Google Tech-Talk Computer Science Video Lectures
Hey everyone! This time I am posting google tech-talk computer science
video lectures which I found interesting.
There are many, many more google tech-talk video lectures available
here:
Google Tech-Talk Lectures
2,3,5, Infinity!
* Video Lecture by Paul Hildebrandt
ABSTRACT: Nearly 60 years after the first electronic digital computer
was designed at the Princeton Institute for Advanced Studies (IAS),
companies like Google are demonstrating the power of a world built
from 1s and 0s. Zome is a system that models the world built from the
numbers 2, 3 and 5. We will explore how these numbers are knotted
together to form the structure of space, from the subatomic framework
of the atom, to the geometry of life, to a recently proposed "shape"
of the universe!
Creative Commons for Googlers
* Video Lecture by Mike Linksvayer
ABSTRACT: Creative Commons provides tools that enable the legal
sharing and re-use of creative and educational materials online. Come
learn about Creative Commons, what they're doing, and how Google might
help. Creative Commons' general counsel will be on hand to answer
questions about CC copyright licenses and other legal issues, but the
presentation will focus on technical projects at Creative Commons:
license-aware web search, microformats, reliable metadata-embedding in
various media types, and licensing integration with user generated
content platforms.
iClaustron: Open Source Grid Cluster Storage Controller
* Video Lecture by Mikael Ronstrom
ABSTRACT: Many applications has requirements to store petabytes of
base data and many terabytes of structured data. Examples of this are
genealogy, astronomy, biotech and so forth. This talk will discuss
requirements from the genealogy application and show how this
requirements requires building very large clustered systems with an
hierarchy of clusters. These clusters are used to both store base data
and structured data. He goes on to show how these requirements
translate into a systems architecture with essential components of
off-the shelf servers, cheap storage, clustered software and
integrated cluster interconnects.
The Technology Behind Debian's Testing Release
* Video Lecture by Anthony Towns
ABSTRACT Current Debian Project Leader, former Release Manager and all
round good guy, Anthony "aj" Towns will give an in depth look at the
ideas and code that hold Debian's "testing" suite together, from its
initial genesis, through basic prototypes, to the "final"
implementation and the couple of rewrites it's had since. The numerous
optimisations used to make the ideas actually operate in an even
vaguely acceptable amount of time would be examined; and the various
tricks and tools used in development and debugging will be examined
(including malloc debugging, writing C extensions to perl and python,
and libapt versus libdpkg).
Better, faster, smarter: Python yesterday, today ... and tomorrow
* Video Lecture by Alex Martelli
A lecture on Python programming language. Emphasis on Python
implementation 2.5 but also a historical review of 2.2, 2.3, 2.4.
Security is Broken
* Video Lecture by Rik Farrow
ABSTRACT: Our computer security model is broken. Worse yet, it never
really has worked at all well, and is even less suitable for today's
uses. In this talk, I explore the history behind the design of the
current security both in hardware and operating systems. Instead of
evolving a more secure model over time, system designers have actually
managed to make things worse, creating insecurity in depth. Most of
today's systems are single user machines: certainly desktops and
laptops, but also most servers. The current security model was not
designed to protect users from themselves, and this goes a long way
towards understanding why security is so difficult. I end by looking
at strategies for improving security -- but no real solutions. The
point is to start thinking outside of the box, while adopting best
practices today. What we have done in the past has not worked, and can
not work. We need to look at the security model in a new way, and that
is the real point of this presentation.
High Radix Interconnection Networks
* Video Lecture by William J. Dally
ABSTRACT: High-radix interconnection networks offer significantly
better cost/performance and lower latency than conventional
(low-radix) topologies. Increasing radix is motivated by the
exponential increase in router pin bandwidth over time. Increasing the
radix or degree of a router node is a more efficient way to exploit
this increasing bandwidth than making channels wider. A high-radix
poses several challenges in router design because the internal
structures of conventional routers (e.g., the allocators) scale
quadratically with radix. A hierarchical switch organization with
internal buffering yields a scalable design with near-optimal
performance. A high-radix "flattened butterfly" topology, enabled by
recent developments in global adaptive routing, offers twice the
performance as a comparable-cost Clos network on balanced traffic.
Many of these developments have been incorporated in the YARC router
and interconnection network for the Cray Black Widow Supercomputer.
Data Representation/Laplace Operator
* Video Lecture by David Vladimirovich Ingerman
ABSTRACT: Data Representation by Graphs, Matrices, Formulas, and
continued Fractions and Inverse Problems for Laplace Operator.
Using Statistics to Search and Annotate Pictures
* Video Lecture by Nuno Vasconcelos
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.
Badvertisements: Stealthy Click Fraud with Unwitting Accessories
* Video Lecture by Dr. Markus Jakobsson
ABSTRACT: We describe a new type of threat to the Internet
infrastructure, in the shape of a highly efficient but very well
camouflaged click-fraud attack on the advertising infrastructure, not
using any type of malware. The attack, which we refer to as a
"badvertisement", is described and experimentally verified on several
prominent advertisement schemes. This stealthy attack can be thought
of as a threatening mutation of spam and phishing attacks, with which
it has many commonalities, except for the fact that it is not the
targeted individual who is the victim in the attack, but the
advertiser.
Decision Making and Chance
* Video Lecture by Dr. Mike Orkin
ABSTRACT: Certain gambling games, such as roulette and craps, are
games of pure chance: In repeated play, luck disappears, and the
persistent gambler will go broke. Other gambling activities, such as
betting on sports or the stock market, may involve an element of
skill. One way to measure this is to compare the results of a gambling
strategy with chance: A skillful strategy should produce long-run
results that are better than would be achieved by someone who is just
guessing. One can also compare a gambler's losses with chance to see
if the gambler is doing worse than chance would allow. I will discuss
two recent projects that illustrate these concepts:
* Automated data mining software discovers that the Baltimore Ravens
are 17-3 versus the point spread when they lost their previous
game and their opponents played their previous game on the road.
Do situations like this give clever gamblers an edge or are such
strong win-loss records merely random flukes?
* A gambler loses $30 million betting at an online casino. Is it
possible to lose this much just by chance or is the gambler being
cheated? Or maybe the gambler is part of a money laundering
scheme.
The Electric Sheep and their Dreams in High Fidelity
* Video Lecture by Scott Draves a.k.a. Spot
ABSTRACT:
Electric Sheep is a distributed screen-saver that harnesses idle
computers into a render farm with the purpose of animating and
evolving artificial life-forms known as sheep. The votes of the users
form the basis for the fitness function for a genetic algorithm on a
space of abstract animations. Users also may design sheep by hand for
inclusion in the gene pool.
This cyborg mind composed of 35,000 computers and people was used to
make Dreams in High Fidelity: a painting that evolves. It consists of
55GB of high definition sheep that would have taken one computer over
100 years to render, played back to form a nonrepeating continuously
morphing image.
The talk will cover the genetic code and renderer, the genetic
algorithm, how error correction is built into the distributed renderer
while minimizing performance penalty, and how to distribute 750GB of
video per day without paying for it. The talk will include a demo of
the artwork.
ReUsable Web Components with Python and Future Python Web Development
* Video Lecture by Ben Bangert
ABSTRACT: Python's Web Server Gateway Interface (WSGI) not only
enables a multitude of Python web frameworks to share code when it
comes to deployment, but also enables entirely new levels of re-use
for Python web development. This talk is focused on explaining WSGI,
new types of re-use with WSGI middleware, and explore new frameworks
that heavily utilize WSGI; in this case, Pylons. Moving beyond
monolithic frameworks that try to do everything themselves, to new
modes of development where you can use just the parts you want and
still have active development communities to interact with.
Nanowires and Nanocrystals for Nanotechnology
(not computer science but too interesting to miss)
* Video Lecture by Yi Cui
ABSTRACT: Nanowires and nanocrystals represent important nanomaterials
with one-dimensional and zero-dimensional morphology, respectively.
Here I will give an overview on the research about how these
nanomaterials impact the critical applications in faster transistors,
smaller nonvolatile memory devices, efficient solar energy conversion,
high-energy battery and nanobiotechnology.
Measuring Programmer Productivity
* Video Lecture by Vikram Aggarwal Viral Shah
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.
Sparse and large-scale learning with heterogeneous data
* Video Lecture by Gert Lanckriet
ABSTRACT: An important challenge for the field of machine learning is
to deal with the increasing amount of data that is available for
learning and to leverage the (also increasing) diversity of
information sources, describing these data. Beyond classical vectorial
data formats, data in the format of graphs, trees, strings and beyond
have become widely available for data mining, e.g., the linked
structure of the world wide web, text, images and sounds on web pages,
protein interaction networks, phylogenetic trees, etc. Moreover, for
interpretability and economical reasons, decision rules that rely on a
small subset of the information sources and/or a small subset of the
features describing the data are highly desired: sparse learning
algorithms are a must. This talk will outline two recent approaches
that address sparse, large-scale learning with heterogeneous data, and
show some applications.
Code Generation With Ruby
* Video Lecture by Jack Herrington
Talk about code generation techniques using Ruby. He will cover both
do-it-yourself and off-the-shelf solutions in a conversation about
where Ruby is as a tool, and where it's going.
Random Sampling from a Search Engine's Index
* Video Lecture by Ziv Bar-Yossef
ABSTRACT: We revisit a problem introduced by Bharat and Broder almost
a decade ago: how to sample random pages from a search engine's index
using only the search engine's public interface?
In this paper we introduce two novel sampling techniques: a
lexicon-based technique and a random walk technique. Our methods
produce biased sample documents, but each sample is accompanied by a
corresponding "weight", which represents the probability of this
document to be selected in the sample. The samples, in conjunction
with the weights, are then used to simulate near-uniform samples. To
this end, we resort to three well known Monte Carlo simulation
methods: rejection sampling, importance sampling and the
Metropolis-Hastings algorithm.
We analyze our methods rigorously and prove that under plausible
assumptions, our techniques are guaranteed to produce near-uniform
samples from the search engine's index. Experiments on a corpus of 2.4
million documents substantiate our analytical findings and show that
our algorithms do not have significant bias towards long or highly
ranked documents.
A New Way to look at Networking
* Video Lecture by Van Jacobson
ABSTRACT: Today's research community congratulates itself for the
success of the internet and passionately argues whether circuits or
datagrams are the One True Way. Meanwhile the list of unsolved
problems grows.
Security, mobility, ubiquitous computing, wireless, autonomous
sensors, content distribution, digital divide, third world
infrastructure, etc., are all poorly served by what's available from
either the research community or the marketplace. I'll use various
strained analogies and contrived examples to argue that network
research is moribund because the only thing it knows how to do is fill
in the details of a conversation between two applications. Today as in
the 60s problems go unsolved due to our tunnel vision and not because
of their intrinsic difficulty. And now, like then, simply changing our
point of view may make many hard things easy.
Privacy Preserving DataMining
* Video Lecture by Matthew Roughan
ABSTRACT: The rapid growth of the Internet over the last decade has
been startling. However, efforts to track its growth have often fallen
afoul of bad data --- for instance, how much traffic does the Internet
now carry? The problem is not that the data is technically hard to
obtain, or that it does not exist, but rather that the data is not
shared. Obtaining an overall picture requires data from multiple
sources, few of whom are open to sharing such data, either because it
violates privacy legislation, or exposes business secrets. The
approaches used so far in the Internet, e.g., trusted third parties,
or data anonymization, have been only partially successful, and are
not widely adopted.
The paper presents a method for performing computations on shared data
without any participants revealing their secret data. For example, one
can compute the sum of traffic over a set of service providers without
any service provider learning the traffic of another. The method is
simple, scalable, and flexible enough to perform a wide range of
valuable operations on Internet data.
Near-optimal Monitoring of Online Data Sources
* Video Lecture by Ryan Peterson
ABSTRACT Crawling the Web for interesting and relevant changes has
become increasingly difficult due to the abundance of frequently
changing information. Common techniques for solving such problems make
use of heuristics, which do not provide performance guarantees and
tend to be tailored to specific scenarios or benchmarks.
In this talk, I will present a principled approach based on
mathematical optimization for monitoring high-volume online data
sources. We have built and deployed a distributed system called Corona
that enables clients to subscribe to Web pages and notifies clients of
updates asynchronously via instant messages. Corona assigns multiple
nodes to cooperatively monitor each Web page and employs a novel
decentralized optimization technique for distributing the monitoring
load. In its currently running form, the optimization algorithm
guarantees the best update detection time on average without exceeding
resource constraints on the monitoring servers. Based on simulations
and measurements on our deployed system, I will show that Corona
performs substantially better than commonly used heuristics.
Related Posts
* Free Computer Science Video Lecture Courses
(Courses include web application development, lisp/scheme
programming, data structures, algorithms, machine structures,
programming languages, principles of software engineering, object
oriented programming in java, systems, computer system
engineering, computer architecture, operating systems, database
management systems, performance analysis, cryptography, artificial
intelligence)
* More Mathematics and Theoretical Computer Science Video Lectures
(Includes algebra, elementary statistics, applied probability,
finite mathematics, trigonometry with calculus, mathematical
computation, pre-calculus, analytic geometry, first year calculus,
business calculus, mathematical writing (by Knuth), computer
science problem seminar (by Knuth), dynamic systems and chaos,
No comments:
Post a Comment