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Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition System
- W. Cai, Jinkun Chen, Ming Li
- Computer ScienceThe Speaker and Language Recognition Workshop
- 14 April 2018
Experimental results on Voxceleb and NIST LRE 07 datasets show that the performance of end-to-end learning system could be significantly improved by the proposed encoding layer and loss function.
2D-LDA: A statistical linear discriminant analysis for image matrix
DyXY - a proximity congestion-aware deadlock-free dynamic routing method for network on chip
- Ming Li, Qing-An Zeng, W. Jone
- Computer Science, Business43rd ACM/IEEE Design Automation Conference
- 24 July 2006
Analytical models based on queuing theory are developed for DyXY routing for a two-dimensional mesh NoC architecture, and analytical results match very well with the simulation results.
Supervised Deep Features for Software Functional Clone Detection by Exploiting Lexical and Syntactical Information in Source Code
Experiments on software clone detection benchmarks indicate that the CDLH approach is effective and outperforms the state-of-the-art approaches in software functional clone detection.
NONCODEv4: exploring the world of long non-coding RNA genes
This update of NONCODE expands the ncRNA data set by collection of newly identified ncRNAs from literature published in the last 2 years and integration of the latest version of RefSeq and Ensembl.
Forecasting Fine-Grained Air Quality Based on Big Data
- Yu Zheng, Xiuwen Yi, Tianrui Li
- Environmental ScienceKnowledge Discovery and Data Mining
- 10 August 2015
In this paper, we forecast the reading of an air quality monitoring station over the next 48 hours, using a data-driven method that considers current meteorological data, weather forecasts, and air…
A Ranking of Software Engineering Measures Based on Expert Opinion
This research proposes a framework based on expert opinion elicitation, developed to select the software engineering measures which are the best software reliability indicators. The current research…
DeepChain: Auditable and Privacy-Preserving Deep Learning with Blockchain-Based Incentive
- Jiasi Weng, J. Weng, Ming Li, Yue Zhang, Weiqi Luo
- Computer ScienceIEEE Transactions on Dependable and Secure…
- 8 November 2019
This paper presents a distributed, secure, and fair deep learning framework named DeepChain, which provides a value-driven incentive mechanism based on Blockchain to force the participants to behave correctly and guarantees data privacy for each participant and provides auditability for the whole training process.
Functional modulation of brain sodium channels by cAMP-dependent phosphorylation