Dissimilarity-Based Sparse Subset Selection Elhamifar, Ehsan; Sapiro, Guillermo; Sastry, S. Shankar
IEEE transactions on pattern analysis and machine intelligence,
2016-Nov.-1, 2016-11-00, 2016-11-1, 20161101, Letnik:
38, Številka:
11
Journal Article
Recenzirano
Finding an informative subset of a large collection of data points or models is at the center of many problems in computer vision, recommender systems, bio/health informatics as well as image and ...natural language processing. Given pairwise dissimilarities between the elements of a `source set' and a `target set,' we consider the problem of finding a subset of the source set, called representatives or exemplars, that can efficiently describe the target set. We formulate the problem as a row-sparsity regularized trace minimization problem. Since the proposed formulation is, in general, NP-hard, we consider a convex relaxation. The solution of our optimization finds representatives and the assignment of each element of the target set to each representative, hence, obtaining a clustering. We analyze the solution of our proposed optimization as a function of the regularization parameter. We show that when the two sets jointly partition into multiple groups, our algorithm finds representatives from all groups and reveals clustering of the sets. In addition, we show that the proposed framework can effectively deal with outliers. Our algorithm works with arbitrary dissimilarities, which can be asymmetric or violate the triangle inequality. To efficiently implement our algorithm, we consider an Alternating Direction Method of Multipliers (ADMM) framework, which results in quadratic complexity in the problem size. We show that the ADMM implementation allows to parallelize the algorithm, hence further reducing the computational time. Finally, by experiments on real-world datasets, we show that our proposed algorithm improves the state of the art on the two problems of scene categorization using representative images and time-series modeling and segmentation using representative models.
Robust Face Recognition via Sparse Representation Wright, J.; Yang, A.Y.; Ganesh, A. ...
IEEE transactions on pattern analysis and machine intelligence,
02/2009, Letnik:
31, Številka:
2
Journal Article
Recenzirano
Odprti dostop
We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one ...of classifying among multiple linear regression models and argue that new theory from sparse signal representation offers the key to addressing this problem. Based on a sparse representation computed by C 1 -minimization, we propose a general classification algorithm for (image-based) object recognition. This new framework provides new insights into two crucial issues in face recognition: feature extraction and robustness to occlusion. For feature extraction, we show that if sparsity in the recognition problem is properly harnessed, the choice of features is no longer critical. What is critical, however, is whether the number of features is sufficiently large and whether the sparse representation is correctly computed. Unconventional features such as downsampled images and random projections perform just as well as conventional features such as eigenfaces and Laplacianfaces, as long as the dimension of the feature space surpasses certain threshold, predicted by the theory of sparse representation. This framework can handle errors due to occlusion and corruption uniformly by exploiting the fact that these errors are often sparse with respect to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training images to maximize robustness to occlusion. We conduct extensive experiments on publicly available databases to verify the efficacy of the proposed algorithm and corroborate the above claims.
This article studies security decisions of identical plant-controller systems, when their security is interdependent due to network induced risks. Each plant is modeled by a discrete-time stochastic ...linear system, with the systems controlled over a shared communication network. We formulate the problem of security choices of the individual system operators (also called players) as a non-cooperative game. We consider a two-stage game, in which on the first stage the players decide whether to invest in security or not; and on the second stage, they apply control inputs to minimize the average operational costs. We characterize the equilibria of the game, which includes the determination of the individually optimal security levels. Next, we solve the problem of finding the socially optimal security levels. The presence of interdependent security causes a negative externality, and the individual players tend to under invest in security relative to the social optimum. This leads to a gap between the individual and the socially optimal security levels for a wide range of security costs. From our results, regulatory impositions to incentivize higher security investments are desirable.
Objective: Heartbeat detection remains central to cardiac disease diagnosis and management, and is traditionally performed based on electrocardiogram (ECG). To improve robustness and accuracy of ...detection, especially, in certain critical-care scenarios, the use of additional physiological signals such as arterial blood pressure (BP) has recently been suggested. Therefore, estimation of heartbeat location requires information fusion from multiple signals. However, reported efforts in this direction often obtain multimodal estimates somewhat indirectly, by voting among separately obtained signal-specific intermediate estimates. In contrast, we propose to directly fuse information from multiple signals without requiring intermediate estimates, and thence estimate heartbeat location in a robust manner. Method: We propose as a heartbeat detector, a convolutional neural network (CNN) that learns fused features from multiple physiological signals. This method eliminates the need for hand-picked signal-specific features and ad hoc fusion schemes. Furthermore, being data-driven, the same algorithm learns suitable features from arbitrary set of signals. Results: Using ECG and BP signals of PhysioNet 2014 Challenge database, we obtained a score of 94%. Furthermore, using two ECG channels of MIT-BIH arrhythmia database, we scored 99.92%. Both those scores compare favorably with previously reported database-specific results. Also, our detector achieved high accuracy in a variety of clinical conditions. Conclusion: The proposed CNN-based information fusion (CIF) algorithm is generalizable, robust and efficient in detecting heartbeat location from multiple signals. Significance: In medical signal monitoring systems, our technique would accurately estimate heartbeat locations even when only a subset of channels are reliable.
The classical function of Vitamin D, which involves mineral balance and skeletal maintenance, has been known for many years. With the discovery of vitamin D receptors in various tissues, several ...other biological functions of vitamin D are increasingly recognized and its role in many human diseases like cancer, diabetes, hypertension, cardiovascular, and autoimmune and dermatological diseases is being extensively explored. The non-classical function of vitamin D involves regulation of cellular proliferation, differentiation, apoptosis, and innate and adaptive immunity. In this review, we discuss and summarize the latest findings on the non-classical functions of vitamin D at the cellular/molecular level and its role in complex human diseases.
Ohmic heating has been revived in the 1980s and after a brief pause in the 1990s, has reemerged in a number of food processing applications. An offshoot, Moderate Electric Field (MEF) processing has ...emerged from the recognition that even relatively mild electric fields themselves have significant effects on food and other biological materials. A number of significant research areas have been identified in this connection. In addition, a discussion is provided on priorities for federal research funding, including the need for basic research balanced with industry relevance, availability of pilot facilities for development of new technologies, and potentially, a mechanism for helping inventions survive through the initial ``Valley of Death'' phase.
Noise Tolerance Under Risk Minimization Manwani, N.; Sastry, P. S.
IEEE transactions on cybernetics,
2013-June, 2013-Jun, 2013-6-00, 20130601, Letnik:
43, Številka:
3
Journal Article
Recenzirano
In this paper, we explore noise-tolerant learning of classifiers. We formulate the problem as follows. We assume that there is an unobservable training set that is noise free. The actual training set ...given to the learning algorithm is obtained from this ideal data set by corrupting the class label of each example. The probability that the class label of an example is corrupted is a function of the feature vector of the example. This would account for most kinds of noisy data one encounters in practice. We say that a learning method is noise tolerant if the classifiers learnt with noise-free data and with noisy data, both have the same classification accuracy on the noise-free data. In this paper, we analyze the noise-tolerance properties of risk minimization (under different loss functions). We show that risk minimization under 0-1 loss function has impressive noise-tolerance properties and that under squared error loss is tolerant only to uniform noise; risk minimization under other loss functions is not noise tolerant. We conclude this paper with some discussion on the implications of these theoretical results.
This paper considers control and estimation problems where the sensor signals and the actuator signals are transmitted to various subsystems over a network. In contrast to traditional control and ...estimation problems, here the observation and control packets may be lost or delayed. The unreliability of the underlying communication network is modeled stochastically by assigning probabilities to the successful transmission of packets. This requires a novel theory which generalizes classical control/estimation paradigms. The paper offers the foundations of such a novel theory. The central contribution is to characterize the impact of the network reliability on the performance of the feedback loop. Specifically, it is shown that for network protocols where successful transmissions of packets is acknowledged at the receiver (e.g., TCP-like protocols), there exists a critical threshold of network reliability (i.e., critical probabilities for the successful delivery of packets), below which the optimal controller fails to stabilize the system. Further, for these protocols, the separation principle holds and the optimal LQG controller is a linear function of the estimated state. In stark contrast, it is shown that when there is no acknowledgement of successful delivery of control packets (e.g., UDP-like protocols), the LQG optimal controller is in general nonlinear. Consequently, the separation principle does not hold in this circumstance
Storage is known to change the physical and chemical properties of produce. The purpose of this study was to determine the effect of applying edible coatings on freshly harvested potatoes under ...different storage conditions. The effects of seven edible coating combination formulations with zein, alginate, potato starch, and essential oil on three potato tuber cultivars, Rio Grande Russet (RG), Yukon Gold (YG), and Purple Majesty (PM), were studied over two seasons (2017 and 2018). The treated tubers were stored in three conditions: high relative humidity storage conditions (HRHSC) at 90% ± 5% RH and 5 °C ± 1 °C; low relative humidity storage conditions (LRHSC) at 55% ± 5% RH and 5 °C ± 1 °C; and room temperature. Most of the edible coatings used for potatoes have limited effects on quality properties in the HRHSC, reasonable effects in RG and PM (weight loss and firmness) in LRHSC, and noticeably favorable effects at room temperature in RG and PM (weight loss and sprout inhibition). Alginate with essential oil and potato starch with alginate formulation significantly improved sensory properties in all cultivars. There was no significant change in the levels of total phenolics and reducing sugars due to the application of coatings.
•Edible coatings efficacy increases under the low relative humidity storage at room temperature.•Edible coatings have limited effects on potato quality under the high relative humidity storage.•Edible coatings improve the sensory properties, particularly with colored skin potatoes.•Edible coatings increased the shelf life of tubers at room temperature by delaying sprouting.
Glass is a microscopically disordered, solid form of matter that results
when a fluid is cooled or compressed in such a manner that it does not crystallize.
Almost all types of materials are capable ...of glass formation, including polymers,
metal alloys and molten salts. Given such diversity, general principles by
which different glass-forming materials can be systematically classified are
invaluable. One such principle is the classification of glass-formers according
to their fragility. Fragility measures the rapidity with which
a liquid's properties (such as viscosity) change as the glassy state is approached.
Although the relationship between the fragility, configurational entropy and
features of the energy landscape (the complicated dependence of energy on
configuration) of a glass-former have been analysed previously,
a detailed understanding of the origins of fragility is lacking. Here I use
simulations to analyse the relationship between fragility and quantitative
measures of the energy landscape for a model liquid whose fragility depends
on its bulk density. The results reveal that fragility depends on changes
in the vibrational properties of individual energy minima in addition to their
total number and spread in energy. A thermodynamic expression for fragility
is derived, which is in quantitative agreement with kinetic fragilities obtained
from the liquid's diffusivity.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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