Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Benjamin Marlin"'
Autor:
Sy-Miin, Chow, Inbal, Nahum-Shani, Justin T, Baker, Donna, Spruijt-Metz, Nicholas B, Allen, Ryan P, Auerbach, Genevieve F, Dunton, Naomi P, Friedman, Stephen S, Intille, Predrag, Klasnja, Benjamin, Marlin, Matthew K, Nock, Scott L, Rauch, Misha, Pavel, Scott, Vrieze, David W, Wetter, Evan M, Kleiman, Timothy R, Brick, Heather, Perry, Dana L, Wolff-Hughes, Einat, Liebenthal
Publikováno v:
Translational Behavioral Medicine. 13:7-16
The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b)
Publikováno v:
Proceedings of the Twentieth ACM Conference on Embedded Networked Sensor Systems.
Autor:
Shiwei Fang, Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin Marlin, Tarek Abdelzaher, Maggie B. Wigness
Publikováno v:
MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM).
Autor:
Jinyang Li, Runyu Ma, Vikram Sharma Mailthody, Colin Samplawski, Benjamin Marlin, Songqing Chen, Shuochao Yao, Tarek Abdelzaher
Publikováno v:
MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM).
Autor:
Benjamin Marlin, Hansuk Sohn
Publikováno v:
Journal of Simulation. 10:272-282
This research presents an assessment of the simulated futures of the Afghan educational system. We use a hybrid analytical process combining simulation, design of experiments, and data envelopment analysis (DEA) that is capable of studying the dynami
Publikováno v:
Computer Graphics Forum. 34:25-38
Autor:
Hansuk Sohn, Benjamin Marlin
Publikováno v:
SIMULATION. 90:800-814
Decision-makers have rightly come to expect thorough, relevant analysis prior to allocating resources. The field of education planning is no different in its requirement for such analysis. In this research, we present a discrete event simulation mode
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with intractable partition functions. In this paper, we study learning methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::204ae5e4be1c2be07d1f2a059fd16c3e
https://ora.ox.ac.uk/objects/uuid:d3682247-07db-448a-a0c2-b940997053b3
https://ora.ox.ac.uk/objects/uuid:d3682247-07db-448a-a0c2-b940997053b3
We consider estimation methods for the class of continuous-data energy based models (EBMs). Our main result shows that estimating the parameters of an EBM using score matching when the conditional distribution over the visible units is Gaussian corre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::97f9baeb882ab3f440bb581bb857eed4
https://ora.ox.ac.uk/objects/uuid:e5048031-d75a-4db9-bbf9-b7784875292f
https://ora.ox.ac.uk/objects/uuid:e5048031-d75a-4db9-bbf9-b7784875292f
Autor:
Benjamin Marlin, Nando de Freitas
Standard maximum likelihood estimation cannot be applied to discrete energy-based models in the general case because the computation of exact model probabilities is intractable. Recent research has seen the proposal of several new estimators designed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53be9d764e6ddea0892d397c98dcb73a
https://ora.ox.ac.uk/objects/uuid:13252030-d357-414b-a7a4-1b7bfa5509ec
https://ora.ox.ac.uk/objects/uuid:13252030-d357-414b-a7a4-1b7bfa5509ec