BestTechVideos: Tag conferences Videos

How To Be Normal - A Guide For Developers

scoundrel — Thu, 17 Apr 2008 19:10:04 GMT

At some point in every software project involving a database it becomes necessary for the developers who created (or inherited) the project to step back and take a look at their database. Many projects have a database schema that has evolved over time, with columns added here and tables added there, increasing complexity and often adding redundancy. Super-tables grow with more and more columns making ALTERs slow and backups difficult.

In this session MySQL author and speaker Mike Hillyer will guide the audience through the principles of database normalization and review some common normalization scenarios encountered by many application developers.

Topics include:

What is normalization and what are its benefits?
What are the normal forms?
- First Normal Form
- Second Normal Form
- Third Normal Form
- And so on…
Normalization Scenarios
Relationships and Joins
How Much is Too Much?

This session is intended for a beginner to intermediate audience and is applicable to developers and administrators who deal with database design.

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Browse the archive of posts filed under Conferences, Databases, Development, Design, MySQL, Lectures, Computer Science

Scene Discovery by Matrix Factorization

scoundrel — Mon, 07 Apr 2008 22:51:58 GMT

Google Tech Talks
March, 24 2008

ABSTRACT

What constitutes a scene? Defining a meaningful vocabulary for scene discovery is a challenging problem that has important consequences for object recognition. We consider scenes to depict correlated objects and present visual similarity. We introduce a max-margin factorization model that finds a low dimensional subspace with high discriminative power for correlated annotations. We postulate this space should allow us to discover a large number of scenes in unsupervised data; we show scene discrimination results on par with supervised approaches. This model also produces state of the art word prediction results including good
annotation completion.

Speaker: Ali Farhadi
Ali Farhadi is a PhD student in the UIUC Computer Science Department working on computer vision and machine learning under David Forsyth. His interests include image segmentation, transfer learning, scene understanding and human activity recognition.

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Browse the archive of posts filed under Conferences, Companies, Broadcasting, Science, Techtalks, Google, Lectures, Math, Computer Science

Movie/Script: Alignment and Parsing of Video and Text Transcription

scoundrel — Mon, 07 Apr 2008 22:51:25 GMT

Google Tech Talks
March, 26 2008

ABSTRACT

Timothee Cour - Research Scientist

Movies and TV are a rich source of highly diverse and complex video of people, objects, actions and locales "in the wild". Harvesting automatically labeled sequences of actions from video would enable creation of large-scale and highly-varied datasets. To enable such collection, we focus on the task of recovering scene structure in movies and TV series for object/person tracking and action retrieval. We present a weakly supervised algorithm that uses the screenplay and closed captions to parse a movie into a hierarchy of shots and scenes. Scene boundaries in the movie are aligned with screenplay scene labels and shots are reordered into a sequence of long continuous tracks or threads which allow for more accurate tracking of people and actions across shot boundaries. Scene segmentation, alignment, and shot threading are formulated as inference in a unified generative model and a novel hierarchical dynamic programming algorithm that can handle alignment and jump-limited reorderings in linear time is introduced. We present quantitative and qualitative results on movie alignment and parsing, and use the recovered structure for tracking and naming of characters as well as retrieval of common actions in several episodes of popular TV series.

If time permits we will also present our recent results on approximate inference with eigenvalue optimization.

Speaker: Timothee Cour - Research Scientist
Timothee Cour is a fifth year PhD student at the University of Pennsylvania, Philadelphia, in Computer Science. He completed his undergraduate education at the Ecole Polytechnique in France, majoring in Computer Science and Applied Mathematics. His research advisor is Prof. Ben Taskar and he also worked closely with Prof. Jianbo Shi.

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Browse the archive of posts filed under Conferences, Companies, Science, Techtalks, Google, Lectures, DSP, Computer Science

Optimization for Machine Learning

scoundrel — Mon, 07 Apr 2008 22:50:57 GMT

Google Tech Talks
March, 25 2008

ABSTRACT

S.V.N. Vishwanathan - Research Scientist

Regularized risk minimization is at the heart of many machine learning algorithms. The underlying objective function to be minimized is convex, and often non-smooth. Classical optimization algorithms cannot handle this efficiently. In this talk we present two algorithms for dealing with convex non-smooth objective functions. First, we extend the well known BFGS quasi-Newton algorithm to handle non-smooth

functions. Second, we show how bundle methods can be applied in a machine learning context. We present both theoretical and experimental justification of our algorithms.

Speaker: S.V.N. Vishwanathan - Research Scientist - Zurich
S.V.N Vishwanathan is a principal researcher in the Statistical Machine Learning program, National ICT Australia with an adjunct appointment at the College of Engineering and Computer Science(CECS), Australian National University. I got my Ph.D in 2002 from the Department of Computer Science and Automation (CSA) at the Indian Institute of Science.

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Browse the archive of posts filed under Conferences, Companies, Science, Techtalks, Google, Lectures, Computer Science

Railscast: 5 View Tips

scoundrel — Mon, 07 Apr 2008 22:50:29 GMT

Here's five quick tips to use in views. Be sure to catch the end of the episode where I reveal an exciting contest!

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Browse the archive of posts filed under Conferences, Development, Frameworks, Techtalks, Ruby, Screencasts, Ruby On Rails

JRuby: The power of Java and Ruby

scoundrel — Wed, 02 Apr 2008 17:59:50 GMT

Google Tech Talks
February, 28 2008

Speaker: Ola Bini
I work for ThoughtWorks Studios, and recently published the book Practical JRuby on Rails at APress. I'm very interested in Artificial Intelligence, Lisp, Ruby and the fuzzy lines between languages...

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Browse the archive of posts filed under Conferences, Companies, Development, Techtalks, Sun, Google, Java, Ruby, Lectures

Algorithms for Data Management and Migration

scoundrel — Mon, 24 Mar 2008 16:11:11 GMT

Google Tech Talks
January, 23 2008

ABSTRACT

I will describe some algorithms for addressing some fundamental optimization problems that arise in the context of data storage and management. In the first part of the talk we will address the following question: How should we store data in order to effectively cope with non-uniform demand for data? How many copies of popular data objects do we need? Where should we store them for effective load balancing?

In the second part of the talk we will address the issue of moving data objects quickly, to react to changing demand patterns. We will develop approximation algorithms for these problems.

The first part of the talk is joint work with Golubchik, Khanna,Thurimella and Zhu. The second part is joint work with Kim and Wan.

Speaker: Samir Khuller
Samir Khuller received his M.S and Ph.D from Cornell University in 1989 and 1990, respectively. He spent 2 years as a Research Associate at the Institute for Advanced Computer Studies at the University of Maryland, before joining the Computer Science Department in 1992, where he is a Professor and Associate Chair in the Department of Computer Science.

His research interests are in graph algorithms, discrete optimization, and computational geometry. He has published about 130 journal and conference papers, and several book chapters on these topics. He received the National Science Foundation's Career Development Award, the Dean's Teaching Excellence Award and also a CTE-Lilly Teaching Fellowship. In 2003, he and his students were awarded the "Best newcomer paper" award for the ACM PODS Conference. He received the University of Maryland's Distinguished Scholar Teacher Award in 2007.

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Browse the archive of posts filed under Conferences, Companies, Development, Science, Techtalks, Google, Lectures, Computer Science

KDE4 Release Event

scoundrel — Sat, 22 Mar 2008 05:03:47 GMT

Google Tech Talks
January 18, 2008

ABSTRACT

Celebration of the KDE 4.0 release, a culmination of several years of design, development and testing.

Speaker: Paul Adams

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Browse the archive of posts filed under OS, Conferences, Linux, Techtalks, Screencasts, Lectures

Content Delivery Network Pricing, Costs for Outsourced Video Delivery

scoundrel — Wed, 12 Mar 2008 23:35:59 GMT

Whether you’re in an organization that needs to deliver lots of video or a smaller company that needs to deliver only a few videos, the going rate for these services can still be hard to figure out. What variables determine the final price? What is the going rate when you outsource delivery and storage to a third party?

This presentation offers real pricing numbers from large, globally focused content delivery networks as well as smaller regional service providers. Hear what the going rate is today for video delivery and learn what you should really be paying for these services.

Presenter Dan Rayburn, Executive Vice President, StreamingMedia.com

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Browse the archive of posts filed under Conferences, Technologies, Companies, Networking, Lectures, TCP/IP

A Search Engine Architecture Based on Collection Selection

scoundrel — Wed, 13 Feb 2008 19:49:56 GMT

Google Tech Talks
December, 19 2007

ABSTRACT

We present a distributed architecture for a Web search engine, based on the concept of collection selection. We introduce a novel approach to partition the collection of documents, able to greatly improve the effectiveness of standard collection selection techniques (CORI), and a new selection function outperforming the state of the art. Our technique is based on the novel query-vector (QV) document model, built from the analysis of query logs, and on our strategy of co-clustering queries and documents at the same time. By suitably partitioning the documents in the collection, our system is able to select the subset of servers containing the most relevant documents for each query. Instead of broadcasting the query to every server in the computing platform, only the most relevant will be polled, this way reducing the average computing cost to solve a query. We introduce a novel strategy to use the instant load at each server to drive the query routing. Also, we describe a new approach to caching, able to incrementally improve the quality of the stored
results. Our caching strategy is effectively both in reducing computing load and in improving result quality. The proposed architecture, overall, presents a trade-off between computing cost and result quality, and we show how to guarantee very precise results in face of a dramatic reduction to computing load. This means that, with the same computing infrastructure, our system can serve more users, more queries and more documents.

Speaker: Diego Puppin

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