Randomized error removal for online spread estimation in data streaming

2021 ◽  
Vol 14 (6) ◽  
pp. 1040-1052
Author(s):  
Haibo Wang ◽  
Chaoyi Ma ◽  
Olufemi O Odegbile ◽  
Shigang Chen ◽  
Jih-Kwon Peir
Keyword(s):  
Data Stream ◽  
State Of The Art ◽  
The State ◽  
High Rate ◽  
Estimation Accuracy ◽  
Data Streaming ◽  
Real World Data ◽  
Practical Applications ◽  
Spread Estimation ◽  
Error Removal

Measuring flow spread in real time from large, high-rate data streams has numerous practical applications, where a data stream is modeled as a sequence of data items from different flows and the spread of a flow is the number of distinct items in the flow. Past decades have witnessed tremendous performance improvement for single-flow spread estimation. However, when dealing with numerous flows in a data stream, it remains a significant challenge to measure per-flow spread accurately while reducing memory footprint. The goal of this paper is to introduce new multi-flow spread estimation designs that incur much smaller processing overhead and query overhead than the state of the art, yet achieves significant accuracy improvement in spread estimation. We formally analyze the performance of these new designs. We implement them in both hardware and software, and use real-world data traces to evaluate their performance in comparison with the state of the art. The experimental results show that our best sketch significantly improves over the best existing work in terms of estimation accuracy, data item processing throughput, and online query throughput.

scholarly journals Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation

2019 ◽  
Vol 33 ◽  
pp. 6626-6633
Author(s):  
Xiang Kong ◽  
Qizhe Xie ◽  
Zihang Dai ◽  
Eduard Hovy
Keyword(s):  
Machine Translation ◽  
State Of The Art ◽  
The State ◽  
Computational Time ◽  
Memory Consumption ◽  
Image Captioning ◽  
Vocabulary Size ◽  
Language Generation ◽  
Practical Applications ◽  
Coding Schemes

Mixture of Softmaxes (MoS) has been shown to be effective at addressing the expressiveness limitation of Softmax-based models. Despite the known advantage, MoS is practically sealed by its large consumption of memory and computational time due to the need of computing multiple Softmaxes. In this work, we set out to unleash the power of MoS in practical applications by investigating improved word coding schemes, which could effectively reduce the vocabulary size and hence relieve the memory and computation burden. We show both BPE and our proposed Hybrid-LightRNN lead to improved encoding mechanisms that can halve the time and memory consumption of MoS without performance losses. With MoS, we achieve an improvement of 1.5 BLEU scores on IWSLT 2014 German-to-English corpus and an improvement of 0.76 CIDEr score on image captioning. Moreover, on the larger WMT 2014 machine translation dataset, our MoSboosted Transformer yields 29.6 BLEU score for English-toGerman and 42.1 BLEU score for English-to-French, outperforming the single-Softmax Transformer by 0.9 and 0.4 BLEU scores respectively and achieving the state-of-the-art result on WMT 2014 English-to-German task.

scholarly journals Multifeature Extreme Ordinal Ranking Machine for Facial Age Estimation

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Zhao ◽  
Han Wang ◽  
Guang-Bin Huang
Keyword(s):  
Age Estimation ◽  
Optimization Problems ◽  
State Of The Art ◽  
Mathematical Optimization ◽  
The State ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Training Process ◽  
Ordinal Ranking ◽  
Facial Age

Recently the state-of-the-art facial age estimation methods are almost originated from solving complicated mathematical optimization problems and thus consume huge quantities of time in the training process. To refrain from such algorithm complexity while maintaining a high estimation accuracy, we propose a multifeature extreme ordinal ranking machine (MFEORM) for facial age estimation. Experimental results clearly demonstrate that the proposed approach can sharply reduce the runtime (even up to nearly one hundred times faster) while achieving comparable or better estimation performances than the state-of-the-art approaches. The inner properties of MFEORM are further explored with more advantages.

scholarly journals Handwritten Bangla Character Recognition Using the State-of-the-Art Deep Convolutional Neural Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Md Zahangir Alom ◽  
Paheding Sidike ◽  
Mahmudul Hasan ◽  
Tarek M. Taha ◽  
Vijayan K. Asari
Keyword(s):  
Neural Networks ◽  
Object Recognition ◽  
Convolutional Neural Networks ◽  
Character Recognition ◽  
State Of The Art ◽  
The State ◽  
Superior Performance ◽  
Deep Convolutional Neural Networks ◽  
Practical Applications ◽  
High Degree

In spite of advances in object recognition technology, handwritten Bangla character recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings. Even many advanced existing methods do not lead to satisfactory performance in practice that related to HBCR. In this paper, a set of the state-of-the-art deep convolutional neural networks (DCNNs) is discussed and their performance on the application of HBCR is systematically evaluated. The main advantage of DCNN approaches is that they can extract discriminative features from raw data and represent them with a high degree of invariance to object distortions. The experimental results show the superior performance of DCNN models compared with the other popular object recognition approaches, which implies DCNN can be a good candidate for building an automatic HBCR system for practical applications.

On the Exact Solution of Prize-Collecting Steiner Tree Problems

2021 ◽  
Author(s):  
Daniel Rehfeldt ◽  
Thorsten Koch
Keyword(s):  
Exact Solution ◽  
Steiner Tree ◽  
State Of The Art ◽  
The State ◽  
Steiner Tree Problem ◽  
New Techniques ◽  
Practical Applications ◽  
Computational Performance ◽  
Benchmark Instances ◽  
Prize Collecting

The prize-collecting Steiner tree problem (PCSTP) is a well-known generalization of the classic Steiner tree problem in graphs, with a large number of practical applications. It attracted particular interest during the 11th DIMACS Challenge in 2014, and since then, several PCSTP solvers have been introduced in the literature. Although these new solvers further, and often drastically, improved on the results of the DIMACS Challenge, many PCSTP benchmark instances have remained unsolved. The following article describes further advances in the state of the art in exact PCSTP solving. It introduces new techniques and algorithms for PCSTP, involving various new transformations (or reductions) of PCSTP instances to equivalent problems, for example, to decrease the problem size or to obtain a better integer programming formulation. Several of the new techniques and algorithms provably dominate previous approaches. Further theoretical properties of the new components, such as their complexity, are discussed. Also, new complexity results for the exact solution of PCSTP and related problems are described, which form the base of the algorithm design. Finally, the new developments also translate into a strong computational performance: the resulting exact PCSTP solver outperforms all previous approaches, both in terms of runtime and solvability. In particular, it solves several formerly intractable benchmark instances from the 11th DIMACS Challenge to optimality. Moreover, several recently introduced large-scale instances with up to 10 million edges, previously considered to be too large for any exact approach, can now be solved to optimality in less than two hours. Summary of Contribution: The prize-collecting Steiner tree problem (PCSTP) is a well-known generalization of the classic Steiner tree problem in graphs, with many practical applications. The article introduces and analyses new techniques and algorithms for PCSTP that ultimately aim for improved (practical) exact solution. The algorithmic developments are underpinned by results on theoretical aspects, such as fixed-parameter tractability of PCSTP. Computationally, we considerably push the limits of tractibility, being able to solve PCSTP instances with up to 10 million edges. The new solver, which also considerably outperforms the state of the art on smaller instances, will be made publicly available as part of the SCIP Optimization Suite.

High-Rate Water Treatment: The State-of-the-Art

1975 ◽  
Vol 101 (4) ◽  
pp. 479-488
Author(s):  
Paul H. King ◽  
Robert L. Johnson ◽  
Clifford W. Randall ◽  
Glenn W. Rehberger
Keyword(s):  
Water Treatment ◽  
State Of The Art ◽  
The State ◽  
High Rate

scholarly journals Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling

2020 ◽  
Vol 34 (04) ◽  
pp. 4602-4609
Author(s):  
Chao Li ◽  
Mohammad Emtiyaz Khan ◽  
Zhun Sun ◽  
Gang Niu ◽  
Bo Han ◽  
...  
Keyword(s):  
State Of The Art ◽  
Synthetic Data ◽  
Tensor Decomposition ◽  
Scientific Data ◽  
Image Steganography ◽  
Real World Data ◽  
Practical Applications ◽  
Scientific Data Analysis ◽  
The Matrix ◽  
Td Methods

Exact recovery of tensor decomposition (TD) methods is a desirable property in both unsupervised learning and scientific data analysis. The numerical defects of TD methods, however, limit their practical applications on real-world data. As an alternative, convex tensor decomposition (CTD) was proposed to alleviate these problems, but its exact-recovery property is not properly addressed so far. To this end, we focus on latent convex tensor decomposition (LCTD), a practically widely-used CTD model, and rigorously prove a sufficient condition for its exact-recovery property. Furthermore, we show that such property can be also achieved by a more general model than LCTD. In the new model, we generalize the classic tensor (un-)folding into reshuffling operation, a more flexible mapping to relocate the entries of the matrix into a tensor. Armed with the reshuffling operations and exact-recovery property, we explore a totally novel application for (generalized) LCTD, i.e., image steganography. Experimental results on synthetic data validate our theory, and results on image steganography show that our method outperforms the state-of-the-art methods.

Reverse-design-strategy for C@Li3VO4 Nanoflakes toward superb high-rate Li-ion storage

2021 ◽  
Author(s):  
Jie Xu ◽  
Pei Liang ◽  
Dongmei Zhang ◽  
Cunyuan Pei ◽  
Zongping Zhang ◽  
...  
Keyword(s):  
State Of The Art ◽  
Design Strategy ◽  
The State ◽  
High Rate ◽  
Ion Storage ◽  
Li Ion

While the design of Li3VO4 (LVO) anode is severely hindered by its hydrophilio, here the state-of-the-art Li3VO4/C nanoflakes with specific crystalline planes exposure (C@LVO-NFs) are designed and firstly synthesized via...

scholarly journals Availability Analysis of HVDC-VSC Systems: A Review

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2703 ◽  
Author(s):  
Dambone Sessa ◽  
Chiarelli ◽  
Benato
Keyword(s):  
State Of The Art ◽  
The State ◽  
Assessment Methods ◽  
Design Phase ◽  
Practical Applications ◽  
Hvdc System ◽  
Availability Analysis ◽  
Conversion System ◽  
Key Aspects ◽  
Availability Assessment

This work stems from the worldwide increasing need to precisely consider, in the design phase of an HVDC project, the availability of the HVDC system. In this paper, an overview of the availability assessment methods for HVDC-VSC transmission systems is presented. In particular, the state of the art of the procedures to estimate the availability of both the HVDC link reparable components and the conversion system on the basis of the converter configuration is given. The theoretical fundamentals of each method, together with their practical applications, have been described, in order to highlight the limits and the potentialities of each approach. The authors aim at giving a guide to choosing the best computation approach on the basis of the specific needs of the users and at summarizing all the key aspects which can be taken into account during the availability assessment of HVDC-VSC links.

The Science of Emotional Intelligence

2008 ◽  
Vol 13 (1) ◽  
pp. 64-78 ◽  
Author(s):  
Moshe Zeidner ◽  
Richard D. Roberts ◽  
Gerald Matthews
Keyword(s):  
Emotional Intelligence ◽  
State Of The Art ◽  
Real Life ◽  
The State ◽  
Current Status ◽  
Practical Applications ◽  
Degree Of Confidence ◽  
New Research

Almost from its inception, the emotional intelligence (EI) construct has been an elusive one. After nearly 2 decades of research, there still appears to be little consensus over how EI should be conceptualized or assessed and the efficacy of practical applications in real life settings. This paper aims at providing a snapshot of the state-of-the-art in research involving this newly minted construct. Specifically, in separate sections of this article, we set out to distinguish what is known from what is unknown in relation to three paramount concerns of EI research, i.e., conceptualization, assessment, and applications. In each section, we start by discussing assertions that may be made with some degree of confidence, elucidating what are essentially sources of consensus concerning EI. We move then to discuss sources of controversy; those things for which there is less agreement among EI researchers. We hope that this “straight talk” about the current status of EI research will provide a platform for new research in both basic and applied domains.

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