Unifying and Merging Well-trained Deep Neural Networks for Inference Stage

We propose a novel method to merge convolutional neural-nets for the inference stage. Given two well-trained networks that may have different architectures that handle different tasks, our method aligns the layers of the original networks and merges them into a unified model by sharing the representative codes of weights. The shared weights are further re-trained to fine-tune the performance of the merged model. The proposed method effectively produces a compact model that may run original tasks simultaneously on resource-limited devices. As it preserves the general architectures and leverages the co-used weights of well-trained networks, a substantial training overhead can be reduced to shorten the system development time. Experimental results demonstrate a satisfactory performance and validate the effectiveness of the method.Comment: To appear in the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, 2018. (IJCAI-ECAI 2018

Learning performance assessment approach using learning portfolio for e-learning systems

Learning performance assessment aims to evaluate what learners learnt during the learning process. In recent years, how to perform the learning performance assessment is a critical issue in the web-based learning field. The traditional summative evaluation can be applied to evaluate the learning performance both for the conventional classroom learning and web-based learning. However, it only considers final learning outcomes without considering the learning progress of learners. This paper proposes a learning performance assessment approach which combines four computational intelligence theories including grey relational analysis, K-means clustering method, fuzzy association rule mining and fuzzy inference to perform this task based on the learning portfolio of individual learner. Experimental results indicate that the evaluation result of proposed method is positive relevance with those of summative assessment. Namely, this method can help teachers to precisely perform the formative assessment for individual learner utilizing only the learning portfolio in web-based learning environment. 1

Multimode optical feedback dynamics in InAs/GaAs quantum dot lasers emitting exclusively on ground or excited states: transition from short- to long-delay regimes

© 2018 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.The optical feedback dynamics of two multimode InAs/GaAs quantum dot lasers emitting exclusively on sole ground or excited lasing states is investigated. The transition from long- to short-delay regimes is analyzed, while the boundaries associated to the birth of periodic and chaotic oscillations are unveiled to be a function of the external cavity length. The results show that depending on the initial lasing state, different routes to chaos are observed. These results are of importance for the development of isolator-free transmitters in short-reach networks