E-print Articles

E-print Articles

 

Recent Submissions

  • Aravind, N. R.; Misra, Neeldhara; Mittal, Harshil (Cornell University Library, 2022-03)
    We introduce a generalization of "Solo Chess", a single-player variant of the game that can be played on this http URL. The standard version of the game is played on a regular 8 x 8 chessboard by a single player, with only ...
  • Singh, Shruti; Singh, Mayank (Cornell University Library, 2022-03)
    Language models are increasingly becoming popular in AI-powered scientific IR systems. This paper evaluates popular scientific language models in handling (i) short-query texts and (ii) textual neighbors. Our experiments ...
  • Adhikary, Rishiraj; Lodhavia, Dhruvi; Francis, Chris; Patil, Rohit; Srivastava, Tanmay; Khanna, Prerna; Batra, Nipun; Breda, Joe; Peplinski, Jacob; Patel, Shwetak (Cornell University Library, 2022-01)
    According to the World Health Organisation (WHO), 235 million people suffer from respiratory illnesses and four million people die annually due to air pollution. Regular lung health monitoring can lead to prognoses about ...
  • Misra, Neeldhara; Nanoti, Saraswati Girish (Cornell University Library, 2022-01)
    Eternal Vertex Cover problem is a dynamic variant of the vertex cover problem. We have a two player game in which guards are placed on some vertices of a graph. In every move, one player (the attacker) attacks an edge. In ...
  • Kumar, Jatin; Mastan, Indra Deep; Raman, Shanmuganathan (Cornell University Library, 2021-11)
    In this paper, we present a Fast Motion Deblurring-Conditional Generative Adversarial Network (FMD-cGAN) that helps in blind motion deblurring of a single image. FMD-cGAN delivers impressive structural similarity and visual ...
  • Misra, Neeldhara; Nayak, Debanuj (Cornell University Library, 2021-11)
    We study the computational complexity of finding fair allocations of indivisible goods in the setting where a social network on the agents is given. Notions of fairness in this context are "localized", that is, agents are ...
  • Anand, Mrinal; Garg, Aditya (Cornell University Library, 2021-11)
    We witnessed a massive growth in the supervised learning paradigm in the past decade. Supervised learning requires a large amount of labeled data to reach state-of-the-art performance. However, labeling the samples requires ...
  • Anand, Mrinal; Harilal, Nidhin; Kumar, Chandan; Raman, Shanmuganathan (Cornell University Library, 2021-10)
    High dynamic range (HDR) videos provide a more visually realistic experience than the standard low dynamic range (LDR) videos. Despite having significant progress in HDR imaging, it is still a challenging task to capture ...
  • Singh, Prajwal; Sadekar, Kaustubh; Raman, Shanmuganathan (Cornell University Library, 2021-10)
    Point cloud is an efficient way of representing and storing 3D geometric data. Deep learning algorithms on point clouds are time and memory efficient. Several methods such as PointNet and FoldingNet have been proposed for ...
  • Kayal, Pratik; Anand, Mrinal; Desai, Harsh; Singh, Mayank (Cornell University Library, 2021-05)
    Tables present important information concisely in many scientific documents. Visual features like mathematical symbols, equations, and spanning cells make structure and content extraction from tables embedded in research ...
  • Desai, Harsh; Kayal, Pratik; Singh, Mayank (Cornell University, 2021-05)
    Information Extraction (IE) from the tables present in scientific articles is challenging due to complicated tabular representations and complex embedded text. This paper presents TabLeX, a large-scale benchmark dataset ...
  • Malaviya, Jayesh (Cornell University Library, 2021-04)
    The event sequence of many diverse systems is represented as a sequence of discrete events in a continuous space. Examples of such an event sequence are earthquake aftershock events, financial transactions, e-commerce ...
  • Sadasivan, Vinu Sankar; Dasgupta, Anirban (Cornell University Library, 2021-02)
    Curriculum learning is a training strategy that sorts the training examples by some measure of their difficulty and gradually exposes them to the learner to improve the network performance. In this work, we propose two ...
  • Misra, Neeldhara; Sonar, Chinmay; Vaidyanathan, P. R.; Vaish, Rohit (Cornell University Library, 2021-01)
    We study fair resource allocation under a connectedness constraint wherein a set of indivisible items are arranged on a path and only connected subsets of items may be allocated to the agents. An allocation is deemed fair ...
  • Sadekar, Kaustubh; Singh, Prajwal; Raman, Shanmuganathan (Cornell University Library, 2021-01)
    Handwritten document image binarization is a challenging task due to high diversity in the content, page style, and condition of the documents. While the traditional thresholding methods fail to generalize on such challenging ...
  • Chhaya, Rachit; Choudhari, Jayesh; Dasgupta, Anirban; Shit, Supratim (Cornell University Library, 2020-12)
    We present algorithms that create coresets in an online setting for clustering problems according to a wide subset of Bregman divergences. Notably, our coresets have a small additive error, similar in magnitude to the ...
  • Mastan, Indra Deep; Raman, Shanmuganathan (Cornell University Library, 2020-12)
    We consider the generic deep image enhancement problem where an input image is transformed into a perceptually better-looking image. Recent methods for image enhancement consider the problem by performing style transfer ...
  • Mastan, Indra Deep; Raman, Shanmuganathan (Cornell University Library, 2020-12)
    One of the major challenges of style transfer is the appropriate image features supervision between the output image and the input (style and content) images. An efficient strategy would be to define an object map between ...
  • Sawant, Shriraj P.; Singh, Shruti (Cornell University Library, 2020-12)
    Attention is a complex and broad concept, studied across multiple disciplines spanning artificial intelligence, cognitive science, psychology, neuroscience, and related fields. Although many of the ideas regarding attention ...
  • Jain, Harshil; Patil, Rohit; Mastan, Indra Deep; Raman, Shanmuganathan (Cornell University Library, 2020-11)
    Blind motion deblurring involves reconstructing a sharp image from an observation that is blurry. It is a problem that is ill-posed and lies in the categories of image restoration problems. The training data-based methods ...

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