IST 597 Special Topics (Spring 2019)

Artificial Intelligence for Humanity

Course Description and Evalutation Criteria Document


Week Paper Readings Student Presentations
  1. Kube, Amanda, Sanmay Das, and Patrick J. Fowler. "Allocating Interventions Based on Predicted Outcomes: A Case Study on Homelessness Services.", AAAI 2019
  2. Ackermann, Klaus, et al. "Deploying Machine Learning Models for Public Policy: A Framework." Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, 2018.
  1. Yadav, Amulya, et al. "Influence maximization in the field: The arduous journey from emerging to deployed application." Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. AAMAS 2017.
  2. Optional: Lipton, Zachary. "The Mythos of Model Interpretability" Arxiv version.
  3. Optional: Finale Doshi-Velez, Been Kim. "Towards A Rigorous Science of Interpretable Machine Learning" Arxiv version.
  1. Kumar, Avishek, et al. "Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks." SIGKDD 2018.
  2. Kar, Debarun et al. "Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data", AAMAS 2017
  1. Selbst, Andrew, et al. "Fairness and Abstraction in Sociotechnical Systems." ACM Conference on Fairness, Accountability, and Transparency (FAT*) 2018
  • No Papers this Week! Lectures this week will cover Decision Theory and Computational Game Theory!
  • Class Canceled Due to Snow
  1. Erika Salomon, et al. "Reducing Incarceration through Prioritized Interventions." SIGKDD 2017.
  2. Garren Gaut et al. "Improving Government Response to Citizen Requests Online", COMPASS 2018
  3. Eric Potash et al. "Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning." KDD 2015.
  • No Papers this Week! Lectures this week will cover Neural Networks and Deep Learning!
  1. Fred Sun Lu et al. "Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis" JMIR 2018.
  2. Neal Jean et al. "Combining satellite imagery and machine learning to predict poverty", Science 2016
  3. Jiaxuan You et al. "Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data." AAAI 2017.
  1. Guest Lecture by Prof. Saeed Abdullah on Data science methods for Novel Assessment and Intervention Methods to support adolescent mental health.
  2. Manish Jain et al. "Deployed ARMOR Protection: The Application of a Game Theoretic Model for Security at the Los Angeles International Airport." AAMAS 2007.
  3. Christopher Kiekinveldt et al. "Computing Optimal Randomized Resource Allocations for Massive Security Games", AAMAS 2009
  • Spring Break. No Class
  1. Guest Lecture by Prof. Fei Fang from Carnegie Mellon University on Integrating Learning with Game Theory for Societal Challenges.
  2. No Papers this Week! Lectures this week will cover MDPs and POMDPs!
  1. Guest Lecture by Prof. Matthew Ferrari from Center of Infectious Disease and Dynamics, Penn State University on Modeling Measles Dynamics in Developing Countries.
  1. Benjamin Ford et al. "Protecting the NECTAR of the Ganga River through Game-Theoretic Factory Inspections, PAAMS 2016.
  2. Jason Tsai et al. "IRIS - A Tool for Strategic Security Allocation in Transportation Networks", AAMAS 2009
  3. Zahra Ashktorab et al. "Tweedr: Mining Twitter to Inform Disaster Response." ISCRAM 2014.
  1. No papers this week! Lecture will cover submodular optimization and influence maximization!
  1. Eric Shieh et al. "PROTECT: A Deployed Game Theoretic System to Protect the Ports of the United States", AAMAS 2012.
  2. Matthew Brown et al. "STREETS: Game-Theoretic Traffic Patrolling with Exploration and Exploitation", IAAI 2014
  3. William Haskell et al. "Robust protection of fisheries with COmPASS" IAAI 2014.
  1. Yadav, Amulya et al. "Using Social Networks to Aid Homeless Shelters: Dynamic Influence Maximization under Uncertainty." AAMAS 2016.
  2. Wilder, Bryan et al. "Uncharted but not Uninfluenced: Influence Maximization with an Uncertain Network", AAMAS 2017
  1. Stefano Ermon et al. "Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa", AAAI 2015.
  2. Stefano Ermon et al. "Learning policies for battery usage optimization in electric vehicles", Journal of Machine Learning
  3. Brown, Matthew et al. "One Size Does Not Fit All: A Game-Theoretic Approach for Dynamically and Effectively Screening for Threats" AAAI 2016.
  1. No papers this week! Lecture will cover Online Learning and Multi Armed Bandits!
  1. Bryan Wilder et al. "Controlling Elections through Social Influence" AAMAS 2018.
  2. Bryan Wilder et al. "End-to-End Influence Maximization in the Field", AAMAS 2018
  3. Amulya Yadav et al. "Please be an Influencer? Contingency-Aware Influence Maximization" AAMAS 2018.
  1. No papers this week! Lecture will cover material on Natural Language Processing and applications!
  1. Thomas Dietterich et al. "PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs" AAAI 2014.
  2. Ronan Le Bras et al. "Robust Network Design for Multispecies Conservation", AAAI 2013.
  3. Bryan Wilder et al. "Defending Elections Against Malicious Spread of Misinformation" AAAI 2019.
  1. Last Week of Class! No papers!
  1. Final Project Presentations Due

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