It’s the Economy, Stupid: Applying (Micro)economic Principles to Microbiome Science

A key challenge in microbiome science is the scale mismatch problem, which arises when the scale at which microbial communities are sampled, interrogated, and averaged is different from the scale at which individual microorganisms within those communities interact with each other and with their environment (D. W.

PQPS: Prior-Art Query-Based Patent Summarizer Using RBM and Bi-LSTM

A prior-art search on patents ascertains the patentability constraints of the invention through an organized review of prior-art document sources. This search technique poses challenges because of the inherent vocabulary mismatch problem. Manual processing of every retrieved relevant patent in its entirety is a tedious and time-consuming job that demands automated patent summarization for ease of access. This paper employs deep learning models for summarization as they take advantage of the massive dataset present in the patents to improve the summary coherence. This work presents a novel approach of patent summarization named PQPS: prior-art query-based patent summarizer using restricted Boltzmann machine (RBM) and bidirectional long short-term memory (Bi-LSTM) models. The PQPS also addresses the vocabulary mismatch problem through query expansion with knowledge bases such as domain ontology and WordNet. It further enhances the retrieval rate through topic modeling and bibliographic coupling of citations. The experiments analyze various interlinked smart device patent sample sets. The proposed PQPS demonstrates that retrievability increases both in extractive and abstractive summaries.

Deep Residual Reinforcement Learning (Extended Abstract)

We revisit residual algorithms in both model-free and model-based reinforcement learning settings. We propose the bidirectional target network technique to stabilize residual algorithms, yielding a residual version of DDPG that significantly outperforms vanilla DDPG in commonly used benchmarks. Moreover, we find the residual algorithm an effective approach to the distribution mismatch problem in model-based planning. Compared with the existing TD(k) method, our residual-based method makes weaker assumptions about the model and yields a greater performance boost.

In defense of fractional free banking

This paper examines the debate between the so-called fractionalists and the reservists within the Austrian School of Economics (1994 – 2005), emphasizing the maturity mismatch problem (2009 – 2019). It focuses on the fundamental arguments: the ontological view on currencies as banks’ products (IOUs) and money, the purchasing power of money, and the maturity mismatch problem. Banking activity is seen as a vital evolutionary superstructure humans use to determine the marginal utilization of existing capital resources, effectively discovering the coincidence of money interest towards natural interest levels and time preferences within society. The thesis advocates the superiority of fractional and free banking over the reservist alternative. It shows that fractional free banking is not based on property rights violations, and does not cause systematic economic cycles beyond those related to natural business errors.