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MODELS, the ACM/IEEE 22th International Conference on Model Driven Engineering Languages and Systems, is the premier conference series for model-driven software and systems engineering, and is organized with support of ACM SIGSOFT and IEEE TCSE. Since 1998, MODELS has covered all aspects of modeling...
Munich, Germany
15-20
Sep
Elicitation and Stakeholders, Requirements Analysis, Specification and Validation, Requirements Management, Pragmatic Requirements Engineering, Large-scale Requirements Engineering, Global Requirements Engineering, Domain-specific Requirements Engineering,Quality Engineering, Product Management, Ind...
Jeju Island, Korea (South)
23-27
Sep
The International Conference on Software Maintenance and Evolution (ICSME) is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolu...
Cleveland, USA
29-04
Sep
Trending from the Computer Society Digital Library
Computer magazine
Robert Bell
AT&T Labs
As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels.
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Kaiming He
Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitly reformulate the layers as learning residual functions with reference to the layer inputs, instead of l...
IEEE Transactions on Knowledge & Data Engineering
Edwardo A. Garcia
Stevens Institute of Technology, Hoboken
With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding of knowledge discovery and analysis from raw data to support decision-making pro...