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In this paper, we propose a novel selective search method to speed up the object detection via category-based attention scheme. The proposed attentional searching strategy is designed to focus on a small set of selected regions where the object category is ...
We apply diffusion strategies to develop a fully-distributed cooperative reinforcement learning algorithm in which agents in a network communicate only with their immediate neighbors to improve predictions about their environment. The algorithm can also be ...
A universal construction is an algorithm which transforms any sequential implementation of an object into a concurrent implementation of that same object in a linearizable and wait-free manner. Such constructions require underlying low-level universal shar ...
The simulation of Phasor Measurement Units (PMUs) into real-time simulators (RTSs) is typically limited by the complexity of the synchrophasor estimation (SE) algorithm. This is especially true when dealing with distribution network PMUs due to the more de ...
In this note we re-evaluate the Eurocrypt’16 paper by Zhang et al. [9] in the area of LPN solving algorithms. We present the history of LPN solving algorithms and give the general description of the algorithm from [9]. While this new algorithm claims to im ...
Query plans offer diverse tradeoffs between conflicting cost metrics such as execution time, energy consumption, or execution fees in a multi-objective scenario. It is convenient for users to choose the desired cost tradeoff in an interactive process, dyna ...
Like other data sensing problems, in unlabeled sensing, the target is to solve the equation y = Φx by finding vector x given a set of sample values in vector y as well as the matrix Φ. However, the main challenge in unlabeled sensing is that the correct or ...
This article presents the first tight bounds on the time complexity of shared-memory renaming, a fundamental problem in distributed computing in which a set of processes need to pick distinct identifiers from a small namespace. We first prove an individual ...
We design a sublinear Fourier sampling algorithm for a case of sparse off-grid frequency recovery. These are signals with the form ; i.e., exponential polynomials with a noise term. The frequencies satisfy and for some . We design a sublinear time randomiz ...
In this paper, the fast alternating minimization algorithm (FAMA) is proposed to solve model predictive control (MPC) problems with polytopic and second-order cone constraints. We extend previous theoretical results of FAMA to a more general case, where co ...
