scholarly journals Pareto Optimization for Subset Selection with Dynamic Cost Constraints

2019 ◽  
Vol 33 ◽  
pp. 2354-2361 ◽  
Author(s):  
Vahid Roostapour ◽  
Aneta Neumann ◽  
Frank Neumann ◽  
Tobias Friedrich
Keyword(s):  
Greedy Algorithms ◽  
Subset Selection ◽  
Pareto Optimization ◽  
Experimental Investigations ◽  
Optimization Approach ◽  
Submodular Optimization ◽  
Approximation Quality ◽  
Cost Constraints ◽  
Changes Over Time ◽  
Over Time

In this paper, we consider the subset selection problem for function f with constraint bound B which changes over time. We point out that adaptive variants of greedy approaches commonly used in the area of submodular optimization are not able to maintain their approximation quality. Investigating the recently introduced POMC Pareto optimization approach, we show that this algorithm efficiently computes a φ = (αf/2)(1− α1f )-approximation, where αf is the sube modularity ratio of f, for each possible constraint bound b ≤ B. Furthermore, we show that POMC is able to adapt its set of solutions quickly in the case that B increases. Our experimental investigations for the influence maximization in social networks show the advantage of POMC over generalized greedy algorithms.

scholarly journals Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints

2021 ◽  
Author(s):  
Chao Bian ◽  
Chao Qian ◽  
Frank Neumann ◽  
Yang Yu
Keyword(s):  
Objective Function ◽  
Greedy Algorithm ◽  
Real World ◽  
Fundamental Problem ◽  
Subset Selection ◽  
Selection Strategy ◽  
Cost Constraints ◽  
Approximation Guarantee ◽  
Changes Over Time ◽  
Over Time

Subset selection with cost constraints is a fundamental problem with various applications such as influence maximization and sensor placement. The goal is to select a subset from a ground set to maximize a monotone objective function such that a monotone cost function is upper bounded by a budget. Previous algorithms with bounded approximation guarantees include the generalized greedy algorithm, POMC and EAMC, all of which can achieve the best known approximation guarantee. In real-world scenarios, the resources often vary, i.e., the budget often changes over time, requiring the algorithms to adapt the solutions quickly. However, when the budget changes dynamically, all these three algorithms either achieve arbitrarily bad approximation guarantees, or require a long running time. In this paper, we propose a new algorithm FPOMC by combining the merits of the generalized greedy algorithm and POMC. That is, FPOMC introduces a greedy selection strategy into POMC. We prove that FPOMC can maintain the best known approximation guarantee efficiently.

scholarly journals Near-Optimal Graph Signal Sampling by Pareto Optimization

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1415
Author(s):  
Dongqi Luo ◽  
Binqiang Si ◽  
Saite Zhang ◽  
Fan Yu ◽  
Jihong Zhu
Keyword(s):  
State Of The Art ◽  
Greedy Algorithms ◽  
Empirical Studies ◽  
Subset Selection ◽  
Reconstruction Error ◽  
Pareto Optimization ◽  
Signal Sampling ◽  
Approximation Bound ◽  
Sampling Problem ◽  
Optimal Graph

In this paper, we focus on the bandlimited graph signal sampling problem. To sample graph signals, we need to find small-sized subset of nodes with the minimal optimal reconstruction error. We formulate this problem as a subset selection problem, and propose an efficient Pareto Optimization for Graph Signal Sampling (POGSS) algorithm. Since the evaluation of the objective function is very time-consuming, a novel acceleration algorithm is proposed in this paper as well, which accelerates the evaluation of any solution. Theoretical analysis shows that POGSS finds the desired solution in quadratic time while guaranteeing nearly the best known approximation bound. Empirical studies on both Erdos-Renyi graphs and Gaussian graphs demonstrate that our method outperforms the state-of-the-art greedy algorithms.

scholarly journals Pareto optimization for subset selection with dynamic cost constraints

2022 ◽  
Vol 302 ◽  
pp. 103597
Author(s):  
Vahid Roostapour ◽  
Aneta Neumann ◽  
Frank Neumann ◽  
Tobias Friedrich
Keyword(s):  
Subset Selection ◽  
Pareto Optimization ◽  
Cost Constraints

Comparison of two devices for measuring exercise transcutaneous oxygen pressures in patients with claudication

VASA ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 355-362 ◽  
Author(s):  
Marie Urban ◽  
Alban Fouasson-Chailloux ◽  
Isabelle Signolet ◽  
Christophe Colas Ribas ◽  
Mathieu Feuilloy ◽  
...  
Keyword(s):  
Oxygen Pressure ◽  
Optical Sensors ◽  
Chemical Sensors ◽  
Transcutaneous Oxygen ◽  
Starting Values ◽  
Two Systems ◽  
Transcutaneous Oxygen Pressure ◽  
New Sensors ◽  
Changes Over Time ◽  
Over Time

Abstract. Summary: Background: We aimed at estimating the agreement between the Medicap® (photo-optical) and Radiometer® (electro-chemical) sensors during exercise transcutaneous oxygen pressure (tcpO2) tests. Our hypothesis was that although absolute starting values (tcpO2rest: mean over 2 minutes) might be different, tcpO2-changes over time and the minimal value of the decrease from rest of oxygen pressure (DROPmin) results at exercise shall be concordant between the two systems. Patients and methods: Forty seven patients with arterial claudication (65 + / - 7 years) performed a treadmill test with 5 probes each of the electro-chemical and photo-optical devices simultaneously, one of each system on the chest, on each buttock and on each calf. Results: Seventeen Medicap® probes disconnected during the tests. tcpO2rest and DROPmin values were higher with Medicap® than with Radiometer®, by 13.7 + / - 17.1 mm Hg and 3.4 + / - 11.7 mm Hg, respectively. Despite the differences in absolute starting values, changes over time were similar between the two systems. The concordance between the two systems was approximately 70 % for classification of test results from DROPmin. Conclusions: Photo-optical sensors are promising alternatives to electro-chemical sensors for exercise oximetry, provided that miniaturisation and weight reduction of the new sensors are possible.

Neuropsychological Symptoms in Posttraumatic Stress Disorder and Changes Over Time

2007 ◽  
Author(s):  
Miranda Olff ◽  
Mirjam Nijdam ◽  
Kristin Samuelson ◽  
Julia Golier ◽  
Mariel Meewisse ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Neuropsychological Symptoms ◽  
Changes Over Time ◽  
Over Time

Changes Over Time in Adaptive Behavior Functioning of Twice-Exceptional Children

2010 ◽  
Author(s):  
Rebecca D. Stinson ◽  
Zachary Sussman ◽  
Megan Foley Nicpon ◽  
Allison L. Allmon ◽  
Courtney Cornick ◽  
...  
Keyword(s):  
Adaptive Behavior ◽  
Exceptional Children ◽  
Twice Exceptional ◽  
Changes Over Time ◽  
Over Time

Kategorisierung der Schädelform des Cavalier King Charles Spaniels

2019 ◽  
Vol 47 (02) ◽  
pp. 133-133
Keyword(s):  
Pilot Study ◽  
Cavalier King Charles Spaniel ◽  
Conformation Changes ◽  
Veterinary Record ◽  
Changes Over Time ◽  
Over Time

Knowler SP, Gillstedt L, Mitchell TJ et al. Pilot study of head conformation changes over time in the Cavalier King Charles spaniel breed. Veterinary Record 2019. doi:10.1136/vr.105135.

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