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Expert elicitations are a promising method for determining how R&D investments are likely to have an impact on technological advance in climate change energy technologies. But, expert elicita-tions are time-consuming and resource intensive. Thus, we investigate the value of the information gained in expert elicitations. More specifically, given baseline(More)
Agent-oriented techniques are being increasingly used in a range of networking security applications. In this paper, we introduce FNTAE, a Federated Network Traffic Analysis Engine for real-time network intrusion detection. In FNTAE, each analysis engine is powered with an incremental learning agent, for capturing attack signatures in real-time, so that the(More)
Training data in real world is often presented in random chunks. Yet existing sequential Incremental IDR/QR LDA (s-QR/IncLDA) can only process data one sample after another. This paper proposes a constructive chunk Incremental IDR/QR LDA (c-QR/IncLDA) for multiple data samples incremental learning. Given a chunk of s samples for incremental learning, the(More)
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