595 research outputs found

    Covariate-invariant gait analysis for human identification(人識別を目的とする共変量不変歩行解析)

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    信州大学(Shinshu university)博士(工学)ThesisYEOH TZE WEI. Covariate-invariant gait analysis for human identification(人識別を目的とする共変量不変歩行解析). 信州大学, 2018, 博士論文. 博士(工学), 甲第692号, 平成30年03月20日授与.doctoral thesi

    FUNCK: Information Funnels and Bottlenecks for Invariant Representation Learning

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    Learning invariant representations that remain useful for a downstream task is still a key challenge in machine learning. We investigate a set of related information funnels and bottleneck problems that claim to learn invariant representations from the data. We also propose a new element to this family of information-theoretic objectives: The Conditional Privacy Funnel with Side Information, which we investigate in fully and semi-supervised settings. Given the generally intractable objectives, we derive tractable approximations using amortized variational inference parameterized by neural networks and study the intrinsic trade-offs of these objectives. We describe empirically the proposed approach and show that with a few labels it is possible to learn fair classifiers and generate useful representations approximately invariant to unwanted sources of variation. Furthermore, we provide insights about the applicability of these methods in real-world scenarios with ordinary tabular datasets when the data is scarce.Comment: 28 page
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