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Computer Science events calendar in HTTP ICS format for of Google calendars, and for Outlook.

Academic Calendar at Technion site.

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  • Computing the Shapley Value of Tuples in Conjunctive Queries with Negation

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    ??? ?????, 30.8.2020, 11:00
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    ????? ??????? ???: https://technion.zoom.us/j/96838343281
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    Prof. Benny Kimelefeld

    The Shapley value is a conventional and well-studied function for determining the contribution of a player to the coalition in a cooperative game. Among its applications in a plethora of domains, it has recently been proposed to use the Shapley value for quantifying the contribution of a tuple to the result of a database query. In particular, we have a thorough understanding of the tractability frontier for the class of Conjunctive Queries (CQs) and aggregate functions over CQs. It has also been established that a tractable (randomized) multiplicative approximation exists for every union of CQs. Nevertheless, all of these results are based on the monotonicity of CQs. In this work, we investigate the implication of negation on the complexity of Shapley computation, in both the exact and approximate senses. We generalize a known dichotomy to accountfor negated atoms. We also show that negation fundamentally changes the complexity of approximation. We do so by drawing a connection to the problem of deciding whether a tuple is “relevant” to a query, and by analyzing its complexity.

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    How Do You Turn a Degree into a Career?

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    ??? ?????, 1.9.2020, 17:00
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    Zoom Lecture: Registration

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  • Efficient MDP Analysis for Selfish-Mining in Blockchains

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    ??? ?????, 2.9.2020, 11:30
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    ????? ??????? ???: https://technion.zoom.us/j/95908254875
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    Prof. Ittay Eyal and Prof. Aviv Tamar

    A proof of work (PoW) blockchain protocol distributes rewards to its participants, called miners, according to their share of the total computational power. Sufficiently large miners can perform selfish mining - deviate from the protocol to gain more than their fair share. Such systems are thus secure if all miners are smaller than a threshold size so their best response is following the protocol. To find the threshold, one has to identify the optimal strategy for miners of different sizes, i.e., solve a Markov Decision Process (MDP). However, because of the PoW difficulty adjustment mechanism, the miners' utility is a non-linear ratio function. We therefore call this an Average Reward Ratio (ARR) MDP. Sapirshtein et al. were the first to solve ARR MDPs by solving a series of standard MDPs that converge to the ARR MDP solution. We present a novel technique for solving an ARR MDP by solving a single standard MDP. The crux of our approach is to augment the MDP such that it terminates randomly, within an expected number of rounds. We call this Probabilistic Termination Optimization (PTO), and the technique applies to any MDP whose utility is a ratio function. We bound the approximation error of PTO - it is inversely proportional to the expected number of rounds before termination, a parameter that we control. Empirically, PTO's complexity is an order of magnitude lower than the state of the art. PTO can be easily applied to different blockchains. We use it to tighten the bound on the threshold for selfish mining in Ethereum.

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    The 8th Summer School on Cyber and Computer Security

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    ??? ???, 7.9.2020, 10:00
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    ????? ???? ???? (????? ???? ?????)

    ???? ????? ?????? ????? ?"? ?????? ???'?????? ????? ?? ???-??? ??? ?????? ?? ????? ?????? ?????? ?????: "Privacy in Challenging Times"

    ???? ?????? ????? ?'-?', 10-7 ???????, 2020, ?????? ??? ???????.

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    Keynote Speakers:
    Ross Anderson, University of Cambridge, UK
    Ann Cavoukian, Global Privacy & Security by Design Centre, Canada
    Susan Landau, Tufts University, USA

    Confirmed Speakers:
    Alessandro Acquisti, Carnegie Mellon University, USA
    Michael Birnhack, Tel Aviv University, Israel
    Sofía Celi, Cloudflare, Inc., UK
    Kamalika Chaudhuri, UCSD, USA
    Claudia Diaz, KU Leuven, Belgium
    Ran Gilad-Bachrach, Tel-Aviv University
    Mathias Humbert, Cyber-Defence Campus, Switzerland
    Karine Nahon, IDC, Israel
    Kobbi Nissim, Georgetown University, USA
    Paul Syverson, Naval Research Laboratory, USA
    Vanessa Teague, Thinking Cybersecurity & The Australian National University
    Carmela Troncoso, EPFL, Switzerland
    Serge Vaudenay, EPF, Switzerland

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