Matches in SemOpenAlex for { <https://semopenalex.org/work/W2783754213> ?p ?o ?g. }
- W2783754213 abstract "We propose a generic spatiotemporal event forecasting method, which we developed for the National Institute of Justice's (NIJ) Real-Time Crime Forecasting Challenge. Our method is a spatiotemporal forecasting model combining scalable randomized Reproducing Kernel Hilbert Space (RKHS) methods for approximating Gaussian processes with autoregressive smoothing kernels in a regularized supervised learning framework. While the smoothing kernels capture the two main approaches in current use in the field of crime forecasting, kernel density estimation (KDE) and self-exciting point process (SEPP) models, the RKHS component of the model can be understood as an approximation to the popular log-Gaussian Cox Process model. For inference, we discretize the spatiotemporal point pattern and learn a log-intensity function using the Poisson likelihood and highly efficient gradient-based optimization methods. Model hyperparameters including quality of RKHS approximation, spatial and temporal kernel lengthscales, number of autoregressive lags, bandwidths for smoothing kernels, as well as cell shape, size, and rotation, were learned using crossvalidation. Resulting predictions significantly exceeded baseline KDE estimates and SEPP models for sparse events." @default.
- W2783754213 created "2018-01-26" @default.
- W2783754213 creator A5006718856 @default.
- W2783754213 creator A5020182705 @default.
- W2783754213 creator A5021031547 @default.
- W2783754213 creator A5032005702 @default.
- W2783754213 date "2018-01-09" @default.
- W2783754213 modified "2023-09-27" @default.
- W2783754213 title "Scalable high-resolution forecasting of sparse spatiotemporal events with kernel methods: a winning solution to the NIJ Real-Time Crime Forecasting Challenge" @default.
- W2783754213 cites W144670803 @default.
- W2783754213 cites W1531081428 @default.
- W2783754213 cites W1560724230 @default.
- W2783754213 cites W166741661 @default.
- W2783754213 cites W1746819321 @default.
- W2783754213 cites W181465672 @default.
- W2783754213 cites W1917966882 @default.
- W2783754213 cites W1933810044 @default.
- W2783754213 cites W1971287718 @default.
- W2783754213 cites W1972824446 @default.
- W2783754213 cites W1974891525 @default.
- W2783754213 cites W1981890344 @default.
- W2783754213 cites W1989520638 @default.
- W2783754213 cites W1991731880 @default.
- W2783754213 cites W2000978920 @default.
- W2783754213 cites W2002860785 @default.
- W2783754213 cites W2009912562 @default.
- W2783754213 cites W2041722960 @default.
- W2783754213 cites W2055195255 @default.
- W2783754213 cites W2057371135 @default.
- W2783754213 cites W2060940929 @default.
- W2783754213 cites W2063478392 @default.
- W2783754213 cites W2064758233 @default.
- W2783754213 cites W2070996757 @default.
- W2783754213 cites W2086260676 @default.
- W2783754213 cites W2090026919 @default.
- W2783754213 cites W2097360283 @default.
- W2783754213 cites W2099973661 @default.
- W2783754213 cites W2122825543 @default.
- W2783754213 cites W2123395972 @default.
- W2783754213 cites W2123906784 @default.
- W2783754213 cites W2131241448 @default.
- W2783754213 cites W2133530184 @default.
- W2783754213 cites W2144902422 @default.
- W2783754213 cites W2147876157 @default.
- W2783754213 cites W2154047075 @default.
- W2783754213 cites W2161075155 @default.
- W2783754213 cites W2162596909 @default.
- W2783754213 cites W2164891102 @default.
- W2783754213 cites W2167409531 @default.
- W2783754213 cites W2168464387 @default.
- W2783754213 cites W2170952786 @default.
- W2783754213 cites W2232870322 @default.
- W2783754213 cites W2269456039 @default.
- W2783754213 cites W2307249059 @default.
- W2783754213 cites W2321357844 @default.
- W2783754213 cites W2471455927 @default.
- W2783754213 cites W2511539680 @default.
- W2783754213 cites W2567030649 @default.
- W2783754213 cites W2579029485 @default.
- W2783754213 cites W2584805976 @default.
- W2783754213 cites W2589632792 @default.
- W2783754213 cites W2599025709 @default.
- W2783754213 cites W2607541615 @default.
- W2783754213 cites W2744556744 @default.
- W2783754213 cites W2785011159 @default.
- W2783754213 cites W2791059564 @default.
- W2783754213 cites W2794778778 @default.
- W2783754213 cites W2799211855 @default.
- W2783754213 cites W2883743474 @default.
- W2783754213 cites W2894881080 @default.
- W2783754213 cites W2900885930 @default.
- W2783754213 cites W2913369497 @default.
- W2783754213 cites W2964135075 @default.
- W2783754213 cites W2969323162 @default.
- W2783754213 cites W3099671035 @default.
- W2783754213 cites W3102356873 @default.
- W2783754213 cites W2564500591 @default.
- W2783754213 hasPublicationYear "2018" @default.
- W2783754213 type Work @default.
- W2783754213 sameAs 2783754213 @default.
- W2783754213 citedByCount "1" @default.
- W2783754213 countsByYear W27837542132018 @default.
- W2783754213 crossrefType "posted-content" @default.
- W2783754213 hasAuthorship W2783754213A5006718856 @default.
- W2783754213 hasAuthorship W2783754213A5020182705 @default.
- W2783754213 hasAuthorship W2783754213A5021031547 @default.
- W2783754213 hasAuthorship W2783754213A5032005702 @default.
- W2783754213 hasConcept C114614502 @default.
- W2783754213 hasConcept C119857082 @default.
- W2783754213 hasConcept C121332964 @default.
- W2783754213 hasConcept C122280245 @default.
- W2783754213 hasConcept C12267149 @default.
- W2783754213 hasConcept C126255220 @default.
- W2783754213 hasConcept C134306372 @default.
- W2783754213 hasConcept C149782125 @default.
- W2783754213 hasConcept C154945302 @default.
- W2783754213 hasConcept C159877910 @default.
- W2783754213 hasConcept C163716315 @default.
- W2783754213 hasConcept C27406209 @default.
- W2783754213 hasConcept C31972630 @default.