Sep 6, 11, 13: Logistics and introduction to machine learning models and ecology study
K. P. Murphy. (2012) Machine Learning: A Probabilistic Perspective. The MIT Press.
Chp 7 (linear regression), 8 (logistic regression), 9.3 (Generalized Linear Models (GLM)), 15 (Gaussian processes), 17 (Markov chain and hidden Markov chain), 28 (deep learning).
Sep 18, 20: data collection methods
J.D. Wegner, S. Branson, D. Hall, K. Schindler, and P. Perona. (2016) Cataloging Public Objects Using Aerial and Street-Level Images. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). [link].
D. Sheldon, A. Farnsworth, and J. Irvine. (2013) Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar. In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI). [link].
A. Farnsworth, D. Sheldon, J. Geevarghese, J. Irvine, B. V. Doren, K. Webb, T. Dietterich and S. Kelling. (2014). Reconstructing Velocities of Migrating Birds from Weather Radar — A Case Study in Computational Sustainability. Ai Magazine. [link].
Sep 25, 27: Sensor placement
C. Guestrin, A. Krause, and A. Singh. (2005) Near-optimal sensor placements in gaussian processes. Proceedings of the 22nd International conference on Machine Learning (ICML). [link]
Y. Xue, B. Dilkina, T. Damoulas, and D. Fink. (2013) Improving Your Chances: Boosting Citizen Science Discovery. AAAI Conference on Human Computation and Crowdsourcing. [link]
Oct 2, 4: Weakly supervised learning
F. Briggs, B. Lakshminarayanan, L. Neal, X. Fern, R. Raich, S. Frey, A. Hadley, and M. G. Betts. (2012) Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach. Journal of the Acoustical Society of America, vol. 131, no. 6, pp. 4640–4650. [link].
A. T. Pham, R. Raich, X. Z. Fern, and J. P. Arriaga. (2015) Multi-instance multi-label learning in the presence of novel class instances. Proceedings of the 32nd International conference on Machine Learning (ICML). [link].
Oct 11, 16: Occupancy-detection model
D. MacKenzie, J. Nichols, G. Lachman, S. Droege, J. A. Royle, and C. Langtimm. (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83(8), pp.~2248–2255. [link]
R. Hutchinson, L.-P. Liu, and T. Dietterich. (2011) Incorporating Boosted Regression Trees into Ecological Latent Variable Models. AAAI Conference on Artificial Intelligence (AAAI). [link].
Oct 18, 23: Species Distribution Modeling
S. Phillips, M. Dudík, and R. Schapire, A maximum entropy approach to species distribution modeling. Proceedings of the twenty-first International Conference on Machine Learning (ICML), pp. 655–662, 2004. [link].
N. Golding, and B. V. Purse. (2016) Fast and flexible Bayesian species distribution modelling using Gaussian processes. Methods in Ecology and Evolution, 7: 598–608. [link]
Oct 25, 30: Species Distribution Modeling with spatial modeling
A. Datta, S. Banerjee, A. O. Finley, and A. E. Gelfand. (2016) Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets. Journal of the American Statistical Association, 111(514). [link].
E. E. Crone. (2016) Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower. Journal of Ecology 104: 281-291. [link].
Nov 1, 6: Trajectories modeling
T. A. Patterson, A. Parton, R. Langrock, P. G. Blackwell. L. Thomas, and R. King. (2016) Statistical modelling of individual animal movement: an overview of key methods and a discussion of practical challenges. ArXiv e-prints stat.AP, 1603.07511. [link]
D. Sheldon, T. G. Dietterich. (2011) Collective Graphical Models. Advances in Neural Information Processing Systems 24 (NIPS 2011). [link]
Nov 8, 13: Trajectories modeling – a diffusion approach
D. R. Brillinger. (2010) Modeling Spatial Trajectories. In: Handbook of Spatial Statistics Edited by A. E. Gelfand, P. Diggle, P. Guttorp, and M. Fuentes. CRC Press. [link].
Y. Zhang. (2015) Trajectory Data Mining: An Overview. ACM Transactions on Intelligent Systems and Technology. Volume 6 Issue 3, Article No.29. [link].
Nov 15, 20: Capture recapture modeling
D. L. Borchers and M. G. Efford. (2008) Spatially Explicit Maximum Likelihood Methods for Capture-Recapture Studies. Biometrics, 64(2), pp.~377-385. [link]
A. K. Fuller, C. S. Sutherland, J. A. Royle, M. P. Hare. (2016) Estimating population density and connectivity of American mink using spatial capture–recapture. Ecological Applications, 26(4), pp.~1125–1135. [link]
Nov 27, 29: Machine Learning for Climate Change
C. Monteleoni, G. Schmidt, S. Saroha, and E. Asplund. (2011). Tracking climate models. Statistical Analysis and Data Mining: Special Issue on Best of CIDU 4(4):72–392. [link]
S. McQuade and M. Claire. (2012). Global Climate Model Tracking Using Geospatial Neighborhoods. In AAAI. [link]