Exploiting Data and Human Knowledge for Predicting Wildlife Poaching
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Lantao Yu | Weiping Li | Fei Fang | Chenyan Zhang | Haidong Zhang | Swaminathan Gurumurthy | Yongchao Jin | Lantao Yu | Swaminathan Gurumurthy | Fei Fang | Yongchao Jin | Chenyan Zhang | Weiping Li | Haidong Zhang
[1] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[2] Milind Tambe,et al. Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test , 2017, ECML/PKDD.
[3] Ting Yu. Incorporating prior domain knowledge into inductive machine learning : its implementation in contemporary capital markets , 2007 .
[4] Joseph A. Bishop,et al. Predicting and Preventing Elephant Poaching Incidents through Statistical Analysis, GIS-Based Risk Analysis, and Aerial Surveillance Flight Path Modeling , 2016 .
[5] A. Lemieux. Situational prevention of poaching , 2014 .
[6] Hugh P Possingham,et al. Track the impact of Kenya's ivory burn , 2016, Nature.
[7] Naphtali Rishe,et al. Integrating domain knowledge in supervised machine learning to assess the risk of breast cancer , 2014, Int. J. Medical Eng. Informatics.
[8] Milind Tambe,et al. CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection , 2016, AAMAS.
[9] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[10] Joydeep Ghosh,et al. Relaxed Oracles for Semi-Supervised Clustering , 2017, ArXiv.
[11] Hang-Bong Kang,et al. Prediction of crime occurrence from multi-modal data using deep learning , 2017, PloS one.
[12] D. Macmillan,et al. Poaching, Trade, and Consumption of Tiger Parts in the Bangladesh Sundarbans , 2016 .
[13] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[14] Nitesh V. Chawla,et al. Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains , 2011, J. Artif. Intell. Res..
[15] Milind Tambe,et al. Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers , 2018, AAMAS.
[16] Milind Tambe,et al. Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data , 2017, AAMAS.
[17] James E. Hines,et al. Are ranger patrols effective in reducing poaching‐related threats within protected areas? , 2018 .
[18] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[19] Milos Hauskrecht,et al. Group-Based Active Learning of Classification Models , 2017, FLAIRS.
[20] Aida Mustapha,et al. A study on classification learning algorithms to predict crime status. , 2013 .
[21] Milos Hauskrecht,et al. Active Learning of Classification Models from Soft-Labeled Groups , 2017 .
[22] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.