scholarly journals A flexible class of dependence-aware multi-label loss functions

2022 ◽  
Author(s):  
Eyke Hüllermeier ◽  
Marcel Wever ◽  
Eneldo Loza Mencia ◽  
Johannes Fürnkranz ◽  
Michael Rapp
Keyword(s):  
Function Class ◽  
Loss Functions ◽  
Mathematical Framework ◽  
Additive Measure ◽  
Performance Improvements ◽  
Special Cases ◽  
Overall Evaluation ◽  
Label Dependence ◽  
And Performance ◽  
Additive Measures

AbstractThe idea to exploit label dependencies for better prediction is at the core of methods for multi-label classification (MLC), and performance improvements are normally explained in this way. Surprisingly, however, there is no established methodology that allows to analyze the dependence-awareness of MLC algorithms. With that goal in mind, we introduce a class of loss functions that are able to capture the important aspect of label dependence. To this end, we leverage the mathematical framework of non-additive measures and integrals. Roughly speaking, a non-additive measure allows for modeling the importance of correct predictions of label subsets (instead of single labels), and thereby their impact on the overall evaluation, in a flexible way. The well-known Hamming and subset 0/1 losses are rather extreme special cases of this function class, which give full importance to single label sets or the entire label set, respectively. We present concrete instantiations of this class, which appear to be especially appealing from a modeling perspective. The assessment of multi-label classifiers in terms of these losses is illustrated in an empirical study, clearly showing their aptness at capturing label dependencies. Finally, while not being the main goal of this study, we also show some preliminary results on the minimization of this parametrized family of losses.

Materials Issues and Characterization of Low-k Dielectric Materials

MRS Bulletin ◽  
1997 ◽  
Vol 22 (10) ◽  
pp. 49-54 ◽  
Author(s):  
E. Todd Ryan ◽  
Andrew J. McKerrow ◽  
Jihperng Leu ◽  
Paul S. Ho
Keyword(s):  
Process Integration ◽  
Dielectric Materials ◽  
Propagation Delay ◽  
Thermomechanical Properties ◽  
General Criterion ◽  
Crosstalk Noise ◽  
Total Delay ◽  
Interlayer Dielectrics ◽  
Performance Improvements ◽  
And Performance

Continuing improvement in device density and performance has significantly affected the dimensions and complexity of the wiring structure for on-chip interconnects. These enhancements have led to a reduction in the wiring pitch and an increase in the number of wiring levels to fulfill demands for density and performance improvements. As device dimensions shrink to less than 0.25 μm, the propagation delay, crosstalk noise, and power dissipation due to resistance-capacitance (RC) coupling become significant. Accordingly the interconnect delay now constitutes a major fraction of the total delay limiting the overall chip performance. Equally important is the processing complexity due to an increase in the number of wiring levels. This inevitably drives cost up by lowering the manufacturing yield due to an increase in defects and processing complexity.To address these problems, new materials for use as metal lines and interlayer dielectrics (ILDs) and alternative architectures have surfaced to replace the current Al(Cu)/SiO2 interconnect technology. These alternative architectures will require the introduction of low-dielectric-constant k materials as the interlayer dielectrics and/or low-resistivity conductors such as copper. The electrical and thermomechanical properties of SiO2 are ideal for ILD applications, and a change to material with different properties has important process-integration implications. To facilitate the choice of an alternative ILD, it is necessary to establish general criterion for evaluating thin-film properties of candidate low-k materials, which can be later correlated with process-integration problems.

Remote Thermal Performance Monitoring and Diagnostics: Turning Data Into Knowledge

2013 ◽  
Author(s):  
Xiaomo Jiang ◽  
Craig Foster
Keyword(s):  
Anomaly Detection ◽  
Gas Turbines ◽  
Performance Monitoring ◽  
Combined Cycle ◽  
Integrated System ◽  
Site Specific ◽  
Performance Improvements ◽  
Maintenance Schedule ◽  
Effectiveness Monitoring ◽  
And Performance

Gas turbine simple or combined cycle plants are built and operated with higher availability, reliability, and performance in order to provide the customer with sufficient operating revenues and reduced fuel costs meanwhile enhancing customer dispatch competitiveness. A tremendous amount of operational data is usually collected from the everyday operation of a power plant. It has become an increasingly important but challenging issue about how to turn this data into knowledge and further solutions via developing advanced state-of-the-art analytics. This paper presents an integrated system and methodology to pursue this purpose by automating multi-level, multi-paradigm, multi-facet performance monitoring and anomaly detection for heavy duty gas turbines. The system provides an intelligent platform to drive site-specific performance improvements, mitigate outage risk, rationalize operational pattern, and enhance maintenance schedule and service offerings via taking appropriate proactive actions. In addition, the paper also presents the components in the system, including data sensing, hardware, and operational anomaly detection, expertise proactive act of company, site specific degradation assessment, and water wash effectiveness monitoring and analytics. As demonstrated in two examples, this remote performance monitoring aims to improve equipment efficiency by converting data into knowledge and solutions in order to drive value for customers including lowering operating fuel cost and increasing customer power sales and life cycle value.

Achieving Health, Safety, and Performance Improvements Through Enhanced Cost Visibility and Workplace Partnerships

AIHA Journal ◽  
2003 ◽  
Vol 64 (5) ◽  
pp. 660-667 ◽  
Author(s):  
Katharyn A. Grant ◽  
John G. Garland ◽  
Todd C. Joachim ◽  
Andrew Wallen ◽  
Twyla Vital
Keyword(s):  
Health Safety ◽  
Performance Improvements ◽  
And Performance

A New Aluminium Silicon-Boron Nitride Abradable for Compressor Components

1998 ◽  
Author(s):  
K. Boddenberg ◽  
B. Kock ◽  
M. Dorfman ◽  
L. Russo ◽  
M. Nestler
Keyword(s):  
Boron Nitride ◽  
Raw Materials ◽  
Electrical Energy ◽  
Air Separation ◽  
Energy Costs ◽  
Performance Improvements ◽  
And Performance ◽  
Materials Used ◽  
Abradable Coatings ◽  
Optimization And Performance

Abstract Air separation plants use centrifugal compressors where air and electrical energy are the only raw materials used in the production process. So energy costs play a crucial role and the compressors are heavily penalized when guaranteed performance levels are not achieved. In order to better generate performance, abradable coatings, previously used in the gas turbine industry, have been designed into turbocompressors. This paper will show the optimization and performance improvements of a new aluminium silicon-boron nitride material.

scholarly journals THE INTERVAL-VALUED INTUITIONISTIC FUZZY GEOMETRIC CHOQUET AGGREGATION OPERATOR BASED ON THE GENERALIZED BANZHAF INDEX AND 2-ADDITIVE MEASURE

2015 ◽  
Vol 21 (2) ◽  
pp. 186-215 ◽  
Author(s):  
Fanyong MENG ◽  
Qiang ZHANG ◽  
Jiaquan ZHAN
Keyword(s):  
Geometric Mean ◽  
Fuzzy Measure ◽  
Entropy Measure ◽  
Additive Measure ◽  
Banzhaf Index ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Operational Laws ◽  
Additive Measures ◽  
Interval Valued

Based on the operational laws on interval-valued intuitionistic fuzzy sets, the generalized Banzhaf interval-valued intuitionistic fuzzy geometric Choquet (GBIVIFGC) operator is proposed, which is also an interval-valued intuitionistic fuzzy value. It is worth pointing out that the GBIVIFGC operator can be seen as an extension of some geometric mean operators. Since the fuzzy measure is defined on the power set, it makes the problem exponentially complex. In order to overall reflect the interaction among elements and reduce the complexity of solving a fuzzy measure, we further introduce the GBIVIFGC operator w.r.t. 2-additive measures. Furthermore, if the information about weights of experts and attributes is incompletely known, the models of obtaining the optimal 2-additive measures on criteria set and expert set are given by using the introduced cross entropy measure and the Banzhaf index. Finally, an approach to pattern recognition and multi-criteria group decision making under interval-valued intuitionistic fuzzy environment is developed, respectively.

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