CS 7840 — Foundations and Applications of Information Theory
4 semester hoursGraduateLectureusually offered: falltypical days: M/ThBostonTraditional
Studies information theory and selected applications for data management, machine learning, and information retrieval. Information theory examines the transmission, processing, extraction, and utilization of information. Topics include entropy; mutual information; cross-entropy; data processing theorem; information inequalities; Cox's theorem; maximum entropy solutions; and applications such as data normalization, decision trees, maximum likelihood, logistic regression, and VC dimensions. Requires prior study of standard computer science algorithms. Offers hands-on experience through a flexible project, allowing students to explore information theory in aspects related to their PhD research.
Prerequisites
- Requires prior study of standard computer science algorithms
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2024 | 1 | 13 | 29 | 45% | 16.0 |
| Fall 2025 | 1 | 15 | 30 | 50% | 15.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 100% · T 0% · W 46% · Th 54% · F 0%
Common patterns: MR (54% of sections), MW (46% of sections) — in patterns, R means Thursday
Professors
Fall
- Wolfgang Gatterbauer (54% of students) · reviews
- Javed Aslam (46% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (CS course descriptions) · Student reviews on RateMyHusky · All CS courses · Plan it at numap.app