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检索条件"机构=Computer Science and Intelligent Systems Program"
214 条 记 录,以下是71-80 订阅
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Notes on the pursuit-evasion games between unmanned aerial vehicles operating in uncertain environments
Notes on the pursuit-evasion games between unmanned aerial v...
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2021 International Conference Engineering and Telecommunication, En and T 2021
作者: Khachumov, Mikhail Khachumov, Vyacheslav Systems Institute of RAS Intelligent Control Laboratory Program Pereslavl-Zalessky Russia RUDN University Federal Research Center 'Computer Science and Control' of RAS Information Technologies Department Moscow Russia
We solve the planar case of the urgent pursuit-evasion problem for players using various strategies of motion. The following options are considered: players perform piecewise-linear motions;the pursuer moves in a stra... 详细信息
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Solution to the Problem of Passing Over the Given Targets by an Unmanned Aerial Vehicle in an Unstable Environment
Solution to the Problem of Passing Over the Given Targets by...
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2023 International Russian Automation Conference, RusAutoCon 2023
作者: Khachumov, Mikhail Intelligent Control Laboratory Ailamazyan Program Systems Institute of Ras Pereslavl-Zalessky Russia Federal Research Center "Computer Science and Control"of Ras Moscow Russia Rudn University Moscow Russia
The paper gives a statement and considers the solution to an urgent problem of flying over the given targets by an unmanned aerial vehicle (UAV) in unstable conditions. A criterion is formulated for constructing effic... 详细信息
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Rapid modeling and analysis with QGENIE
Rapid modeling and analysis with QGENIE
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International Multiconference on computer science and Information Technology, IMCSIT '09
作者: Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok Technical University Wiejska 45A 15-351 Bialystok Poland
QGENIE is a specialized interface to GENIE, a decision modeling environment developed by the Decision systems Laboratory, University of Pittsburgh. QGENIE allows for rapid construction of graphical models in which all... 详细信息
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Does query-based diagnostics work?
Does query-based diagnostics work?
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8th Bayesian Modeling ApplicationsWorkshop, BMAW 2011
作者: Ratnapinda, Parot Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok University of Technology Wiejska 45A 15-351 Bialystok Poland
Query-based diagnostics (Agosta, Gardos, & Druzdzel, 2008) offers passive, incremental construction of diagnostic models that rest on the interaction between a diagnostician and a computer-based diagnostic system.... 详细信息
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An empirical evaluation of costs and benefits of simplifying Bayesian networks by removing weak arcs  27
An empirical evaluation of costs and benefits of simplifying...
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27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014
作者: Ratnapinda, Parot Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Faculty of Computer Science Bialystok University of Technology Wiejska 45A Bialystok15-351 Poland
We report the results of an empirical evaluation of structural simplification of Bayesian networks by removing weak arcs. We conduct a series of experiments on six networks built from real data sets selected from the ... 详细信息
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PAC Bayesian performance guarantees for deep (Stochastic) networks in medical imaging
arXiv
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arXiv 2021年
作者: Sicilia, Anthony Zhao, Xingchen Sosnovskikh, Anastasia Hwang, Seong Jae Intelligent Systems Program University of Pittsburgh Department of Computer Science University of Pittsburgh
Application of deep neural networks to medical imaging tasks has in some sense become commonplace. Still, a "thorn in the side" of the deep learning movement is the argument that deep networks are prone to o... 详细信息
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Importance sampling for general hybrid Bayesian networks
Importance sampling for general hybrid Bayesian networks
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11th International Conference on Artificial Intelligence and Statistics, AISTATS 2007
作者: Yuan, Changhe Druzdzel, Marek J. Department of Computer Science and Engineering Mississippi State University Mississippi State MS 39762 United States Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States
Some real problems are more naturally modeled by hybrid Bayesian networks that consist of mixtures of continuous and discrete variables with their interactions described by equations and continuous probability distrib... 详细信息
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Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition
Incorporating Geo-Diverse Knowledge into Prompting for Incre...
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Conference on computer Vision and Pattern Recognition (CVPR)
作者: Kyle Buettner Sina Malakouti Xiang Lorraine Li Adriana Kovashka Intelligent Systems Program Department of Computer Science University of Pittsburgh PA USA
Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to domain shifts in design and context. Class representations need to be adapted to more accurately reflect a... 详细信息
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Insensitivity of constraint-based causal discovery algorithms to violations of the assumption of multivariate normality
Insensitivity of constraint-based causal discovery algorithm...
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21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21
作者: Voortman, Mark Druzdzel, Marek J. Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Faculty of Computer Science Bialystok Technical University Wiejska 45A 15-351 Bialystok Poland
Constraint-based causal discovery algorithms, such as the PC algorithm, rely on conditional independence tests and are otherwise independent of the actual distribution of the data. In case of continuous variables, the... 详细信息
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Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth
Boosting Weakly Supervised Object Detection using Fusion and...
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IEEE Workshop on Applications of computer Vision (WACV)
作者: Cagri Gungor Adriana Kovashka Intelligent Systems Program University of Pittsburgh Department of Computer Science University of Pittsburgh
Despite recent attention to depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integratin...
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