This book constitutes the refereed proceedings of the 21st International Symposium on Methodologies for Intelligent systems, ISMIS 2014, held in Roskilde, Denmark, in June 2014. The 61 revised full papers were careful...
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ISBN:
(数字)9783319083261
ISBN:
(纸本)9783319083254
This book constitutes the refereed proceedings of the 21st International Symposium on Methodologies for Intelligent systems, ISMIS 2014, held in Roskilde, Denmark, in June 2014. The 61 revised full papers were carefully reviewed and selected from 111 submissions. The papers are organized in topical sections on complex networks and data stream mining; data mining methods; intelligent systems applications; knowledge representation in databases and systems; textual data analysis and mining; special session: challenges in text mining and semantic information retrieval; special session: warehousing and OLAPing complex, spatial and spatio-temporal data; ISMIS posters.
Gradient-based methods have been widely used for system design and optimization in diverse application domains. Recently, there has been a renewed interest in studying theoretical properties of these methods in the co...
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Gradient-based methods have been widely used for system design and optimization in diverse application domains. Recently, there has been a renewed interest in studying theoretical properties of these methods in the context of control and reinforcement learning. This article surveys some of the recent developments on policy optimization, a gradient-based iterative approach for feedback control synthesis that has been popularized by successes of reinforcement learning. We take an interdisciplinary perspective in our exposition that connects control theory, reinforcement learning, and large-scale optimization. We review a number of recently developed theoretical results on the optimization landscape, global convergence, and sample complexityof gradient-based methods for various continuous control problems, such as the linear quadratic regulator (LQR), control, risk-sensitive control, linear quadratic Gaussian (LQG) control, and output feedback synthesis. In conjunction with these optimization results, we also discuss how direct policy optimization handles stability and robustness concerns in learning-based control, two main desiderata in control engineering. We conclude the survey by pointing out several challenges and opportunities at the intersection of learning and control.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of appl...
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ISBN:
(数字)9783030054113
ISBN:
(纸本)9783030054106
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.
This volume contains selected and thoroughly revised papers plus contributions from invited speakers presented at the First International Workshop on C- straint Solving and Language Processing, held in Roskilde, Denma...
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ISBN:
(数字)9783540319283
ISBN:
(纸本)9783540261650
This volume contains selected and thoroughly revised papers plus contributions from invited speakers presented at the First International Workshop on C- straint Solving and Language Processing, held in Roskilde, Denmark, September 1–3, 2004. Constraint programming and Constraint Solving, in particular Constraint Logic programming, appear to be a very promising platform, perhaps the most promising present platform, for bringing forward the state of the art in natural language processing, this due to the naturalness in speci?cation and the direct relation to e?cient implementation. Language, in the present context, may - fer to written and spoken language, formal and semiformal language, and even general input data to multimodal and pervasive systems, which can be handled in very much the same ways using constraint programming. The notion of constraints, with slightly di?ering meanings, apply in the ch- acterization of linguistic and cognitive phenomena, in formalized linguistic m- els as well as in implementation-oriented frameworks. programming techniques for constraint solving have been, and still are, in a period with rapid devel- ment of new e?cient methods and paradigms from which language processing can pro?t. A common metaphor for human language processing is one big c- straintsolvingprocessinwhichthedi?erent(-lyspeci?ed)linguisticandcognitive phases take place in parallel and with mutual cooperation, which ?ts quite well with current constraint programming paradigms.
Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44 children. Like many neurological disorder phenotypes, the diagnostic features are observable, can be tracked over time, and...
Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44 children. Like many neurological disorder phenotypes, the diagnostic features are observable, can be tracked over time, and can be managed or even eliminated through proper therapy and treatments. However, there are major bottlenecks in the diagnostic, therapeutic, and longitudinal tracking pipelines for autism and related neurodevelopmental delays, creating an opportunity for novel data science solutions to augment and transform existing workflows and provide increased access to services for affected families. Several efforts previously conducted by a multitude of research labs have spawned great progress toward improved digital diagnostics and digital therapies for children with autism. We review the literature on digital health methods for autism behavior quantification and beneficial therapies using data science. We describe both case–control studies and classification systems for digital phenotyping. We then discuss digital diagnostics and therapeutics that integrate machine learning models of autism-related behaviors, including the factors that must be addressed for translational use. Finally, we describe ongoing challenges and potential opportunities for the field of autism data science. Given the heterogeneous nature of autism and the complexities of the relevant behaviors, this review contains insights that are relevant to neurological behavior analysis and digital psychiatry more broadly.
This volume contains a selection of revised papers that were presented at the Software Aspects of Robotic systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during O...
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ISBN:
(数字)9783642347818
ISBN:
(纸本)9783642347801
This volume contains a selection of revised papers that were presented at the Software Aspects of Robotic systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during October 17-18 in Vienna, Austria, under the auspices of the International Symposium Series on Leveraging Applications of Formal Methods, Verification, and Validation, ISoLA. The topics covered by the papers of the SARS and the MLSC workshop demonstrate the breadth and the richness of the respective fields of the two workshops stretching from robot programming to languages and compilation techniques, to real-time and fault tolerance, to dependability, software architectures, computer vision, cognitive robotics, multi-robot-coordination, and simulation to bio-inspired algorithms, and from machine learning for anomaly detection, to model construction in software product lines to classification of web service interfaces. In addition the SARS workshop hosted a special session on the recently launched KOROS project on collaborating robot systems that is borne by a consortium of researchers of the faculties of architecture and planning, computerscience, electrical engineering and information technology, and mechanical and industrial engineering at the Vienna University of Technology. The four papers devoted to this session highlight important research directions pursued in this interdisciplinary research project.
Reachability analysis consists in computing the set of states that are reachable by a dynamical system from all initial states and for all admissible inputs and parameters. It is a fundamental problem motivated by man...
Reachability analysis consists in computing the set of states that are reachable by a dynamical system from all initial states and for all admissible inputs and parameters. It is a fundamental problem motivated by many applications in formal verification, controller synthesis, and estimation, to name only a few. This article focuses on a class of methods for computing a guaranteed overapproximation of the reachable set of continuous and hybrid systems, relying predominantly on set propagation; starting from the set of initial states, these techniques iteratively propagate a sequence of sets according to the system dynamics. After a review of set representation and computation, the article presents the state of the art of set propagation techniques for reachability analysis of linear, nonlinear, and hybrid systems. It ends with a discussion of successful applications of reachability analysis to real-world problems.
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