019/69852019 fatcat:mwb2tbivzjdhrfs4qidgupz35e

Unsupervised Texture Classification And Segmentation

V.P.Subramanyam Rallabandi, S.K.Sett
2007 Zenodo  
When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images.  ...  We apply this technique to the problem of unsupervised texture classification and segmentation.  ...  Each class is learned in an unsupervised fashion and contains the statistical intrinsic structure of its image texture.  ... 
doi:10.5281/zenodo.1332180 fatcat:gx6hru6j7bbejeferxj4aqpame

Independent Component Analysis [chapter]

Xudong Xie, Kin-Man Lam, Qionghai Dai, Xiaoming Peng, Jian Yang, Jingyu Yang, Xin Geng, Kate Smith-Miles, Seungjin Choi, Sarat C. Dass, S. Pankanti, S. Prabhakar (+44 others)
2009 Encyclopedia of Biometrics  
PCA Linear transform Compression (dimensionality reduction) Classification (feature extraction) PCA Second-order statistics (Gaussian) Linear orthogonal transform Optimal coding in MS sense ICA Higher-order  ...  Theorem The steepest descent direction of J (w) in a Riemannian space is given by / 78 Theory and Preliminaries for ICA Algorithms for ICA Beyond ICA Applications of ICA Criteria Unsupervised Learning  ...  Theory and Preliminaries for ICA Algorithms for ICA Beyond ICA Applications of ICA Criteria Unsupervised Learning Algorithms Algebraic Algorithms More Algebraic Algorithms FOBI: 4th-order moment  ... 
doi:10.1007/978-0-387-73003-5_305 fatcat:odqmmnym6zddpfvggdues6fsie

NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay

Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan Qi
2018 2018 IEEE International Conference on Big Data (Big Data)  
Different from the manual review for credit card application in conventional banks, the credit limit of Ant Credit Pay is automatically offered to users based on the knowledge learned from big data.  ...  Similar to credit card, loan default is one of the major risks of this credit product.  ...  The higher value of KS statistic means the better performance. B. Experimental Results As shows in Figure 3 (a), BenchDP outperforms NetDP.  ... 
doi:10.1109/bigdata.2018.8622169 dblp:conf/bigdataconf/LinZZLFFYQ18 fatcat:jn6klcbb5veanjmrahhziyxlb4

Diagnostic Value of SonoVue Contrast-Enhanced Ultrasonography in Nipple Discharge Based on Artificial Intelligence

Ling Guo, Le Sun
2021 Journal of Healthcare Engineering  
This paper aims to explore the application value of SonoVue contrast-enhanced ultrasonography based on deep unsupervised learning (DNS) in the diagnosis of nipple discharge.  ...  In this paper, a new model (ODNS) is proposed based on the unsupervised learning model and stack self-coding network.  ...  compared, as shown in Figure 7 . e maximum Acc value of unsupervised deep learning model is 96.67 ± 0.45%, which is significantly higher than 91.52 ± 0.57%, 92.08 ± 0.33%, and 94.35 ± 0.64% of perceptron  ... 
doi:10.1155/2021/2961697 pmid:34956565 pmcid:PMC8702308 fatcat:gxqwvd5rnvdobm5ck4ghym6rxe

High-order Connectomic Manifold Learning for Autistic Brain State Identification [chapter]

Mayssa Soussia, Islem Rekik
2017 Lecture Notes in Computer Science  
We benchmark our ASD identification method against supervised and unsupervised state-of-the-art methods, while depicting the most discriminative high-and low-order relationships between morphological regions  ...  and high-order levels.  ...  High-order Connectomic Manifold Learning for Unsupervised Clustering of Autistic and Healthy BrainsIn this section, we present the high-order connectomic manifold learning for ASD identification using  ... 
doi:10.1007/978-3-319-67159-8_7 fatcat:cjpcvux3l5bjvpg5hqgonjkcvy

Rethinking Sampling Strategies for Unsupervised Person Re-identification [article]

Xumeng Han, Xuehui Yu, Guorong Li, Jian Zhao, Gang Pan, Qixiang Ye, Jianbin Jiao, Zhenjun Han
2021 arXiv   pre-print
Group sampling regulates the representation learning process, which enhances statistical stability for feature representation in a progressive fashion.  ...  Unsupervised person re-identification (re-ID) remains a challenging task.  ...  Unsupervised Person re-ID Unsupervised person re-ID aims to learn effective features for unlabeled person image datasets.  ... 
arXiv:2107.03024v2 fatcat:ft536gktn5ci7gep6zmq7jvkgm
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