Sponsorised links
June 2008
DeepLearningWorkshopNIPS2007 < Public < TWiki
by ogrisel
(via)
Theoretical results strongly suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need "deep architectures", which are composed of multiple levels of non-linear operations (such as in neural nets with many hidden layers). Searching the parameter space of deep architectures is a difficult optimization task, but learning algorithms (e.g. Deep Belief Networks) have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas.
This workshop is intended to bring together researchers interested in the question of deep learning in order to review the current algorithms' principles and successes, but also to identify the challenges, and to formulate promising directions of investigation. Besides the algorithms themselves, there are many fundamental questions that need to be addressed: What would be a good formalization of deep learning? What new ideas could be exploited to make further inroads to that difficult optimization problem? What makes a good high-level representation or abstraction? What type of problem is deep learning appropriate for?
The workshop presentation page show selected links to relevant papers (PDF) on the topic.
May 2008
CVXMOD – Convex optimization software in Python
by ogrisel
CVXMOD is a Python-based tool for expressing and solving convex optimization problems. It uses CVXOPT as its solver. It is developed by Jacob Mattingley, as PhD work under Stephen Boyd at Stanford University.
CVXMOD is primarily a modeling layer for CVXOPT. While it is possible to use CVXOPT directly, CVXMOD makes it faster and easier to build and solve problems. Advanced users who want to see or manipulate how their problems are being solved should consider using CVXOPT directly. Additional features are being added to CVXMOD beyond just modeling. These are currently experimental.
CVXMOD has a similar design philosophy to CVX, a convex optimization modeling language for Matlab®, and uses the principles of disciplined convex programming, as developed by Michael Grant, Stephen Boyd and Yinyu Ye.
Sponsorised links
April 2008
March 2008
SEO for your Wordpress Blog
by springnet
& 3 others
This plugin is streamlined for some best practices for Wordpress SEO. While it gives you many options the defaults reflect the settings I recommend using.
Linear Programming: Foundations and Extensions
by ogrisel
(via)
# Balanced treatment of the simplex method and interior-point methods.
# Efficient source code (in C) for all the algorithms presented in the text.
# Thorough discussion of several interior-point methods including primal-dual path-following, affine-scaling, and homogeneous self dual methods.
# Extensive coverage of applications including traditional topics such as network flows and game theory as well as less familiar ones such as structural optimization, L^1 regression, and the Markowitz portfolio optimization model.
# Over 200 class-tested exercises.
# A dynamically expanding collection of exercises.
February 2008
Simple SSE optimized sin, cos, log and exp
by ogrisel
I chose to write them in pure SSE1 MMX so that they run on the pentium III of your grand mother, and also on my brave athlon-xp, since thoses beast are not SSE2 aware. Intel AMath showed me that the performance gain for using SSE2 for that purpose was not large enough (10%) to consider providing an SSE2 version (but it can be done very quickly).
The functions use only the _mm_ intrinsics , there is no inline assembly in the code. Advantage: easier to debug, works out of the box on 64 bit setups, let the compiler choose what should be stored in a register, and what is stored in memory. Inconvenient: some versions of gcc 3.x are badly broken with certain intrinsic functions ( _mm_movehl_ps , _mm_cmpeq_ps etc). Mingw's gcc for example -- beware that the brokeness is dependent on the optimization level. A workaround is provided (inline asm replacement for the braindead intrinsics), it is not nice but robust, and broken compilers are detected by the validation program below.
January 2008
November 2007
SAP Memory analyzer
by Regis
SAP Memory Analyzer is a fast and feature-rich heap analyzer that helps you easily find big chunks of memory and identify who is keeping these objects alive.
The Memory Analyzer was developed to analyze productive heap dumps with hundreds of millions of objects. Once the heap dump is parsed, you can re-open it instantly, immediately get the retained size of single objects and quickly approximate the retained size of a set of objects. The Analyzer is (relatively) low on resource consumption, so you can analyze multi-GB heap dumps on 32 bit boxes.
October 2007
Web Page Analyzer - free website optimization tool website speed test check website performance report from web site optimization
by lukeslytalker
& 13 others
Try our free web site speed test to improve website performance. Enter a URL below to calculate page size, composition, and download time. The script calculates the size of individual elements and sums up each type of web page component.
