Capacity-achieving Sparse Regression Codes via approximate message passing decoding

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. In this code, the codewords are sparse linear combinations of columns of a design matrix. In this paper, we propose an approximate message passing decoder for sparse superposition codes. The complexity of the decoder scales linearly with the size of the design matrix. The performance of the decoder is rigorously analyzed and it is shown to asymptotically achieve the AWGN capacity. We also provide simulation results to demonstrate the performance of the decoder at finite block lengths, and introduce a power allocation that significantly improves the empirical performance.RV would like to acknowledge support from a Marie Curie Career Integration Grant (GA Number 631489). AG is supported by an EPSRC Doctoral Training Award.This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ISIT.2015.728280

Capacity-Achieving Sparse Superposition Codes via Approximate Message Passing Decoding.

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the AWGN channel at rates approaching the channel capacity. The codebook is defined in terms of a Gaussian design matrix, and codewords are sparse linear combinations of columns of the matrix. In this paper, we propose an approximate message passing decoder for sparse superposition codes, whose decoding complexity scales linearly with the size of the design matrix. The performance of the decoder is rigorously analyzed and it is shown to asymptotically achieve the AWGN capacity with an appropriate power allocation. Simulation results are provided to demonstrate the performance of the decoder at finite blocklengths. We introduce a power allocation scheme to improve the empirical performance, and demonstrate how the decoding complexity can be significantly reduced by using Hadamard design matrices.Comment: 25 pages, 4 figures. IEEE Transactions on Information Theor

West End Broadway: the golden age of the American musical in London by Adrian Wright Woodbridge [London: The Boydell Press, 2012]

Review of West End Broadway: the golden age of the American musical in London by Adrian Wright Woodbridge, London: The Boydell Press, 2012, in Platform: Journal of Theatre and Performing Arts, 7(2) 92-95

Creating musical theatre: conversations with Broadway directors and choreographers by Lyn Cramer [London and New York: Bloomsbury Methuen Drama, 2013]

Review of Creating musical theatre: conversations with Broadway directors and choreographers by Lyn Cramer, London and New York: Bloomsbury Methuen Drama, 2013 in Platform: Journal of Theatre and Performing Arts, 9(1) 77-81

Improved differential privacy for SGD via optimal private linear operators on adaptive streams

CCF-1763786 - National Science Foundation; Apple, Inchttps://arxiv.org/abs/2202.0831

Differentially private model personalization

We study personalization of supervised learning with user-level differential privacy. Consider a setting with many users, each of whom has a training data set drawn from their own distribution Pi . Assuming some shared structure among the problems Pi, can users collectively learn the shared structure---and solve their tasks better than they could individually---while preserving the privacy of their data? We formulate this question using joint, user-level differential privacy---that is, we control what is leaked about each user's entire data set. We provide algorithms that exploit popular non-private approaches in this domain like the Almost-No-Inner-Loop (ANIL) method, and give strong user-level privacy guarantees for our general approach. When the problems Pi are linear regression problems with each user's regression vector lying in a common, unknown low-dimensional subspace, we show that our efficient algorithms satisfy nearly optimal estimation error guarantees. We also establish a general, information-theoretic upper bound via an exponential mechanism-based algorithm.https://proceedings.neurips.cc/paper/2021/hash/f8580959e35cb0934479bb007fb241c2-Abstract.htm

Recycled culture: the significance of intertextuality in twenty-first century musical theatre

The twenty-first century musical is dominated by high-profile adaptations and the recycling of popular texts in a wider trend Graham Allen terms ‘cultural regurgitation’. From Wicked (2003) and Billy Elliot the Musical (2005) to Jersey Boys (2005) and The Book of Mormon (2011), the commercial musical stage is a prominent site of high-profile intertextuality in that it draws from ‘innumerable centres of culture’ to fuel an evening’s entertainment. Given the proliferation of such intertextuality, however, this trend has received little critical attention beyond the detailing of these musicals as ‘safe-bet’ entertainments which attract an audience through the recycling of familiar elements. The primary aim of this thesis is therefore to fill an important gap within existing scholarship by investigating how intertextual references function and operate within contemporary musical theatre. In differentiating the various styles of intertextual reference evidenced within the form, this thesis argues that most twenty-first century musicals either adapt a specific text, capitalise on nostalgia, fashion a bricolage of references or metatheatricalise perceptions of musical theatre as an art form. In doing so, it put forwards the claim that musical theatre invites intertextuality as a diverse layering of textual elements in and of itself. Not only is musical theatre an inherently intertextual form, but it ultimately requires intertextuality to reflect the recycled nature of popular culture more broadly