Using Statistics to Search and Annotate Pictures

Google Tech Talks September 25, 2006

Nuno Vasconcelos is an Assistant Professor at the Electrical and Computer Engineering Department ... all » of the University of California, San Diego, where he heads the Statistical Visual Computing Laboratory. Before joining UCSD, he was a member of the research staff at the Compaq Cambridge Research Laboratory, which later became the HP Cambridge Research Laboratory. He received a PhD from MIT in 2000 and his areas of research interest are computer vision, statistical signal processing, machine learning, and multimedia. He is the recipient of a 2005 NSF CAREER award, and a Hellman Fellowship.

ABSTRACT The last decade has produced significant advances in content-based image retrieval, i.e. the design of computer vision systems for image search. I will review our efforts in the area, with emphasis on the subject of semantic retrieval. This consists of learning to annotate images, in order to support natural language queries. In particular, I will argue for a retrieval framework which combines the best properties of classical "query by visual example" (QBVE), and more recent semantic methods, and which we denote as "query by semantic example" (QBSE). While simple, we show that, when combined with ideas from multiple instance learning, this framework can be quite powerful. It improves semantic retrieval along a number of dimensions, the most notable of which is generalization (out-of-vocabulary queries). It can also be directly compared to query by example, making it possible to quantify the gains of representing images in semantic spaces. Our results show that these gains are quite significant, even when the semantic characterization is noisy and somewhat unreliable. This suggests an interesting hypothesis for computer vision: that it may suffice to adopt simple visual models, as long as they operate at various levels of abstraction and are learned from large amounts of data.

An Introduction to SQLite

Google TechTalks May 31, 2006

Richard Hipp

ABSTRACT SQLite is a small C library that implements a self-contained, embeddable, ... all » zero-configuration SQL database engine. SQLite implements a large subset of SQL-92 and stores a complete database in a single disk file. The library footprint is less than 250 KB making is suitable for use in embedded devices and applications where memory space is scarce.

This talk provides a quick overview of SQLite, its history, its strengths and weaknesses, and describes situations where it is much more useful than a traditional client/server database. The talk concludes with a discussion of the lessons learned from the development of SQLite and how those lessons can be applied to other projects.

Measuring Programmer Productivity

SLIDES

"ABSTRACT: Developers have been programming for the last 30 years in a wide variety of programming languages. Over the years, we have all developed a feeling for what it is in a programming language that makes us productive as programmers. As part of the DARPA HPCS (High Productivity Computing Systems) program, we are developing models and tools to measure programmer productivity. We will describe our data gathering process, and our effort to model programmer workflows using timed markov models. timed markov models."

A Googly MySQL Cluster Talk

Google TechTalks April 28, 2006
Stewart Smith Stewart Smith works for MySQL AB as a software engineer working on MySQL Cluster. He is ... all » an active member of the free and open source software community, especially in Australia.

ABSTRACT Part 1 - Introduction to MySQL Cluster The NDB storage engine (MySQL Cluster) is a high-availability storage engine for MySQL. It provides synchronous replication between storage nodes and many mysql servers having a consistent view of the database. In 4.1 and 5.0 it's a main memory database, but in 5.1 non-indexed attributes can be stored on disk. NDB also provides a lot of determinism in system resource usage. I'll talk a bit about that.

Part 2 - New features in 5.1 including cluster to cluster replication, disk based data and a bunch of other things. anybody that is attending the mysql users conference may find this eerily familiar.

Using Static Analysis For Software Defect Detection

Google TechTalks July 6, 2006
William Pugh

ABSTRACT I'll talk about some of my experience in using and expanding static analysis ... all » tools for defect detection. The FindBugs tool developed at the Univ. of Maryland is now being widely used, including inside Google.

I'll give an overview of FindBugs, show some of the kinds of errors we routinely find in production code, discuss the methodology we use for enhancing and expanding FindBugs and some of the recent additions to it, discuss ways of incorporating FindBugs into your development process (such as being able to get a report of all the warnings introduced since the last release of your software), and talk about the future of static analysis, including things such as a new Java JSR to provide standard annotations for things such as @NonNull and @Tainted.