11,267 research outputs found

    Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms

    Get PDF
    We present an interactive version of an evidence-driven state-merging (EDSM) algorithm for learning variants of finite state automata. Learning these automata often amounts to recovering or reverse engineering the model generating the data despite noisy, incomplete, or imperfectly sampled data sources rather than optimizing a purely numeric target function. Domain expertise and human knowledge about the target domain can guide this process, and typically is captured in parameter settings. Often, domain expertise is subconscious and not expressed explicitly. Directly interacting with the learning algorithm makes it easier to utilize this knowledge effectively.Comment: 4 pages, presented at the Human in the Loop workshop at ICML 201

    Improving Missing Data Imputation with Deep Generative Models

    Full text link
    Datasets with missing values are very common on industry applications, and they can have a negative impact on machine learning models. Recent studies introduced solutions to the problem of imputing missing values based on deep generative models. Previous experiments with Generative Adversarial Networks and Variational Autoencoders showed interesting results in this domain, but it is not clear which method is preferable for different use cases. The goal of this work is twofold: we present a comparison between missing data imputation solutions based on deep generative models, and we propose improvements over those methodologies. We run our experiments using known real life datasets with different characteristics, removing values at random and reconstructing them with several imputation techniques. Our results show that the presence or absence of categorical variables can alter the selection of the best model, and that some models are more stable than others after similar runs with different random number generator seeds

    Don't break a leg: Running birds from quail to ostrich prioritise leg safety and economy in uneven terrain

    Get PDF
    Cursorial ground birds are paragons of bipedal running that span a 500-fold mass range from quail to ostrich. Here we investigate the task-level control priorities of cursorial birds by analysing how they negotiate single-step obstacles that create a conflict between body stability (attenuating deviations in body motion) and consistent leg force–length dynamics (for economy and leg safety). We also test the hypothesis that control priorities shift between body stability and leg safety with increasing body size, reflecting use of active control to overcome size-related challenges. Weight-support demands lead to a shift towards straighter legs and stiffer steady gait with increasing body size, but it remains unknown whether non-steady locomotor priorities diverge with size. We found that all measured species used a consistent obstacle negotiation strategy, involving unsteady body dynamics to minimise fluctuations in leg posture and loading across multiple steps, not directly prioritising body stability. Peak leg forces remained remarkably consistent across obstacle terrain, within 0.35 body weights of level running for obstacle heights from 0.1 to 0.5 times leg length. All species used similar stance leg actuation patterns, involving asymmetric force–length trajectories and posture-dependent actuation to add or remove energy depending on landing conditions. We present a simple stance leg model that explains key features of avian bipedal locomotion, and suggests economy as a key priority on both level and uneven terrain. We suggest that running ground birds target the closely coupled priorities of economy and leg safety as the direct imperatives of control, with adequate stability achieved through appropriately tuned intrinsic dynamics

    Refinement of Techniques Metallographic Analysis of Highly Dispersed Structures

    Get PDF
    Flaws are regularly made while developing standards and technical specifications. They can come out as minor misprints, as an insufficient description of a technique. In spite the fact that the flaws are well known, it does not come to the stage of introducing changes to standards. In this paper shows that in the normative documents is necessary to clarify the requirements for metallurgical microscopes, which are used for analysis of finely-dispersed

    January 1932

    Get PDF

    January 1944

    Get PDF

    July 1934

    Get PDF

    October 1933

    Get PDF

    November 1943

    Get PDF
    corecore