3,156 research outputs found
Reading: Amit Majmudar
No full textBecause of COVID-19 this event is canceled.
Amit Majmudar, a multi-genre author and translator, offers a Sacred Arts Festival reading that explores the concept of Building Bridges.
Co-sponsored by the Department of English and the Sacred Arts Festival
Representation of Dispersed Identity in the Novels of Arundhati Roy and Amit Chaudhuri
Full text linkThis article addresses the issue of dispersed identity and studies various cultural phenomena in which the idea of a horizontal cultural space within a nation seems to be ruptured. The fictional characters of Arundhati Roy and Amit Chaudhuri exhibit a disseminating and dispersed nature of identities. They seem to be trapped in an interstitial space, reflecting the ambivalent nature of nation, national identity and national cultur
Exploring young students creativity: The effect of model eliciting activities
Full text linkThe aim of this paper is to show how engaging students in real-life mathematical situations can stimulate their mathematical creative thinking. We analyzed the mathematical modeling of two girls, aged 10 and 13 years, as they worked on an authentic task involving the selection of a track team. The girls displayed several modeling cycles that revealed their thinking processes, as well as cognitive and affective features that may serve as the foundation for a methodology that uses model-eliciting activities to promote the mathematical creative process
Minimizing Weighted lp-Norm of Flow-Time in the Rejection Model
Full text linkWe consider the online scheduling problem to minimize the weighted ell_p-norm of flow-time of jobs. We study this problem under the rejection model introduced by Choudhury et al. (SODA 2015) - here the online algorithm is allowed to not serve an eps-fraction of the requests. We consider the restricted assignments setting where each job can go to a specified subset of machines. Our main result is an immediate dispatch non-migratory 1/eps^{O(1)}-competitive algorithm for this problem when one is allowed to reject at most eps-fraction of the total weight of jobs arriving. This is in contrast with the speed augmentation model under which no online algorithm for this problem can achieve a competitive ratio independent of p
A Tight Competitive Ratio for Online Submodular Welfare Maximization
Full text linkIn this paper we consider the online Submodular Welfare (SW) problem. In this problem we are given n bidders each equipped with a general non-negative (not necessarily monotone) submodular utility and m items that arrive online. The goal is to assign each item, once it arrives, to a bidder or discard it, while maximizing the sum of utilities. When an adversary determines the items' arrival order we present a simple randomized algorithm that achieves a tight competitive ratio of 1/4. The algorithm is a specialization of an algorithm due to [Harshaw-Kazemi-Feldman-Karbasi MOR`22], who presented the previously best known competitive ratio of 3-2√2≈ 0.171573 to the problem. When the items' arrival order is uniformly random, we present a competitive ratio of ≈ 0.27493, improving the previously known 1/4 guarantee. Our approach for the latter result is based on a better analysis of the (offline) Residual Random Greedy (RRG) algorithm of [Buchbinder-Feldman-Naor-Schwartz SODA`14], which we believe might be of independent interest
Review of Wanderings in India: Australian Perceptions, edited by Rick Hosking and Amit Sarwal
No full textReview of Wanderings in India: Australian Perceptions, edited by Rick Hosking and Amit Sarwa
Temporal Model Adaptation for Person Re-Identification
No full textPerson re-identification is an open and challenging problem in computer vision. Majority of the efforts have been spent either to design the best feature representation or to learn the optimal matching metric. Most approaches have neglected the problem of adapting the selected features or the learned model over time. To address such a problem, we propose a temporal model adaptation scheme with human in the loop. We first introduce a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure. Then, to achieve temporal adaptation with limited human effort, we exploit a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model. Results on three datasets have shown that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%
Re-identification in the function space of feature warps
No full textPerson re-identification in a non-overlapping multicamera scenario is an open challenge in computer vision because of the large changes in appearances caused by variations in viewing angle, lighting, background clutter, and occlusion over multiple cameras. As a result of these variations, features describing the same person get transformed between cameras. To model the transformation of features, the feature space is nonlinearly warped to get the "warp functions". The warp functions between two instances of the same target form the set of feasible warp functions while those between instances of different targets form the set of infeasible warp functions. In this work, we build upon the observation that feature transformations between cameras lie in a nonlinear function space of all possible feature transformations. The space consisting of all the feasible and infeasible warp functions is the warp function space (WFS). We propose to learn a discriminating surface separating these two sets of warp functions in the WFS and to re-identify persons by classifying a test warp function as feasible or infeasible. Towards this objective, a Random Forest (RF) classifier is employed which effectively chooses the warp function components according to their importance in separating the feasible and the infeasible warp functions in the WFS. Extensive experiments on five datasets are carried out to show the superior performance of the proposed approach over state-of-the-art person re-identification methods. We show that our approach outperforms all other methods when large illumination variations are considered. At the same time it has been shown that our method reaches the best average performance over multiple combinations of the datasets, thus, showing that our method is not designed only to address a specific challenge posed by a particular dataset. © 2014 IEEE
Reviewing the Author-Function in the Age of Wikipedia
Full text linkIn Reviewing the Author-Function in the Age of Wikipedia, Amit Ray and Erhardt Graeff examine how wiki technology challenges traditional concepts of authorship and authority in knowledge production. The authors build on poststructuralist theory, particularly Roland Barthes\u27s Death of the Author and Michel Foucault\u27s concept of the author-function, to analyze how wikis destabilize individual authorship in favor of collaborative, community-driven content creation.
The essay argues that wikis represent a fundamental shift from the Romantic notion of the solitary author-genius to what they term the wiki writing process —a dynamic system where traditional roles of reader, writer, and editor blur into a unified community of users. Using Wikipedia as a primary case study, the authors demonstrate how the platform\u27s structure (article, discussion, and history pages) creates a digital palimpsest that archives all contributions while enabling continuous revision.
Through analysis of Wikipedia\u27s editing patterns and community oversight mechanisms, Ray and Graeff show how wikis embody poststructuralist principles in practice, creating what they call serial collaborations that exist in perpetual flux. The authors conclude that wikis represent an evolved form of textual production that realizes Foucault\u27s vision of discourse freed from traditional authorial constraints, offering new possibilities for collaborative knowledge creation while challenging established notions of intellectual authority and ownership
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