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E-print Articles: Recent submissions

  • Simple weak coresets for non-decomposable classification measures 
    Malaviya, Jayesh; Dasgupta, Anirban; Chhaya, Rachit (Cornell University Library, 2023-12)
    While coresets have been growing in terms of their application, barring few exceptions, they have mostly been limited to unsupervised settings. We consider supervised classification problems, and non-decomposable evaluation ...
  • The Frobenius problem for the proth numbers 
    Srivastava, Pranjal; Thakkar, Dhara (Cornell University Library, 2023-11)
    Let n be a positive integer greater than 2. We define \textit{the Proth numerical semigroup}, Pk(n), generated by {k2n+i+1∣i∈N}, where k is an odd positive number and k<2n. In this paper, we introduce the Frobenius problem ...
  • Unveiling the multi-annotation process: examining the influence of annotation quantity and instance difficulty on model performance 
    Kadasi, Pritam; Singh, Mayank (Cornell University Library, 2023-10)
    The NLP community has long advocated for the construction of multi-annotator datasets to better capture the nuances of language interpretation, subjectivity, and ambiguity. This paper conducts a retrospective study to show ...
  • Learning robust deep visual representations from EEG brain recordings 
    Singh, Prajwal; Dalal, Dwip; Vashishtha, Gautam; Miyapuram, Krishna Prasad; Raman, Shanmuganathan (Cornell University Library, 2023-10)
    Decoding the human brain has been a hallmark of neuroscientists and Artificial Intelligence researchers alike. Reconstruction of visual images from brain Electroencephalography (EEG) signals has garnered a lot of interest ...
  • Unlocking model insights: a dataset for automated model card generation 
    Singh, Shruti; Lodwal, Hitesh; Malwat, Husain; Thakur, Rakesh; Singh, Mayank (Cornell University Library, 2023-09)
    Language models (LMs) are no longer restricted to ML community, and instruction-tuned LMs have led to a rise in autonomous AI agents. As the accessibility of LMs grows, it is imperative that an understanding of their ...
  • Modeling interdisciplinary interactions among Physics, Mathematics & Computer Science 
    Hazra, Rima; Singh, Mayank; Goyal, Pawan; Adhikari, Bibhas; Mukherjee, Animesh (Cornell University Library, 2023-09)
    Interdisciplinarity has over the recent years have gained tremendous importance and has become one of the key ways of doing cutting edge research. In this paper we attempt to model the citation flow across three different ...
  • Parameterized aspects of distinct Kemeny rank aggregation 
    De, Koustav; Mittal, Harshil; Dey, Palash; Misra, Neeldhara (Cornell University Library, 2023-09)
    The Kemeny method is one of the popular tools for rank aggregation. However, computing an optimal Kemeny ranking is NP-hard. Consequently, the computational task of finding a Kemeny ranking has been studied under the lens ...
  • Layered symbolic security analysis in DY 
    Bhargavan, Karthikeyan; Bichhawat, Abhishek; Hosseyni, Pedram; Kuesters, Ralf; Pruiksma, Klaas; Schmitz, Guido; Waldmann, Clara; Wurtele, Tim (International Association for Cryptologic Research, 2023-09)
    While cryptographic protocols are often analyzed in isolation, they are typically deployed within a stack of protocols, where each layer relies on the security guarantees provided by the protocol layer below it, and in ...
  • Spartan Bipartite graphs are essentially elementary 
    Misra, Neeldhara; Nanoti, Saraswati Girish (Cornell University, 2023-08)
    We study a two-player game on a graph between an attacker and a defender. To begin with, the defender places guards on a subset of vertices. In each move, the attacker attacks an edge. The defender must move at least one ...
  • The minimum generating set problem 
    Lucchini, Andrea; Thakkar, Dhara (Cornell University Library, 2023-06)
    Let G be a finite group. In order to determine the smallest cardinality d(G) of a generating set of G and a generating set with this cardinality, one should repeat many times the test whether a subset of G of small cardinality ...
  • Improving expressivity of graph neural networks using localization 
    Kumar, Anant; Das, Shrutimoy; Roy, Shubhajit; Maity, Binita; Dasgupta, Anirban (Cornell University Library, 2023-05)
    In this paper, we propose localized versions of Weisfeiler-Leman (WL) algorithms in an effort to both increase the expressivity, as well as decrease the computational overhead. We focus on the specific problem of subgraph ...
  • The isomorphism problem of power graphs and a question of cameron 
    Das, Bireswar; Ghosh, Jinia; Kumar, Anant (Cornell University Library, 2023-05)
    The isomorphism problem for graphs (GI) and the isomorphism problem for groups (GrISO) have been studied extensively by researchers. The current best algorithms for both these problems run in quasipolynomial time. In this ...
  • Algorithms for the minimum generating set problem 
    Das, Bireswar; Thakkar, Dhara (Cornell University Library, 2023-05)
    For a finite group G, the size of a minimum generating set of G is denoted by d(G). Given a finite group G and an integer k, deciding if d(G)≤k is known as the minimum generating set (MIN-GEN) problem. A group G of order ...
  • D-STACK: high throughput DNN inference by effective multiplexing and spatio-temporal scheduling of GPUs 
    Dhakal, Aditya; Kulkarni, Sameer G.; Ramakrishnan, K. K. (Cornell University Library, 2023-03)
    Hardware accelerators such as GPUs are required for real-time, low-latency inference with Deep Neural Networks (DNN). However, due to the inherent limits to the parallelism they can exploit, DNNs often under-utilize the ...
  • EEG2IMAGE: image reconstruction from EEG brain signals 
    Singh, Prajwal; Pandey, Pankaj; Miyapuram, Krishna Prasad; Raman, Shanmuganathan (Cornell University Library, 2023-02)
    Reconstructing images using brain signals of imagined visuals may provide an augmented vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) technology. The recent progress in deep learning ...
  • FedSpectral+: spectral clustering using federated learning 
    Thakkar, Janvi; Joshi, Devvrat (Cornell University Library, 2023-02)
    Clustering in graphs has been a well-known research problem, particularly because most Internet and social network data is in the form of graphs. Organizations widely use spectral clustering algorithms to find clustering ...
  • k-means subclustering: a differentially private algorithm with improved clustering quality 
    Joshi, Devvrat; Thakkar, Janvi (Cornell University Library, 2023-01)
    In today's data-driven world, the sensitivity of information has been a significant concern. With this data and additional information on the person's background, one can easily infer an individual's private data. Many ...
  • Finding and counting patterns in sparse graphs 
    Komarath, Balagopal; Kumar, Anant; Mishra, Suchismita; Sethia, Aditi (Cornell University Library, 2023-01)
    We consider algorithms for finding and counting small, fixed graphs in sparse host graphs. In the non-sparse setting, the parameters treedepth and treewidth play a crucial role in fast, constant-space and polynomial-space ...
  • Detecting moments of distraction during meditation practice based on changes in the EEG signal 
    Pandey, Pankaj; Rodriguez-Larios, Julio; Miyapuram, Krishna Prasad; Lomas, Derek (IEEE, 2022-11)
    Electroencephalography (EEG) enables online monitoring brain activity, which can be used for neurofeedback. One of the growing applications of EEG neurofeedback is to facilitate meditation practice. Specifically, EEG ...
  • Exploring explainability methods for graph neural networks 
    Patel, Harsh; Sahni, Shivam (Cornell University Library, 2022-11)
    With the growing use of deep learning methods, particularly graph neural networks, which encode intricate interconnectedness information, for a variety of real tasks, there is a necessity for explainability in such settings. ...

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