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Events
Workshop on Distributed Computing in 6G IoT Networks
with Â鶹´«Ã½AV International Conference on Advanced Networks and Telecommunications Systems (ANTS) 2024 15-18 December 2024, Indian Institute of Technology Guwahati, Assam, India
Australasian Summer School: Recent Trends in Algorithms
Free 4-day Australasian Summer School on "Recent Trends in Algorithms" at the University of Sydney, for undergraduate and postgraduate students, on Algorithmic Fairness, Quantum Computing, Data Structures, and Privacy. Student travel funding available!
Machine Learning and Compression Workshop @ NeurIPS 2024
The workshop solicits original research in the intersection of machine learning, data/model compression, and more broadly information theory. We look forward to your participation and contributions!
Events and meeting: Events and Meeting
2024 The International Symposium on Information Theory and Its Applications (ISITA2024)
The 2024 International Symposium on Information Theory and Its Applications (ISITA) will be held…
Australasian Summer School: Recent Trends in Algorithms
Free 4-day Australasian Summer School on "Recent Trends in Algorithms" at the University…
Â鶹´«Ã½AV Globecom 2024 Workshop on Channel Coding beyond 5G: Call for Papers
Workshop on Channel Coding beyond 5G (in conjunction with Â鶹´«Ã½AV Globecom 2024) is now open for…
Upcoming Events
Deadline Extension: Â鶹´«Ã½AV-ITW'24
2024 Â鶹´«Ã½AV Information Theory Workshop (ITW)
Â鶹´«Ã½AV International Symposium on Information Theory (ISIT) 2025
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Deadline Extension: Â鶹´«Ã½AV-ITW'24
2024 Â鶹´«Ã½AV Information Theory Workshop (ITW)
Â鶹´«Ã½AV International Symposium on Information Theory (ISIT) 2025
Research In Information Theory
In this article, we consider a particular data structure consisting of a union of several nested low-rank subspaces with missing data entries. Given the rank of each subspace, we treat the data completion problem, i.e., to estimate the missing entries. Starting from the case of two-dimensional data, i.e., matrices, we show that the union of nested subspaces data structure leads to a structured decomposition U = XY where the factor Y has blocks of zeros that are determined by the rank values.
We study hypergraph clustering in the weighted d-uniform hypergraph stochastic block model (d -WHSBM), where each edge consisting of d nodes from the same community has higher expected weight than the edges consisting of nodes from different communities. We propose a new hypergraph clustering algorithm, called CRTMLE, and provide its performance guarantee under the d -WHSBM for general parameter regimes. We show that the proposed method achieves the order-wise optimal or the best existing results for approximately balanced community sizes.
Quantum phenomena provide computing and information handling paradigms that are clearly different and very likely much more powerful than their classical counterparts. Over the past few years, several governments throughout the world have allocated substantial funding aimed at boosting quantum information science. Much progress has been made on the theoretical side, and experiments have been conducted in which quantum computational operations were executed on a small number of quantum bits.