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2014 4th International Workshop on Cognitive Information Processing (CIP)最新文献

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Structured sparse-low rank matrix factorization for the EEG inverse problem 脑电反问题的结构化稀疏-低秩矩阵分解
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844505
Jair Montoya-Martínez, Antonio Artés-Rodríguez, M. Pontil
{"title":"Structured sparse-low rank matrix factorization for the EEG inverse problem","authors":"Jair Montoya-Martínez, Antonio Artés-Rodríguez, M. Pontil","doi":"10.1109/CIP.2014.6844505","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844505","url":null,"abstract":"We consider the estimation of the Brain Electrical Sources (BES) matrix from noisy EEG measurements, commonly named as the EEG inverse problem. We propose a new method based on the factorization of the BES as a product of a sparse coding matrix and a dense latent source matrix. This structure is enforced by minimizing a regularized functional that includes the ℓ21-norm of the coding matrix and the squared Frobenius norm of the latent source matrix. We develop an alternating optimization algorithm to solve the resulting nonsmooth-nonconvex minimization problem. We have evaluated our approach under a simulated scenario consisting on estimating a synthetic BES matrix with 5124 sources. We compare the performance of our method respect to the Lasso, Group Lasso, Sparse Group Lasso and Trace norm regularizers.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126239987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Emotional responses as independent components in EEG 情绪反应是脑电图的独立组成部分
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844509
Camilla Birgitte Falk Jensen, Michael Kai Petersen, J. E. Larsen
{"title":"Emotional responses as independent components in EEG","authors":"Camilla Birgitte Falk Jensen, Michael Kai Petersen, J. E. Larsen","doi":"10.1109/CIP.2014.6844509","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844509","url":null,"abstract":"With neuroimaging studies showing promising results for discrimination of affective responses, the perspectives of applying these to create more personalised interfaces that adapt to our preferences in real-time seems within reach. Additionally the emergence of wireless electroencephalograph (EEG) neuroheadsets and smartphone brainscanners widens the possibilities for this to be used in mobile settings on a consumer level. However the neural signatures of emotional responses are characterized by small voltage changes that would be highly susceptible to noise if captured in a mobile context. Hypothesizing that retrieval of emotional responses in mobile usage scenarios could be enhanced through spatial filtering, we compare a standard EEG electrode-based analysis against an approach based on independent component analysis (ICA). By clustering scalp maps and time series responses we identify neural signatures that are differentially modulated when passively viewing neutral, pleasant and unpleasant images. While early responses can be detected from the raw EEG signal, we identify multiple early and late ICA components that are modulated by emotional content. We propose that similar approaches to spatial filtering might allow us to retrieve more robust signals in real-life mobile usage scenarios, and potentially facilitate design of cognitive interfaces that adapt the selection of media to our emotional responses.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122255469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Automatic detection of microphone handling noise 自动检测麦克风处理噪音
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844501
P. Kendrick, T. Cox, Francis F. Li, B. Fazenda, Iain Jackson
{"title":"Automatic detection of microphone handling noise","authors":"P. Kendrick, T. Cox, Francis F. Li, B. Fazenda, Iain Jackson","doi":"10.1109/CIP.2014.6844501","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844501","url":null,"abstract":"Microphone handling noise is a common problem with user-generated content. It can occur when the operator inadvertently knocks or brushes a recording device. Handling noise may be impulsive, where a microphone is knocked, or a more sustained rubbing noise, when the microphone is brushed against something. A detector able to accurately detect handling noises caused by rubbing while recording speech, music or quotidian sounds has been developed. Ensembles of decision trees were trained to classify handling noise level over 23 ms frames; a second ensemble flags frames when the noise may be masked by foreground audio. Aggregation of the detection over 1 s yielded a Matthews correlation coefficient of 0.91.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134536452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Discovering hierarchical structure in normal relational data 发现正常关系数据中的层次结构
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844498
Mikkel N. Schmidt, Tue Herlau, Morten Mørup
{"title":"Discovering hierarchical structure in normal relational data","authors":"Mikkel N. Schmidt, Tue Herlau, Morten Mørup","doi":"10.1109/CIP.2014.6844498","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844498","url":null,"abstract":"Hierarchical clustering is a widely used tool for structuring and visualizing complex data using similarity. Traditionally, hierarchical clustering is based on local heuristics that do not explicitly provide assessment of the statistical saliency of the extracted hierarchy. We propose a non-parametric generative model for hierarchical clustering of similarity based on multifurcating Gibbs fragmentation trees. This allows us to infer and display the posterior distribution of hierarchical structures that comply with the data. We demonstrate the utility of our method on synthetic data and data of functional brain connectivity.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123958615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using the Echo Nest's automatically extracted music features for a musicological purpose 使用Echo Nest的自动提取音乐特征为音乐目的
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844510
J. Andersen
{"title":"Using the Echo Nest's automatically extracted music features for a musicological purpose","authors":"J. Andersen","doi":"10.1109/CIP.2014.6844510","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844510","url":null,"abstract":"This paper sums up the preliminary observations and challenges encountered during my first engaging with the music intelligence company Echo Nest's automatically derived data of more than 35 million songs. The overall purpose is to investigate whether musicologists can draw benefit from Echo Nest's API, and to explore what practical and analytical consideration one should take into account when engaging with the numbers derived from the Echo Nest API. This paper suggests that the Echo Nest API hold a large potential of doing new types of analyses and visualizing the results. But it concurrently argues that a careful and critical approach is requisite, when interpreting the results.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127807466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
A comparative study of two popular families of sparsity-aware adaptive filters 两种流行的稀疏感知自适应滤波器的比较研究
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844507
B. K. Das, L. A. Azpicueta-Ruiz, M. Chakraborty, J. Arenas-García
{"title":"A comparative study of two popular families of sparsity-aware adaptive filters","authors":"B. K. Das, L. A. Azpicueta-Ruiz, M. Chakraborty, J. Arenas-García","doi":"10.1109/CIP.2014.6844507","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844507","url":null,"abstract":"In this paper, we review two families for sparsity-aware adaptive filtering. Proportionate-type NLMS filters try to accelerate filter convergence by assigning each filter weight a different gain that depends on its actual value. Sparsity-norm regularized filters penalize the cost function minimized by the filter using sparsity-promoting norms (such as ℓ0 or ℓ1) and derive new stochastic gradient descent rules from the regularized cost function. We compare both families of algorithms in terms of computational complexity and studying how well they deal with the convergence vs steady-state error tradeoff. We conclude that sparsity-norm regularized filters are computationally less expensive and can achieve a better tradeoff, making them more attractive in principle. However, selection of the strength of the regularization term seems to be a critical element for the good performance of these filters.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115457908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Application of factor graphs to multi-camera fusion for maritime tracking 因子图在多相机海上跟踪融合中的应用
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844515
F. Castaldo, F. Palmieri
{"title":"Application of factor graphs to multi-camera fusion for maritime tracking","authors":"F. Castaldo, F. Palmieri","doi":"10.1109/CIP.2014.6844515","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844515","url":null,"abstract":"Propagation of Gaussian belief messages in factor graphs in normal form is applied to data fusion for tracking moving objects in maritime scenarios, as crowded harbors. The data are yielded by multiple cameras, deployed in the region under surveillance, and AIS system, wherever is available. The track model and the estimates coming from the sensors are integrated bi-directionally, providing a flexible framework for comprehensive inference. The framework is applied to tracking a large cargo ship in a harbor from frames recorded with three commercial cameras.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122093907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Infinite factorial unbounded hidden Markov model for blind multiuser channel estimation 盲多用户信道估计的无限阶乘无界隐马尔可夫模型
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844506
I. Valera, Francisco J. R. Ruiz, F. Pérez-Cruz
{"title":"Infinite factorial unbounded hidden Markov model for blind multiuser channel estimation","authors":"I. Valera, Francisco J. R. Ruiz, F. Pérez-Cruz","doi":"10.1109/CIP.2014.6844506","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844506","url":null,"abstract":"Bayesian nonparametric models allow solving estimation and detection problems with an unbounded number of degrees of freedom. In multiuser multiple-input multiple-output (MIMO) communication systems we might not know the number of active users and the channel they face, and assuming maximal scenarios (maximum number of transmitters and maximum channel length) might degrade the receiver performance. In this paper, we propose a Bayesian nonparametric prior and its associated inference algorithm, which is able to detect an unbounded number of users with an unbounded channel length. This generative model provides the dispersive channel model for each user and a probabilistic estimate for each transmitted symbol in a fully blind manner, i.e., without the need of pilot (training) symbols.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132129319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Robust image denoising in RKHS via orthogonal matching pursuit 基于正交匹配追踪的RKHS鲁棒图像去噪
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844496
P. Bouboulis, G. Papageorgiou, S. Theodoridis
{"title":"Robust image denoising in RKHS via orthogonal matching pursuit","authors":"P. Bouboulis, G. Papageorgiou, S. Theodoridis","doi":"10.1109/CIP.2014.6844496","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844496","url":null,"abstract":"We present a robust method for the image denoising task based on kernel ridge regression and sparse modeling. Added noise is assumed to consist of two parts. One part is impulse noise assumed to be sparse (outliers), while the other part is bounded noise. The noisy image is divided into small regions of interest, whose pixels are regarded as points of a two-dimensional surface. A kernel based ridge regression method, whose parameters are selected adaptively, is employed to fit the data, whereas the outliers are detected via the use of the increasingly popular orthogonal matching pursuit (OMP) algorithm. To this end, a new variant of the OMP rationale is employed that has the additional advantage to automatically terminate, when all outliers have been selected.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121755564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Belief propagation and learning in convolution multi-layer factor graphs 卷积多层因子图的信念传播与学习
2014 4th International Workshop on Cognitive Information Processing (CIP) Pub Date : 2014-05-26 DOI: 10.1109/CIP.2014.6844500
F. Palmieri, A. Buonanno
{"title":"Belief propagation and learning in convolution multi-layer factor graphs","authors":"F. Palmieri, A. Buonanno","doi":"10.1109/CIP.2014.6844500","DOIUrl":"https://doi.org/10.1109/CIP.2014.6844500","url":null,"abstract":"In modeling time series, convolution multi-layer graphs are able to capture long-term dependence at a gradually increasing scale. We present an approach to learn a layered factor graph architecture starting from a stationary latent models for each layer. Simulations of belief propagation are reported for a three-layer graph on a small data set of characters.","PeriodicalId":117669,"journal":{"name":"2014 4th International Workshop on Cognitive Information Processing (CIP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126190120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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