This morning, therefore, I created a new section on one of my office whiteboards: The KDD Tickle Spot.
- Computational Learning Theory (COLT): particularly computational geometry and information retrieval and extraction (IR/IE)
- Dynamic Decision Networks (DDNs) for Reinforcement Learning (RL): market driven policy learning
- Technique Selection in Critiquing-Based Tutoring: secondary and tertiary math education - formal rewrite systems for error diagnosis in algebra, plane geometry, precalculus (analytic geometry and trigonometry), calculus (AP Calc AB and BC or Calc I and II), vector analysis ("Calc III"), differential equations and linear algebra
- RoboSim Applications: partially-observable Markov Decision Processes (POMDPs) and procedural representations
- Probabilistic Relational Models for clustering: class identification and concept discovery - intra-configuration and inter-configuration in NSF ITR project
- Graphics models and kernel methods for time series learning (bioinformatics)
Topics he suggested, and that came out:
- Fundamental topics: e.g., entropy (data compression, learning, etc.)
- Computability and complexity theory: reductions for semidecidable (recursive enumerable but not recursive) and undecidable (non-recursive enumerable), and NP-hard, decision problems - namely, how to do them
- Proof patterns: diagonalization, structural induction, the "black art" of widget design (see above)
- Understanding solution approaches: cf. Polya's How To Solve It
- Recognizing algorithm patterns: divide-and-conquer (synthetic use of the Master Theorem), greedy, "radix sort"-type cleverness, approximation
- Applying algorithm patterns: analytical use of the Master Theorem, amortized, expected case, confidence (delta), error (epsilon), and ratio (rho) bounds
- Factoring methods: modularity by design, cohesion by systematic analysis of control structure boundaries and functional interfaces
ETA, 12:55 CDT Sat 30 Oct 2004: I should mention that what zengeneral calls "ticklish" and what I consider an interesting current topic of research do not necessarily coincide. As you can see from the above, zengeneral is looking at methodologies of proof and algorithm (and equation) derivation. It's the "showcase of problems" (including open ones such as "P == NP?") that are good for drawing and holding the attention of beginning CS students, he asserts.
Our department (Computing and Information Sciences at Kansas State University) is hosting its Alumni Advisory Council this homecoming week. Class is therefore relocated to the library (Nichols 233) - I hope you see this before 15:30, masaga, megruder, and zengeneral, and before 16:30, istari_ala.
Edit, 12:45 CDT: And now I realize that I am using LJ instead of verbal speech to announce meeting venue changes. Gah! zengeneral is sitting right in front of me and asked where the meeting is. Oops.
Later (c. 17:30), we will be giving a demo on our bayesnets software package, Bayesian Network tools in Java (BNJ) v3.
zengeneral: Privacy? What's that? All hail Patriot Act!
banazir: Verbal speech? What's that? All hail ascetic hermitage!