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469 research outcomes, page 2 of 47
  • publication . Other literature type . Preprint . Article . 2016
    Open Access English
    Authors:
    Leenoy Meshulam; Jeffrey L. Gauthier; Carlos D. Brody; David W. Tank; William Bialek;
    Project: NSF | Emerging Frontiers of Sci... (0939370), NSF | Theoretical Physics of Bi... (1305525), NSF | BRAIN EAGER: Toward a The... (1451171)

    Summary Discussions of the hippocampus often focus on place cells, but many neurons are not place cells in any given environment. Here we describe the collective activity in such mixed populations, treating place and non-place cells on the same footing. We start with op...

  • publication . Conference object . Article . Preprint . 2012
    Open Access
    Authors:
    Merhav, Neri; Szpankowski, Wojciech;
    Publisher: IEEE
    Project: NSF | Collaborative Research: I... (0830140), NSF | Emerging Frontiers of Sci... (0939370)

    It is known that for memoryless sources, the average and maximal redundancy of fixed-to-variable length codes, such as the Shannon and Huffman codes, exhibit two modes of behavior for long blocks. It either converges to a limit or it has an oscillatory pattern, dependin...

  • publication . Article . 2011
    Open Access English
    Authors:
    Narayanan Tejaswini; Gersten Merril; Subramaniam Shankar; Grama Ananth;
    Publisher: Springer Nature
    Project: NSF | CDI-Type II: Hierarchiaca... (0835541), NSF | Biochemical Pathways Work... (0641037), NSF | Emerging Frontiers of Sci... (0939370)

    Abstract Background Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is ...

  • publication . Preprint . 2019
    Open Access English
    Authors:
    Lu, Yawei; Chen, Wei; Poor, H. Vincent;
    Project: NSF | Emerging Frontiers of Sci... (0939370), NSF | CIF: Medium: Collaborativ... (1513915)

    Recently coded caching has emerged as a promising means to handle continuously increasing wireless traffic. However, coded caching requires users to cooperate in order to minimize the overall transmission rate. How users with heterogeneous preferences cooperate in coded...

  • publication . Preprint . 2020
    Open Access English
    Authors:
    Fountoulakis, K.; Liu, M.; Gleich, D. F.; Mahoney, M. W.;
    Project: NSERC , NSF | Emerging Frontiers of Sci... (0939370), NSF | BIGDATA: F: Models, Algor... (1546488)

    Comment: 71 Pages, 21 Figures

  • publication . Preprint . 2020
    Open Access English
    Authors:
    Hu, Ye; Chen, Mingzhe; Saad, Walid; Poor, H. Vincent; Cui, Shuguang;
    Project: NSF | Emerging Frontiers of Sci... (0939370)

    Comment: 6 pages, Fig.4

  • publication . Conference object . Article . Preprint . 2017
    Open Access
    Authors:
    Ehsan Shafieepoorfard; Maxim Raginsky;
    Publisher: IEEE
    Project: NSF | Emerging Frontiers of Sci... (0939370), NSF | CAREER: An Information-Th... (1254041)

    Comment: 12 pages, double-column format, accepted to IEEE Transactions on Information Theory

  • publication . Book
    Open Access
    Authors:
    Monika Piazzesi;
    Project: NSF | Emerging Frontiers of Sci... (0939370)
  • publication . Preprint . 2012
    Open Access English
    Authors:
    Kim, Kyoung-Dae; Mitra, Sayan; Kumar, P. R.;
    Project: NSF | CPS: Medium: Collaborativ... (1035340), NSF | CPS: Small: Delays, Clock... (1035378), NSF | Emerging Frontiers of Sci... (0939370)

    We define a special class of hybrid automata, called Deterministic and Transversal Linear Hybrid Automata (DTLHA), whose continuous dynamics in each location are linear time-invariant (LTI) with a constant input, and for which every discrete transition up to a given bou...

  • publication . Preprint . 2019
    Open Access English
    Authors:
    Devlin, Summer; Singh, Chandan; Murdoch, W. James; Yu, Bin;
    Project: NSF | Emerging Frontiers of Sci... (0939370), NSF | BIGDATA: F: Scalable and ... (1741340), NSERC

    Tree ensembles, such as random forests and AdaBoost, are ubiquitous machine learning models known for achieving strong predictive performance across a wide variety of domains. However, this strong performance comes at the cost of interpretability (i.e. users are unable ...

469 research outcomes, page 2 of 47
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