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Multi-Label Classifier Chains for Bird Sound
[article]
2013
arXiv
pre-print
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Bird sound data collected with unattended microphones for automatic surveys, or mobile devices for citizen science, typically contain multiple simultaneously vocalizing birds of different species. However, few works have considered the multi-label structure in birdsong. We propose to use an ensemble of classifier chains combined with a histogram-of-segments representation for multi-label classification of birdsong. The proposed method is compared with binary relevance and three multi-instance
arXiv:1304.5862v2
fatcat:62pmpnejjjftzeyz3ewws6xtbm
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... lti-label learning (MIML) algorithms from prior work (which focus more on structure in the sound, and less on structure in the label sets). Experiments are conducted on two real-world birdsong datasets, and show that the proposed method usually outperforms binary relevance (using the same features and base-classifier), and is better in some cases and worse in others compared to the MIML algorithms.
Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations
[article]
2021
arXiv
pre-print
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Enabling humans to identify potential flaws in an agent's decision making is an important Explainable AI application. We consider identifying such flaws in a planning-based deep reinforcement learning (RL) agent for a complex real-time strategy game. In particular, the agent makes decisions via tree search using a learned model and evaluation function over interpretable states and actions. This gives the potential for humans to identify flaws at the level of reasoning steps in the tree, even if
arXiv:2109.13978v1
fatcat:srck72u6orc4tk7pgz75xlbyam
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... the entire reasoning process is too complex to understand. However, it is unclear whether humans will be able to identify such flaws due to the size and complexity of trees. We describe a user interface and case study, where a small group of AI experts and developers attempt to identify reasoning flaws due to inaccurate agent learning. Overall, the interface allowed the group to identify a number of significant flaws of varying types, demonstrating the promise of this approach.
Red deer exhibit spatial and temporal responses to hiking activity
2021
Wildlife Biology
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Explaining Reinforcement Learning to Mere Mortals: An Empirical Study
[article]
2019
arXiv
pre-print
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2019 pre-print arXiv:1903.09708v1 fatcat:hfca5yrbovhcdcc6il3vay6ccu
We present a user study to investigate the impact of explanations on non-experts' understanding of reinforcement learning (RL) agents. We investigate both a common RL visualization, saliency maps (the focus of attention), and a more recent explanation type, reward-decomposition bars (predictions of future types of rewards). We designed a 124 participant, four-treatment experiment to compare participants' mental models of an RL agent in a simple Real-Time Strategy (RTS) game. Our results show
arXiv:1903.09708v2
fatcat:e7b3wft65jb2rlbqoli2z2uc44
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... t the combination of both saliency and reward bars were needed to achieve a statistically significant improvement in mental model score over the control. In addition, our qualitative analysis of the data reveals a number of effects for further study.
Detecting and correcting user activity switches
2008
Proceedingsc of the 13th international conference on Intelligent user interfaces - IUI '09
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The TaskTracer system allows knowledge workers to define a set of activities that characterize their desktop work. It then associates with each user-defined activity the set of resources that the user accesses when performing that activity. In order to correctly associate resources with activities and provide useful activity-related services to the user, the system needs to know the current activity of the user at all times. It is often convenient for the user to explicitly declare which
doi:10.1145/1502650.1502670
dblp:conf/iui/ShenIBGKTCKSD09
fatcat:6cbgqk5lk5dwjkvuzbni2oqzdq
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... y he/she is working on. But frequently the user forgets to do this. TaskTracer applies machine learning methods to detect undeclared activity switches and predict the correct activity of the user. This paper presents TaskPredictor2, a complete redesign of the activity predictor in TaskTracer and its notification user interface. TaskPredictor2 applies a novel online learning algorithm that is able to incorporate a richer set of features than our previous predictors. We prove an error bound for the algorithm and present experimental results that show improved accuracy and a 180-fold speedup on real user data. The user interface supports negotiated interruption and makes it easy for the user to correct both the predicted time of the task switch and the predicted activity.
A systematic review of methods for studying the impacts of outdoor recreation on terrestrial wildlife
2020
Global Ecology and Conservation
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., 2009; Irvine et al., 2009) . ...
doi:10.1016/j.gecco.2020.e00917
fatcat:4hohcdcycndfnelpxqbngmnl3y
Reconstructing Velocities of Migrating Birds from Weather Radar – A Case Study in Computational Sustainability
2014
The AI Magazine
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Jed Irvine is a faculty research assistant at Oregon State University providing software development support to Tom Dietterich's machine-learning group. ...
doi:10.1609/aimag.v35i2.2527
fatcat:w3f6nkape5bjxbihq2eoepdu4q
Next-generation phenomics for the Tree of Life
2013
PLOS Currents
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The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing,
doi:10.1371/currents.tol.085c713acafc8711b2ff7010a4b03733
pmid:23827969
pmcid:PMC3697239
fatcat:zy6bcq3annawffxtswzgrtdchy
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... has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next-generation phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life.
The 9th annual MLSP competition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment
2013
2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
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Detecting insider threats in a real corporate database of computer usage activity
2013
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13
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This paper reports on methods and results of an applied research project by a team consisting of SAIC and four universities to develop, integrate, and evaluate new approaches to detect the weak signals characteristic of insider threats on organizations' information systems. Our system combines structural and semantic information from a real corporate database of monitored activity on their users' computers to detect independently developed red team inserts of malicious insider activities. We
doi:10.1145/2487575.2488213
dblp:conf/kdd/SenatorGMYRPHRBCEJBCGKZBMMWDFWDEILKFCFGJ13
fatcat:byb6q65tlfgntczndcx2fhzpom
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... e developed and applied multiple algorithms for anomaly detection based on suspected scenarios of malicious insider behavior, indicators of unusual activities, high-dimensional statistical patterns, temporal sequences, and normal graph evolution. Algorithms and representations for dynamic graph processing provide the ability to scale as needed for enterpriselevel deployments on real-time data streams. We have also developed a visual language for specifying combinations of features, baselines, peer groups, time periods, and algorithms to detect anomalies suggestive of instances of insider threat behavior. We defined over 100 data features in seven categories based on approximately 5.5 million actions per day from approximately 5,500 users. We have achieved area under the ROC curve values of up to 0.979 and lift values of 65 on the top 50 user-days identified on two months of real data.
Page 269 of Aerospace Engineering Vol. 17, Issue 9
[page]
1958
Aerospace Engineering
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Unit, JED, AGTD
Aero /Space Engineering 269 ...
., JED
Cliffe, Richard T., Jr., Tech. Engr., ANP Dept.
Clinton, R. L., Supvr., Tech. Objectives, Engr. Proj. Sect., JED
Cochran, David, Gen. Mgr., Fit. Lab. Dept. ...
A Post-Management System of Digital Assets on Social network Services
소셜 네트워크 서비스에 게시된 디지털 자산의 사후 관리 시스템
2015
Journal of Digital Convergence
소셜 네트워크 서비스에 게시된 디지털 자산의 사후 관리 시스템
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그래서 페이스 북은 이런 문제를 해결하기 위해서 UC Irvine 대 학교의 Jed R. Brubaker의 연구 결과를 적용하려고 시도하고 있다. 하지만 국내에서는 이런 노력들이 아직까지는 별 로 나타나지 않고 있다. ...
Facebook is trying to apply the findings Jed R. Brubaker of UC Irvine University in order to solve this problem. However, in Korea, such efforts, not much appears for now. ...
이것은 UC Irvine 대학교의 Jed Brubaker의 박사과정 연구논문에서부터 시작되었다. 이것의 동작 방법은 고인이 생전에 남긴 다 양한 디지털 자산들을 새롭게 수정하고 게시할 수 있도 록 한다. 심지어 고인을 대신해서 법적 대리인이 새로운 친구 맺기나 프로필 변경 등도 가능하다[9, 11, 12]. ...
doi:10.14400/jdc.2015.13.3.209
fatcat:rzzuxqqyibh5ljv4jrunqgssyi
Page 153 of None Vol. 27, Issue 3
[page]
1828
None
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Love, hatred, and_am- bition, have an end, and perish with the attainment of their object, and the hopes that Jed to it, But this sordid and unac- countable propensity is never satisfied; but continues ...
Irvin felt the tears start into his eyes, . « Unhappy young lady!” he said; “how many anxious ‘looks have you cast upon the ocean! how many prayers. have you breathed for his safety! ...
acknowledgments
[chapter]
2020
History, the Human, and the World Between
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, organized by Lindon Barrett; Steve Mailloux and the Critical Theory Emphasis at the University of California, Irvine, for inviting me to present my chapter on Edward Said and humanism; Sumathi Ramaswamy ...
requesting that I present my work on Ranajit Guha and historiography; the Indian Institute of Technology, Guwahati; the dynamic informal reading group in Murray Krieger Hall, University of California, Irvine ...
inviting me to present my thoughts about the relationship between intellectual work and disciplinarity; and my good friends and former students from the University of Massachusetts, Amherst, Prateeti Balal, Jed ...
doi:10.1515/9780822389309-001
fatcat:y4wj6tsrrnhrto34jjvukfmmgq
Page 882 of Annals of Internal Medicine Vol. 25, Issue 5
[page]
1946
Annals of Internal Medicine
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IRVINE, JED HOTCHKISS, New York, N. Y. Issos, Demetrios Nestor, Birmingham, Ala. Jenkins, Daniel Edwards, Ann Arbor, Mich. JENNINGS, HARRY NELSON, Calgary, Alberta, Can. ...
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