30,098 research outputs found
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
To relieve the pain of manually selecting machine learning algorithms and
tuning hyperparameters, automated machine learning (AutoML) methods have been
developed to automatically search for good models. Due to the huge model search
space, it is impossible to try all models. Users tend to distrust automatic
results and increase the search budget as much as they can, thereby undermining
the efficiency of AutoML. To address these issues, we design and implement
ATMSeer, an interactive visualization tool that supports users in refining the
search space of AutoML and analyzing the results. To guide the design of
ATMSeer, we derive a workflow of using AutoML based on interviews with machine
learning experts. A multi-granularity visualization is proposed to enable users
to monitor the AutoML process, analyze the searched models, and refine the
search space in real time. We demonstrate the utility and usability of ATMSeer
through two case studies, expert interviews, and a user study with 13 end
users.Comment: Published in the ACM Conference on Human Factors in Computing Systems
(CHI), 2019, Glasgow, Scotland U
TASKers: A Whole-System Generator for Benchmarking Real-Time-System Analyses
Implementation-based benchmarking of timing and schedulability analyses requires system code that can be executed on real hardware and has defined properties, for example, known worst-case execution times (WCETs) of tasks. Traditional approaches for creating benchmarks with such characteristics often result in implementations that do not resemble real-world systems, either due to work only being simulated by means of busy waiting, or because tasks have no control-flow dependencies between each other. In this paper, we address this problem with TASKers, a generator that constructs realistic benchmark systems with predefined properties. To achieve this, TASKers composes patterns of real-world programs to generate tasks that produce known outputs and exhibit preconfigured WCETs when being executed with certain inputs. Using this knowledge during the generation process, TASKers is able to specifically introduce inter-task control-flow dependencies by mapping the output of one task to the input of another
Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples
Embeddings mapping high-dimensional discrete input to lower-dimensional
continuous vector spaces have been widely adopted in machine learning
applications as a way to capture domain semantics. Interviewing 13 embedding
users across disciplines, we find comparing embeddings is a key task for
deployment or downstream analysis but unfolds in a tedious fashion that poorly
supports systematic exploration. In response, we present the Embedding
Comparator, an interactive system that presents a global comparison of
embedding spaces alongside fine-grained inspection of local neighborhoods. It
systematically surfaces points of comparison by computing the similarity of the
-nearest neighbors of every embedded object between a pair of spaces.
Through case studies, we demonstrate our system rapidly reveals insights, such
as semantic changes following fine-tuning, language changes over time, and
differences between seemingly similar models. In evaluations with 15
participants, we find our system accelerates comparisons by shifting from
laborious manual specification to browsing and manipulating visualizations.Comment: Equal contribution by first two author
The complexity of mesoporous silica nanomaterials unravelled by single molecule microscopy
Mesoporous silica nanomaterials are a novel class of materials that offer a highly complex porous network with nanometre-sized channels into which a wide amount of differently sized guests can be incorporated.
This makes them an ideal host for various applications for example in catalysis, chromatography and nanomedicine. For these applications, analyzing the host properties and understanding the complicated host–guest interactions is of pivotal importance. In this perspective we review some of our recent work that demonstrates that single molecule microscopy techniques can be utilized to characterize the porous silica host with unprecedented detail. Furthermore, the single molecule studies reveal sample heterogeneities and are a highly efficient tool to gain direct mechanistic insights into the host–guest interactions. Single molecule microscopy thus contributes to a thorough understanding of these nanomaterials enabling the development of novel tailor-made materials and hence optimizing their applicability significantly
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Design Space Exploration in Cyber-Physical Systems
Cyber physical systems (CPS) integrate a variety of engineering areas such as control, mechanical and computer engineering in a holistic design effort. While interdependencies between the different disciplines are key attributes of CPS design science, little is known about the impact of design decisions of the cyber part on the overall system qualities. To investigate these interdependencies, this paper proposes a simulation-based Design Space Exploration (DSE) framework that considers detailed cyber system parameters such as cache size, bus width, and voltage levels in addition to physical and control parameters of the CPS. We propose an exploration algorithm that surfs the parameter configurations in the cyber physical sub-systems, in order to approximate the Pareto-optimal design points with regards to the trade-os among the design objectives, such as energy consumption and control stability. We apply the proposed framework to a network control system for an inverted-pendulum application. The presented holistic evaluation of the identified Pareto-points reveals the presence of non-trivial trade-os, which are imposed by the control, physical, and detailed cyber parameters. For instance the identified energy and control optimal design points comprise configurations with a wide range of CPU speeds, sample times and cache configuration following non-trivial zig-zag patterns. The proposed framework could identify and manage those trade-os and, as a result, is an imperative rst step to automate the search for superior CSP configurations
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