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Learning Theory

with Ido Nachum, Jan Hązła, and Michael Gastpar (all @EPFL)

with Elad Domanovitz and Tal Philosof (Samsung Research)

A Johnson–Lindenstrauss framework for randomly initialized CNNs

Information Theory & Computer Communications

The information velocity of packet-erasure links

About the Lab

The research carried in the lab is mathematically focused and spans the broad areas of Information Theory, Communications, Control Theory, Signal Processing, Statistics, and Learning Theory.

   In particular, we study various aspects of causality: measures of causality, efficacy, and dependence, as well as distilling them via learning; applications with causality constraints: low-delay communications, real-time signal processing, and control.

Some Recent Works

Learning Theory

A Johnson–Lindenstrauss framework for randomly initialized CNNs

with Ido Nachum, Jan Hązła, and Michael Gastpar (all @EPFL)

Information Theory & Computer Communications

The information velocity of packet-erasure links

with Elad Domanovitz and Tal Philosof (Samsung Research)

Communications & Signal Processing

Energy-limited joint source–channel coding via analog pulse position modulation

with Omri Lev

Control Theory & Learning Theory

Learning-based attacks in cyber-physical systems

with Mohammad Javad Khojasteh, Massimo Franceschetti, and Tara Javidi (all @UCSD)

Statistical Signal Processing

Monotonicty of the trace–inverse of covariance submatrices and two-sided prediction

with Arie Yeredor and Ram Zamir

Anatoly Khina

Principal investigator

Contact Us

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If you're interested in the math behind systems research (communications, signal processing, statistics, control theory, information theory, or learning theory), let us know!

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Postdoc, PhD, MSc, and BSc positions are available.

Email: anatolyk@tau.ac.il
Tel: +972-(3)-640-7195

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