625.692.81 - Probabilistic Graphical Models

Expanded Course Description

Coursework and abilities in general concepts of probability. Having previous experience in coursework or applications with MarkovChains and/or Network models will also be a plus, but is not required.

Course Structure

The course content is divided into modules. Course Modules can be accessed by clicking Course Content on the left menu. A module will have several sections including the overview, content, readings, discussions, and assignments. Students are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted on the Course Outline page. Students should regularly check the Calendar and Announcements for assignment due dates.

Course Topics

• Module 1: Introduction, Reminder of Probability Theory, Overview of Graphs
• Module 2: Bayesian Networks
• Module 3: Undirected Graphical Models
• Module 4: Template Based Representations
• Module 5: Gaussian Network Models; Exponential Family Models
• Module 6: Exact Inference
• Module 7: Clique Trees and Belief Propagation
• Module 8: Inference as Optimization
• Module 9: Particle based Approximate Inference
• Module 10: MAP inference and Dirichlet Learning
• Module 11: Learning from Directed Models
• Module 12: Learning from Undirected Models
• Module 13: Partially Observed Data
• Module 14: Structured Decision Problems and Causality

Course Goals

Determining an optimal graphical model and solving real-world questions on that model are skills needed for dealing with large data and complex questions. While simple questions can be addressed in a single statement of probability or looked up quickly in an Excel database, questions with many linked events that build to create a complex network are not trivial to define optimally or to query for learning. This course has as its overarching goal the creation of an ability to work confidently with graphical models andtheir applications to real-world problems.

Course Learning Outcomes (CLOs)

• Explain theoretical principles and practical approaches to create, usefully apply, and maintain an application of graphical models for domain specific problems.
• Apply strategies and skills for structured learning and inference on graphical models.
• Create graphical models for domain problems of interest to you and realize how to solve and apply them to other domains.
• Challenge poorly designed graphical models and poorly addressed inference, learning and optimization problems for graphical models.
• Understand and analyze the utility of graphical models for Big Data applications.

Textbooks

Required

Probabilistic Graphical Models, by Daphne Koller and Nir Friedman, MIT Press, 2009 ISBN 978-0-262-0139-2

Optional

Pattern Recognition and Machine Learning by Christopher M. Bishop, Springer, 2006 [ISBN 978-0387-31073-2]

This is an optional text for those looking for a different take on presentation of the material and/or for different homework problems.

Textbook information for this course is available online through the appropriate bookstore website: For online courses, search the MBS website at http://ep.jhu.edu/bookstore.

Student Coursework Requirements

It is expected that each class will take approximately 9–12 hours per week to complete. Here is an approximate breakdown: reading the assigned sections of the texts (approximately 2 hours per week) as well as some outside reading, listening to the audio annotated slide presentations (approximately 2 hours per week), contributing to the discussion forum (approximately 1-2 hours per week), problem assignments (approximately 2-3 hours per week) and progress on the term project (roughly 2-3 hours per week).

This course will consist of three basic student requirements:

Participation (Class Discussions and Journals) (30% of Final Grade Calculation; 15% for each)

Each student is responsible for carefully reading all assigned material and being prepared for discussion. The majority ofreadings are from the course text. Additional reading may be assigned to supplement text readings.

In addition to the open discussion each student will keep a journal throughout the length of the course. The journal will be a forum for exploration of the topic that is read by the instructor and used to provide additional feedback on the students progress. The journal entries are related to the subjects covered each week and students should take responsibility for timely and topical entrance of material to their journal. Keeping a journal is an extremely good habit forlearning to organize and think through new material. The instructor will be evaluating how engaged the journal entries are with the material and how deeply considered is the grappling with new concepts.

Post your initial response to the discussion questions by the evening of day 3 for that module week. Posting a response to the discussion question is the first part of your grade for class discussions.

Part two of your grade for class discussions is your interaction (i.e., responding to classmate postings with thoughtful responses) with at least two classmates (i.e., Critical Thinking). Just posting your response to a discussion question isnot sufficient; I want you to interact with your classmates. Be detailed in your postings and in your responses to your classmates' postings. Feel free to agree or disagree with your classmates. Please ensure that your postings are civil and constructive.

I will monitor class discussions and will respond to some of the discussions as discussions are posted. In some instances, I will summarize the overall discussions and post the summary for the class.

Your journal entries should be consistent throughout the week. Please don’t plan on doing one massive journal entry at the end of the week. The grading of your journal entries will evaluate the degree of your involvement with the subject and your willingness to think beyond the textbook for how the material might be applied to areas that interest you. Documenting your thoughts and explorations is a central part of a successful career and the initial steps along that pathare part of what is being evaluated through your journal entries. Thus, your growth and your engagement with the material should be evident through what you put into the journal.

Problem Sets/Assignments (30% of Final Grade Calculation)

Assignments will largely consist of problem sets from the main textbook. Include a cover sheet with your name and assignment identifier. Also include your name and a page number indicator (i.e., page x of y) on each page of your submissions. Each problem should have the problem statement, assumptions, computations, and conclusions /discussion delineated. All Figures and Tables should be captioned and labeled appropriately. Please use pdf for the files that you submit.

Students need to take care on the file-naming convention for uploading coarse-work in Canvas (e.g.: Last_name_problem_number_title)

Avoid capital letters, spaces, hyphens, period, colon (things that html has problems with).

Individual Project (40% of Final Grade Calculation)

You each will choose a project that will build throughout the class. There are four deliverables during the 14-weeks of the class that should document your progress on your project. The first deliverable is the choice of topic. This needs to becarefully thought through and considered. You want to pick something that is substantial, but not overly ambitious. Likewise you want to make sure that its not trivial. The overall project should impress those who know the subject, butshould also be a level of work that you can bring to completion with your skill set and time availability. You will be evaluated on the quality of your estimate for what you can do and what you accomplish with the project.

Detailed Rubrics are available for the evaluation of each of the three components. Basically the following criteria will be used:

Discussions (15% of grade): (1) number of original posts, replies to other posts (politeness, on-topic, helpful and engaged comments), (2) quality of post (logical argument, depth of engagement with material, politeness, on-topic), (3) originality of post (going beyond the usual or a web-search), and as part of the same component.

Personal Journal Entries (15% of grade): (1) number of entries, quality of entries (originality, degree of engagement with the material, amount of effort demonstrated), (2) originality of entries (going beyond the book/modest web search; demonstrating clear independent thinking), (3) willingness to think outside the boundaries of the class and to find problems/application domains that impact on your interests.

Problem Sets (30% of grade): (1) all assigned problems completed, extra-credit for more problems done (maximum of five extra points) (2) quality of work (intermediate steps demonstrated, neatly and clearly organized), (3) final answer correct (with steps illustrated and with final answer clearly demonstrated).

Project (40% of grade); with four deliverables before the final due date).

Topic (10% of grade): (1) doable-ness of the project (not too hard and not too easy), (2) amount of thinking behind the topic choice demonstrated (the why that project question), (3) some presentation of nearby alternative topics and why they were not selected (further rationalizing the choice and its do-ability).

Outline/Bibliography (15% of grade): (1) quality and quantity of references; (2) initial demonstration of grappling with the topic through outline; quality and originality of the outline; (3) continued ‘doability’ check (that ‘mission creep’ hasn’t happened with it becoming too hard or too easy).

Pseudo Code (15% of grade): (1) should flow logically, (2) should be clearly laid out, (3) amount of actual underlying code or math needed to fill in the steps should be possible to estimate from the pseudo code.

Fifty-percent Done (10% of grade): (1) continued ‘doability’ check, should clearly be showing significant progress (not just the easy things done with all the hard work ahead); (2) ideally working prototypes of code with demonstrations that they are working; (3)logical analysis of the remaining steps to completion and timelines for when those will be done.

Final (50% of grade): (1) quality of final work (significant class project achieved on-time), (2) steps clearly defined and described, if code (quality of documentation, quality of demonstration that it works correctly), if math (quality of intermediate steps; demonstration of logical completeness and soundness of result), if bio-related (connections to literature and to other bio projects in literature demonstrated; quality of results and logical connections to intermediate steps) (3) context clearly documented (connections to other’s work; ideal end-point for this type of project; any possible connections to your own long term goals and plans).

Grading Policy

The final grade will be a combination of these three components to be evaluated during the 14-week long course. First, all students will be contributing to the discussion forum and keeping a journal of events related to graphical models and you will be discussing ideas and concepts regarding graphical models in the discussion forum and in your journal (these two together are 30% of the total).The level of discussion participation and the quality of your journal keeping will be the first component of the grade. Second, for each module, there will be homework problems that are assigned at the start of the week and due at the end of the week. This is another 30% of the grade. For these assignments, the start of the week is seen as Wednesday and they will be due on Tuesday by 11 PM.The last component of the grade is a term-long project (40% of total). This project will be staged with four milestones along the way that are graded for completion and their connection to the overall project. The goal of these components to the grading and of the overall course framework is to aid the students in learning the material.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellencein all aspects of assignments, journal entries, and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteriaapply to both undergraduates and graduate students taking the course.

EP uses a +/- grading system (see “Grading System”, Graduate Programs catalog, p. 10).

Final grades will be determined by the following weighting:

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.