עברית

Dr. Alon Kipnis

Efi Arazi School of Computer Science

Alon Kipnis received the PhD in electrical engineering from Stanford University in 2017. Between 2017-2021 he was a postdoctoral research scholar and a lecturer at the Department of Statistics at Stanford, advised by David Donoho. Dr. Kipnis' research combines mathematical statistics, information theory, and ambitious data science. He is the recipient of numerous fellowships and awards, including the Koret foundation postdoctoral fellowship, Stanford's electrical engineering department fellowship, and a prize from the Wolf Foundation.
David Donoho and Alon Kipnis. (2022). Higher Criticism to Compare Two Large Frequency Tables, with sensitivity to Possible Rare and Weak DifferencesAnnals of Statistics

Alon Kipnis. (2021). Higher criticism for discriminating word frequency tables and testing authorship. Annals of Applied Statistics

Alon Kipnis and David Donoho. (2021). Two-sample testing of discrete distributions under rare/weak perturbations. International Symposium on Information Theory (ISIT)

Alon Kipnis and Galen Reeve. (2021). Gaussian approximation of quantization error for estimation from compressed data. IEEE Transactions on Information Theory

Alon Kipnis, Stefano Rini, and Andrea J. Goldsmith. (2021).The rate-distortion risk in estimation from compressed data. IEEE Transactions on Information Theory.

Alon Kipnis, Yonina Eldar and Andrea Goldsmith. (2021). An information theoretic approach to analog-to-digital compression. In Information-Theoretic Methods in Data Science. Cambridge University Press

Alon Kipnis. (2020). Higher Criticism as an Unsupervised Authorship Discriminator. Working Notes of CLEF

Alon Kipnis and Galen Reeves. (2019). Gaussian approximation of quantization error for estimation from compressed data. IEEE International Symposium on Information Theory (ISIT)

Stefano Rini, Alon Kipnis, Ruiyang Song, and Andrea J. Goldsmith. (2019). The compress-and-estimate coding scheme for Gaussian sources. IEEE Transactions on Wireless Communications

Georgia Murray, Alon Kipnis and Andrea Goldsmith. (2018). Lossy compression of decimated Gaussian random walks. Annual Conference on Information Sciences and Systems (CISS)

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2018). The distortion-rate function of sampled Wiener processes.IEEE Transactions on Information Theory

Alon Kipnis, Galen Reeves and Yonina Eldar. (2018) Single letter formulas for quantized compressed sensing with Gaussian codebooks. IEEE International Symposium on Information Theory (ISIT)

Alon Kipnis, Yonina Eldar and Andrea Goldsmith. (2018). Analog-to-digital compression: a new paradigm for converting signals to bits. IEEE Signal Processing Magazine

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2018). Fundamental distortion limits of analog-to-digital compression. IEEE Transactions on Information Theory

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2017). The distortion rate function of cyclostationary Gaussian processes. IEEE Transactions on Information Theory

Alon Kipnis and John Duchi. (2017). Mean estimation from adaptive one-bit measurements. Annual Conference on Communication, Control, and Computing (Allerton)

Ruyiang Song, Stefano Rini, Alon Kipnis and Andrea Goldsmith. (2017). Compress-and-estimate source coding for a vector Gaussian Source.Information Theory Workshop (ITW)

Alon Kipnis, Galen Reeves, Yonina Eldar and Andrea Goldsmith. (2017). Compressed sensing under optimal quantization. IEEE International Symposium on Information Theory (ISIT)

Alon Kipnis, Stefano Rini and Andrea Goldsmith. (2017). Coding theorems for the compress and estimate source coding problem. IEEE International Symposium on Information Theory (ISIT)

Milind Rao, Alon Kipnis, Tara Javidi, Yonina Eldar and Andrea Goldsmith. (2016). System identification from partial samples: non-asymptotic analysis.IEEE Conference on Decision and Control

Alon Kipnis, Andrea Goldsmith, Yonina Eldar and Tsachy Weissman. (2016) Distortion-rate function of sub-Nyquist sampled Gaussian stationary processes. IEEE Transactions on Information Theory

Ruyiang Song, Stefano Rini, Alon Kipnis and Andrea Goldsmith. (2016). Optimal rate-allocation in multiterminal compress-and-estimate source coding. Information Theory Workshop (ITW)

Alon Kipnis, Yonina Eldar and Andrea Goldsmith. (2016). Information rates of sampled Wiener processes.IEEE International Symposium on Information Theory (ISIT)

Alon Kipnis, Stefano Rini and Andrea Goldsmith. (2016). Multiterminal compress-and-estimate source coding.IEEE International Symposium on Information Theory (ISIT)

Alon Kipnis, Yonina Eldar and Andrea Goldsmith. (2015). Optimal trade-off between sampling rate and quantization precision in A/D conversion. Annual Conference on Communication, Control, and Computing (Allerton)

Alon Kipnis, Stefano Rini and Andrea Goldsmith. (2015). Indirect rate-distortion function of a binary i.i.d source. presented at IEEE Information Theory Workshop

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2015). Optimal trade-off between sampling rate and quantization precision in sigma-delta A/D conversion. International Conference on Sampling Theory and Applications (SampTA)

Mainak Chowdhury, Alon Kipnis and Andrea Goldsmith. (2015). Reliable uncoded communication in the quantized SIMO MAC.IEEE International Symposium on Information Theory (ISIT)

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2015). Sub-Nyquist sampling achieves optimal rate-distortion. IEEE Information Theory Workshop

Daniel Alpay and Alon Kipnis. (2015). Wiener-chaos approach to optimal prediction. Numerical Functional Analysis and Optimization

Alon Kipnis, Andrea Goldsmith and Yonina Eldar. (2014). Gaussian distortion-rate function under sub-Nyquist nonuniform sampling. Annual Conference on Communication, Control, and Computing (Allerton)

Alon Kipnis and Andrea Goldsmith. (2014). Distortion-rate function of Gaussian cyclostationary processes. IEEE International Symposium on Information Theory

Alon Kipnis, Andrea Goldsmith, Tsachy Weissman and Yonina Eldar. (2013). Rate-distortion function of sub-Nyquist sampled Gaussian stationary processes corrupted by noise. Annual Conference on Communication, Control, and Computing (Allerton)

Daniel Alpay and Alon Kipnis. (2013). Generalized white noise space approach to stochastic integration for a class of Gaussian stationary increment processes. Opuscula Mathematica
Higher Criticism as an Unsupervised Authorship Discriminator

Inference from compressed data

Two-sample problem for high-dimensional multinomials and testing authorship