39255438
Design of progressive auctions for procurement based on Lagrangian relaxation
Auction mechanisms have been found successful in implementing e-procurement, with the buyer as the auctioneer and the sellers as the bidders. Single round auctions are prevalently used in e-procurement, in which the suppliers submit sealed bids in response to the buyer's request-for-quote. The bid evaluation problem faced by the buyer is an optimization problem that selects the winning bids to minimize the cost of procurement. Though these auction types are advantageous in many scenarios, progressive auctions (multiple rounds) are preferred in terms of information elicitation and bid preparation. This paper demonstrates the design of progressive auctions, from their single-round counterparts, using Lagrangian relaxation. In particular, we show that an appropriate algorithm for a judiciously selected Lagrangian relaxation of the bid evaluation problem, can help in designing a progressive auction. The procurement of multiple units of a single item is considered with linear and piecewise linear supply curves.
14041261
Discount auctions for procuring heterogeneous items
e-Procurement is an Internet based business process for sourcing direct or indirect materials. In this paper we propose an auction mechanism called as discount auctions for procuring multiple items. The bid from a supplier consists of individual costs for each of the items and a discount function, which specifies the discount over the number of items. We show that such a bid is more meaningful and cost effective in terms of bid preparation and communication in common procurement scenarios. The bid evaluation problem is modeled as a mixed integer linear program and various structures in the problem that can be exploited for developing algorithms are explored. A heuristic based on linear programming relaxation is proposed to determine a feasible solution to the problem and its closeness to optimality is studied with computational experiments.
12946117
Searching One Billion Web Images by Content: Challenges and Opportunities
Although content-based image retrieval has been studied for decades, most commercial image search engines are still text-based. However, there is a growing demand for techniques to support content-based image search at Web scale. In this paper, we propose an ambitious goal to searching one billion Web images by content, and discuss the major challenges and opportunities. We also present several important applications that can be greatly benefited by techniques to enable Web-scale image search by content. These applications include image copyright infringement detection, street-side photo search, and searchbased image annotation. We believe that the insights presented in the paper are enlightening to researchers in this field, and any breakthrough we make in this space will lead to many impactful applications in the future.
10740927
Photo-to-search: using multimodal queries to search the web from mobile devices
Nowadays, mobile phones with the digital camera are getting more and more popular. With necessary technologies, they are possible to become a powerful tool to search the Web on the go. Most Web search engines only support text queries. Therefore, users have to convert their information needs into words. However, it is sometimes difficult to describe the needs in text and the text input is inconvenient on small devices. To solve the problem, we propose a system named Photo-to-Search which allows users to input multimodal queries. Particularly, we study queries with captured images and optional text messages in this paper. For example, the user can simply take a photo of the flower and input a few terms like "flower". Textually relevant Web images are retrieved according to the query terms. Afterwards, the snapped picture is compared with these images by the CBIR (Content Based Image Retrieval) method. According to the context of the visually similar images, related key phrases are extracted. Finally, the search results are returned in multiple forms. Our system can also search for very similar images on the Web, such as movie posters or photos of film stars, to find related information. Experimental results on the large scale data showed our system achieved satisfactory efficiency and performance.
1448018
Generating velocity tuning by asymmetric recurrent connections
Asymmetric lateral connections are one possible mechanism that can account for the direction selectivity of cortical neurons. We present a mathematical analysis for a class of these models. Contrasting with earlier theoretical work that has relied on methods from linear systems theory, we study the network's nonlinear dynamic properties that arise when the threshold nonlinearity of the neurons is taken into account. We show that such networks have stimulus-locked traveling pulse solutions that are appropriate for modeling the responses of direction selective cortical neurons. In addition, our analysis shows that outside a certain regime of stimulus speeds the stability of this solutions breaks down giving rise to another class of solutions that are characterized by specific spatio-temporal periodicity. This predicts that if direction selectivity in the cortex is mainly achieved by asymmetric lateral connections lurching activity waves might be observable in ensembles of direction selective cortical neurons within appropriate regimes of the stimulus speed.
5342027
Attention model based progressive image transmission
Progressive image transmission provides a convenient user interface when images are transmitted slowly. However, most of the existing PIT techniques only consider the objective quality of the reconstructed image. Here we present an attention model based progressive image transmission approach to improve the subjective quality of the transmission process. We use both bottom-up image features and top-down semantic information to extract the regions of interest and also propose a new ROI coding scheme based on JPEG2000 to control the trade-off between the transmission of ROI and background. Experiments have shown the efficiency of our approach
10678156
Detecting The Sufficient Display Resolution For Image Browsing
In image browsing, the resolution greatly affects user’s experience. If an image is down-scaled too much, a considerable amount of information within it will be lost. In this paper, we studied the problem of "What is a sufficient display resolution or scale for an image or an image region?" This problem arises in many real-life applications including image browsing on mobile devices, image adaptation and progressive image delivery. Kullback-Leibler (K-L) distance is employed to measure the information loss and the sufficient display scale is selected based on the information loss curve during image down-sampling. Since the images are presented to viewers finally, some visual characteristics are also taken into account to ensure the precision of the measurement. A user study was carried out to evaluate the performance of our approach. Experimental results show that the approach is in good accord with human perception.