arXiv subjects

Gera Weiss

Publications and source records attributed to Gera Weiss.

22 records · Page 2Linked to original sources

arXiv2018

An optimal approximation of discrete random variables with respect to the Kolmogorov distance

We present an algorithm that takes a discrete random variable $X$ and a number $m$ and computes a random variable whose support (set of possible outcomes) is of size at most $m$ and whose Kolmogorov distance from $X$ is minimal. In addition to a formal theoretical analysis of the correctness and of the computational complexity of the algorithm, we present a detailed empirical evaluation that shows how the proposed approach performs in practice in different applications and domains.

cs.DS↗

arXiv2017

Estimating the Probability of Meeting a Deadline in Hierarchical Plans

Given a hierarchical plan (or schedule) with uncertain task times, we propose a deterministic polynomial (time and memory) algorithm for estimating the probability that its meets a deadline, or, alternately, that its {\em makespan} is less than a given duration. Approximation is needed as it is known that this problem is NP-hard even for sequential plans (just, a sum of random variables). In addition, we show two new complexity results: (1) Counting the number of events that do not cross deadline is \#P-hard; (2)~Computing the expected makespan of a hierarchical plan is NP-hard. For the proposed approximation algorithm, we establish formal approximation bounds and show that the time and memory complexities grow polynomially with the required accuracy, the number of nodes in the plan, and with the size of the support of the random variables that represent the durations of the primitive tasks. We examine these approximation bounds empirically and demonstrate, using task networks taken from the literature, how our scheme outperforms sampling techniques and exact computation in terms of accuracy and run-time. As the empirical data shows much better error bounds than guaranteed, we also suggest a method for tightening the bounds in some cases.

cs.AI↗

arXiv2015

Simple Executions of Snapshot Implementations

The well known snapshot primitive in concurrent programming allows for n-asynchronous processes to write values to an array of single-writer registers and, for each process, to take a snapshot of these registers. In this paper we provide a formulation of the well known linearizability condition for snapshot algorithms in terms of the existence of certain mathematical functions. In addition, we identify a simplifying property of snapshot implementations we call "schedule-based algorithms". This property is natural to assume in the sense that as far as we know, every published snapshot algorithm is schedule-based. Based on this, we prove that when dealing with schedule-based algorithms, it suffices to consider only a small class of very simple executions to prove or disprove correctness in terms of linearizability. We believe that the ideas developed in this paper may help to design automatic verification of snapshot algorithms. Since verifying linearizability was recently proved to be EXPSPACE-complete, focusing on unique objects (snapshot in our case) can potentially lead to designing restricted, but feasible verification methods.

cs.DC↗

arXiv2005

Memoryless output nullification and canonical forms, for time varying systems

We study the possibility of nullifying time-varying systems with memoryless output feedback. The systems we examine are linear single-input single-output finite-dimensional time-varying systems. For generic completely controllable and completely observable discrete-time systems, we show that any state at any time can be steered to the origin within finite time. An algorithm for nullification and an upper bound for nullification time, depending only on the system's dimension, are provided. The algorithm is described using a representation of the system in time-varying controller canonical form. We verify that every completely controllable system has such a representation. The application of the nullification algorithm to sampled-data systems is also analysed: we show that a controllable continuous-time time-varying system with analytic coefficients can be nullified utilising zero-hold sampling of the output and time-varying memoryless linear feedback; for generic observables, almost any sampling period can be used. We also prove that controllability of time-varying systems with analytic coefficients is preserved under zero-hold sampling at almost any rate.

math.OC↗