Last week I wrote and then gave two lectures on “Categorization” and “Practical Parallelism”. It was a ton of fun to prepare them, and actually giving them made me realize how much I miss teaching. Abstracts and slides follow.

Categorization

Student Organization for Cognitive Science (SOCS)
November 15, 2011 @ 5:30pm

Abstract: Categorization is a fundamental problem in cognitive science that goes by a multitude of names: In artificial intelligence, categorization is known as clustering; in mathematics, the problem is partitioning. There are many applications in linguistics, vision, and memory research. In this talk, I will provide a brief overview of exemplar vs. prototype models in the cognitive sciences (Goldstone & Kersten 2003), followed by an introduction to three different general-purpose clustering algorithms: k-means (MacQueen 1967), qt-clust (Heyer et al 1999), and information-theoretic clustering (Gokcayso & Principe 2002). Open-source Python implementations of each algorithm will be provided.

Slides

Practical Parallelism

CS Club Tech Talk
November 17, 2011 @ 7pm

Abstract: In this talk, I will give a brief overview of several key parallelism concepts and practical tools for several languages. After this talk, attendees should have the resources to recognize and solve “painfully parallel problems”. Topics will include: threads vs. processes, Amdahl’s Law, shared vs. distributed memory, synchronization, locks, pipes, queues, process pools, futures, OpenMP, MapReduce, Hadoop, and GPU programming.

Slides