759,950 research outputs found
Computing the Kalman form
We present two algorithms for the computation of the Kalman form of a linear
control system. The first one is based on the technique developed by
Keller-Gehrig for the computation of the characteristic polynomial. The cost is
a logarithmic number of matrix multiplications. To our knowledge, this improves
the best previously known algebraic complexity by an order of magnitude. Then
we also present a cubic algorithm proven to more efficient in practice.Comment: 10 page
The Logic of the Method of Agent-Based Simulation in the Social Sciences: Empirical and Intentional Adequacy of Computer Programs
The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences.Computer and Social Sciences, Agent-Based Simulation, Intentional Computation, Program Verification, Intentional Verification, Scientific Knowledge
SBNet: Sparse Blocks Network for Fast Inference
Conventional deep convolutional neural networks (CNNs) apply convolution
operators uniformly in space across all feature maps for hundreds of layers -
this incurs a high computational cost for real-time applications. For many
problems such as object detection and semantic segmentation, we are able to
obtain a low-cost computation mask, either from a priori problem knowledge, or
from a low-resolution segmentation network. We show that such computation masks
can be used to reduce computation in the high-resolution main network. Variants
of sparse activation CNNs have previously been explored on small-scale tasks
and showed no degradation in terms of object classification accuracy, but often
measured gains in terms of theoretical FLOPs without realizing a practical
speed-up when compared to highly optimized dense convolution implementations.
In this work, we leverage the sparsity structure of computation masks and
propose a novel tiling-based sparse convolution algorithm. We verified the
effectiveness of our sparse CNN on LiDAR-based 3D object detection, and we
report significant wall-clock speed-ups compared to dense convolution without
noticeable loss of accuracy.Comment: 10 pages, CVPR 201
Necessary and Sufficient Conditions on Partial Orders for Modeling Concurrent Computations
Partial orders are used extensively for modeling and analyzing concurrent
computations. In this paper, we define two properties of partially ordered
sets: width-extensibility and interleaving-consistency, and show that a partial
order can be a valid state based model: (1) of some synchronous concurrent
computation iff it is width-extensible, and (2) of some asynchronous concurrent
computation iff it is width-extensible and interleaving-consistent. We also
show a duality between the event based and state based models of concurrent
computations, and give algorithms to convert models between the two domains.
When applied to the problem of checkpointing, our theory leads to a better
understanding of some existing results and algorithms in the field. It also
leads to efficient detection algorithms for predicates whose evaluation
requires knowledge of states from all the processes in the system
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