領域専門家の知識活用によるユーザへの親和性を重視した機械学習

京都大学新制・課程博士博士(工学)甲第23615号工博第4936号京都大学大学院工学研究科機械理工学専攻(主査)教授 椹木 哲夫, 教授 松野 文俊, 教授 藤本 健治学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDFA

To Crown a Broccoli. Progressing on the path of Jungian individuation through animistic images in painting

This practice-led research report investigated my personal individuation journey in painting. Art has, in contemporary days, become an increasingly discursive and broad concept which contains overwhelming diversity and has a tendency to confuse not only the audience but also the artists. As a researcher as well as an artist early in her career, I faced similar questions as many others. How to find authenticity in art? How to become an individual on canvas? Inspired by Jung’s concept of individuation, the lifelong development of personality, I created a planning and analytical tool for art, the Creative and Evaluative Model of Artistic Individuation, or CEMAI. This tool consists of multiple axes of contradictions. I identified different axes on CEMAI and experimented with various visual complexities in painting, looking at Chinese (professional) and UK (liberal) art education, the interchanging identities of child and adult, and the relationship between word and image. I tried to find my position in all of this, a balanced zone among different contradictions. Inspired by the Naxi culture I realised the validity and significance of the animistic point of view. This was that middle zone, a conclusion as well as an opening of the future. Through this process, I continue to gradually progress along the path of Jungian individuation on an authentic journey of selfrealisation. The approach I have taken is largely autoethnographic, with my own stories and lived experiences acting as an integral part of and often mixed in with more methodological research

Fair Resource Sharing with Externailities

We study a fair resource sharing problem, where a set of resources are to be shared among a set of agents. Each agent demands one resource and each resource can serve a limited number of agents. An agent cares about what resource they get as well as the externalities imposed by their mates, whom they share the same resource with. Apparently, the strong notion of envy-freeness, where no agent envies another for their resource or mates, cannot always be achieved and we show that even to decide the existence of such a strongly envy-free assignment is an intractable problem. Thus, a more interesting question is whether (and in what situations) a relaxed notion of envy-freeness, the Pareto envy-freeness, can be achieved: an agent i envies another agent j only when i envies both the resource and the mates of j. In particular, we are interested in a dorm assignment problem, where students are to be assigned to dorms with the same capacity and they have dichotomous preference over their dorm-mates. We show that when the capacity of the dorms is 2, a Pareto envy-free assignment always exists and we present a polynomial-time algorithm to compute such an assignment; nevertheless, the result fails to hold immediately when the capacities increase to 3, in which case even Pareto envy-freeness cannot be guaranteed. In addition to the existential results, we also investigate the implications of envy-freeness on proportionality in our model and show that envy-freeness in general implies approximations of proportionality

Nematic crossover in BaFe2_2As2_2 under uniaxial stress

Raman scattering can detect spontaneous point-group symmetry breaking without resorting to single-domain samples. Here we use this technique to study $\mathrm{BaFe_2As_2}$, the parent compound of the "122" Fe-based superconductors. We show that an applied compression along the Fe-Fe direction, which is commonly used to produce untwinned orthorhombic samples, changes the structural phase transition at temperature $T_{\mathrm{s}}$ into a crossover that spans a considerable temperature range above $T_{\mathrm{s}}$. Even in crystals that are not subject to any applied force, a distribution of substantial residual stress remains, which may explain phenomena that are seemingly indicative of symmetry breaking above $T_{\mathrm{s}}$. Our results are consistent with an onset of spontaneous nematicity only below $T_{\mathrm{s}}$.Comment: 4 pages, 4 figure

Investigating the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning model

BACKGROUND: Survival analysis is an important part of cancer studies. In addition to the existing Cox proportional hazards model, deep learning models have recently been proposed in survival prediction, which directly integrates multi-omics data of a large number of genes using the fully connected dense deep neural network layers, which are hard to interpret. On the other hand, cancer signaling pathways are important and interpretable concepts that define the signaling cascades regulating cancer development and drug resistance. Thus, it is important to investigate potential associations between patient survival and individual signaling pathways, which can help domain experts to understand deep learning models making specific predictions. RESULTS: In this exploratory study, we proposed to investigate the relevance and influence of a set of core cancer signaling pathways in the survival analysis of cancer patients. Specifically, we built a simplified and partially biologically meaningful deep neural network, DeepSigSurvNet, for survival prediction. In the model, the gene expression and copy number data of 1967 genes from 46 major signaling pathways were integrated in the model. We applied the model to four types of cancer and investigated the influence of the 46 signaling pathways in the cancers. Interestingly, the interpretable analysis identified the distinct patterns of these signaling pathways, which are helpful in understanding the relevance of signaling pathways in terms of their application to the prediction of cancer patients\u27 survival time. These highly relevant signaling pathways, when combined with other essential signaling pathways inhibitors, can be novel targets for drug and drug combination prediction to improve cancer patients\u27 survival time. CONCLUSION: The proposed DeepSigSurvNet model can facilitate the understanding of the implications of signaling pathways on cancer patients\u27 survival by integrating multi-omics data and clinical factors

New Weather Indices for China: Tool of Risk Control of International Supply Chain

China is at the core of the world’s supply chain because of its focus on production and consumption. However, as weather can significantly affect supply chain operations, China plans to introduce weather derivatives to secure the multinational supply chain. Using historical records over the decade, weather derivatives could be an important tool for hedging risk and meeting the needs of Chinese market. In this paper, new weather indices for China financial markets are experimentally created through simulated machine learning to assess the ability of the weather indices to reduce risk. Through a simulation test from 2008 to 2017, the indices were found to successfully match 98% of the risk with the situation across two dimensions: i). changing Chinese weather data; and ii). a connection with US weather indices