"This is the first internationally published paper (it was previously published in a Spanish conference of a series that deals with a system, intended for volunteer computing, that uses a pool for implementing distributed evolutionary algorithms. The basic idea is that the population resides in a pool (implemented using CouchDB), with clients pulling individuals from the pool, doing stuff on them, and putting them back in the pool. The algorithm uses, as much as possible, CouchDB features (such as revisions and views) to achieve good performance. All the code (for this and, right now, for the next papers) is available as open-source code."

"This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment measures, for agent-environment systems with stochastic transitions, how much influence an agent has on its environment, but only that influence that can be sensed by the agent sensors. It is an information-theoretic generalization of joint controllability (influence on environment) and observability (measurement by sensors) of the environment by the agent, both controllability and observability being usually defined in control theory as the dimensionality of the control/observation spaces.…"

"Data collection at a massive scale is becoming ubiquitous in a wide variety of settings, from vast offline databases to streaming real-time information. Learning algorithms deployed in such contexts must rely on single-pass inference, where the data history is never revisited. In streaming contexts, learning must also be temporally adaptive to remain up-to-date against unforeseen changes in the data generating mechanism. Although rapidly growing, the online Bayesian inference literature remains challenged by massive data and transient, evolving data streams. Non-parametric modelling techniques can prove particularly ill-suited, as the complexity of the model is allowed to increase with the sample size. In this work, we take steps to overcome these challenges by porting standard streaming techniques, like data discarding and downweighting, into a fully Bayesian framework via the use of informative priors and active learning heuristics. We showcase our methods by augmenting a modern non-parametric modelling framework, dynamic trees, and illustrate its performance on a number of practical examples. The end product is a powerful streaming regression and classification tool, whose performance compares favourably to the state-of-the-art."

XY is a family of array-oriented, concatenative programming languages with first-class continuations. XY 1 has quotations, lists, functions, and patterns. XY 2 is flat. XY 0 has quotations and shuffle-symbols but dispenses with lists and patterns.

"The design of genetic networks with specific functions is one of the major goals of synthetic biology. However, constructing biological devices that work "as required" remains challenging, while the cost of uncovering flawed designs experimentally is large. To address this issue, we propose a fully automated framework that allows the correctness of synthetic gene networks to be formally verified in silico from rich, high level functional specifications.
Given a device, we automatically construct a mathematical model from experimental data characterizing the parts it is composed of. The specific model structure guarantees that all experimental observations are captured and allows us to construct finite abstractions through polyhedral operations. The correctness of the model with respect to temporal logic specifications can then be verified automatically using methods inspired by model checking.
Overall, our procedure is conservative but it can filter through a large number of potential device designs and select few that satisfy the specification to be implemented and tested further experimentally. Illustrative examples of the application of our methods to the design of simple synthetic gene networks are included."

does what it says

"…There are situations where you might want to provide an implementation of a method dynamically.…"

"ParseKit is a Mac OS X Framework written by Todd Ditchendorf in Objective-C 2.0 and released under the MIT Open Source License. ParseKit is suitable for use on Mac OS X Leopard, Snow Leopard or iPhone OS. ParseKit is an Objective-C implementation of the tools described in "Building Parsers with Java" by Steven John Metsker. ParseKit includes additional features beyond the designs from the book and also some changes to match common Cocoa/Objective-C conventions. These changes are relatively superficial, however, and Metsker's book is the best documentation available for ParseKit."

"In a nutshell, give your grammar files a .ym extension instead of .y. Xcode will then run Bison with the necessary magic to support Objective-C."

"In the paper arguments are given why the concept of static evaluation has the potential to be a useful extension to Monte Carlo tree search. A new concept of modeling static evaluation through a dynamical system is introduced and strengths and weaknesses are discussed. The general suitability of this approach is demonstrated."

"We consider the problem of designing the the utility functions of the utility-maximizing agents in a multi-agent system so that they work synergistically to maximize a global utility. The particular problem domain we explore is the control of network routing by placing agents on all the routers in the network. Conventional approaches to this task have the agents all use the Ideal Shortest Path routing Algorithm (ISPA). We demonstrate that in many cases, due to the side-effects of one agent's actions on another agent's performance, having agents use ISPA's is suboptimal as far as global aggregate cost is concerned, even when they are only used to route infinitesimally small amounts of traffic. The utility functions of the individual agents are not "aligned" with the global utility, intuitively speaking. As a particular example of this we present an instance of Braess' paradox in which adding new links to a network whose agents all use the ISPA results in a decrease in overall throughput. We also demonstrate that load-balancing, in which the agents' decisions are collectively made to optimize the global cost incurred by all traffic currently being routed, is suboptimal as far as global cost averaged across time is concerned. This is also due to 'side-effects', in this case of current routing decision on future traffic. The mathematics of Collective Intelligence (COIN) is concerned precisely with the issue of avoiding such deleterious side-effects in multi-agent systems, both over time and space. We present key concepts from that mathematics and use them to derive an algorithm whose ideal version should have better performance than that of having all agents use the ISPA, even in the infinitesimal limit. We present experiments verifying this, and also showing that a machine-learning-based version of this COIN algorithm in which costs are only imprecisely estimated via empirical means (a version potentially applicable in the real world) also outperforms the ISPA, despite having access to less information than does the ISPA. In particular, this COIN algorithm almost always avoids Braess' paradox."

"Recent years are seeing an increasing need for on-line monitoring of teams of cooperating agents, e.g., for visualization, or performance tracking. However, in monitoring deployed teams, we often cannot rely on the agents to always communicate their state to the monitoring system. This paper presents a non-intrusive approach to monitoring by 'overhearing', where the monitored team's state is inferred (via plan-recognition) from team-members' routine communications, exchanged as part of their coordinated task execution, and observed (overheard) by the monitoring system. Key challenges in this approach include the demanding run-time requirements of monitoring, the scarceness of observations (increasing monitoring uncertainty), and the need to scale-up monitoring to address potentially large teams. To address these, we present a set of complementary novel techniques, exploiting knowledge of the social structures and procedures in the monitored team: (i) an efficient probabilistic plan-recognition algorithm, well-suited for processing communications as observations; (ii) an approach to exploiting knowledge of the team's social behavior to predict future observations during execution (reducing monitoring uncertainty); and (iii) monitoring algorithms that trade expressivity for scalability, representing only certain useful monitoring hypotheses, but allowing for any number of agents and their different activities to be represented in a single coherent entity. We present an empirical evaluation of these techniques, in combination and apart, in monitoring a deployed team of agents, running on machines physically distributed across the country, and engaged in complex, dynamic task execution. We also compare the performance of these techniques to human expert and novice monitors, and show that the techniques presented are capable of monitoring at human-expert levels, despite the difficulty of the task."

a charming little language for GP, introduced to me by Maarten Keijzer "… Various introductions to Joy / Papers on Joy / The C sources and the Joy libraries…"

"This article attempts to outline, in informal terms, a new theory of combinators, related to the theory of Combinatory Logic pioneered by Moses Schonfinkel, Haskell Curry, and others in the 1930s. Although not essential, an understanding of the classical theory of combinators may be helpful (see the links at the bottom of this article for some introductory material to combinators)."

“Nobody’s original,” Cope says. “We are what we eat, and in music, we are what we hear. What we do is look through history and listen to music. Everybody copies from everybody. The skill is in how large a fragment you choose to copy and how elegantly you can put them together.”

"Assume that we observe a large number of curves, all of them with identical, although unknown, shape, but with a different random shift. The objective is to estimate the individual time shifts and their distribution. Such an objective appears in several biological applications like neuroscience or ECG signal processing, in which the estimation of the distribution of the elapsed time between repetitive pulses with a possibly low signal-noise ratio, and without a knowledge of the pulse shape is of interest. We suggest an M-estimator leading to a three-stage algorithm: we split our data set in blocks, on which the estimation of the shifts is done by minimizing a cost criterion based on a functional of the periodogram; the estimated shifts are then plugged into a standard density estimator. We show that under mild regularity assumptions the density estimate converges weakly to the true shift distribution. The theory is applied both to simulations and to alignment of real ECG signals.…"

"OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision.

OpenCV is released under a BSD license, it is free for both academic and commercial use.
The library has >500 optimized algorithms (see figure below). It is used around the world, has >2M downloads and >40K people in the user group. Uses range from interactive art, to mine inspection, stitching maps on the web on through advanced robotics."

"For every list of integers x_1, ..., x_m there is some j such that x_1 + ... + x_j - x_{j+1} - ... - x_m \approx 0. So the list can be nearly balanced and for this we only need one alternation between addition and subtraction. But what if the x_i are k-dimensional integer vectors? Using results from topological degree theory we show that balancing is still possible, now with k alternations.
This result is useful in multi-objective optimization, as it allows a polynomial-time computable balance of two alternatives with conflicting costs. The application to two multi-objective optimization problems yields the following results:
- A randomized 1/2-approximation for multi-objective maximum asymmetric traveling salesman, which improves and simplifies the best known approximation for this problem.
- A deterministic 1/2-approximation for multi-objective maximum weighted satisfiability."

"It features generic data abstraction through Collections, a Visualization API allowing the creation of pluggable visualizations, and a Scene Graph implementation on top of HTML 5 Canvas. See the GitHub project, the documentation, and an example."

"We introduced an effective algorithm for k-nearest neighbor problem which works on multiple GPUs. By an experiment, we have shown that it runs more than 330 times faster than an implementation on a single core of an up-to-date CPU. We have also shown that the algorithm is effective from the viewpoint of parallelism of GPUs. That is because 1) there is no synchronization between GPUs until the very end of the process and 2) the workload is well balanced."

"Environment for DeveLoping KDD-Applications Supported by Index-Structures (ELKI) is a Knowledge Discovery in Databases (KDD, "data mining") software framework developed for use in research and teaching by the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany. It aims at allowing the development and evaluation of advanced data mining algorithms and their interaction with database index structures."

"The goal of this work is to provide an empirical basis for research on image segmentation and boundary detection. To this end, we have collected 12,000 hand-labeled segmentations of 1,000 Corel dataset images from 30 human subjects. Half of the segmentations were obtained from presenting the subject with a color image; the other half from presenting a grayscale image. The public benchmark based on this data consists of all of the grayscale and color segmentations for 300 images. The images are divided into a training set of 200 images, and a test set of 100 images."

I wonder to what extent this sort of thing might be useful in heuristics for Pareto-ranking

"… In this paper, we provide a formal introduction to riffled independence and present algorithms for using riffled independence within Fourier-theoretic frameworks which have been explored by a number of recent papers. Additionally, we propose an automated method for discovering sets of items which are riffle independent from a training set of rankings. We show that our clustering-like algorithms can be used to discover meaningful latent coalitions from real preference ranking datasets and to learn the structure of hierarchically decomposable models based on riffled independence."

"This introduction is based on my experiences with using Protovis in my Visualization and Visual Communication class earlier this spring. While the concepts involved are really not that difficult, they are rather foreign to students who have not been exposed to functional programming. And since that is also the case for a lot of hobbyists and people wanting to do visualization who do not have a computer science background, I imagine they run into the same problems."

"Object orientation provides a flexible framework for the implementation of the convolution of arbitrary distributions of real-valued random variables.
We discuss an algorithm which is based on the Discrete Fourier Transformation and its fast computability via the Fast Fourier Transformation. It directly applies to lattice-supported distributions. In the case of continuous distributions an additional discretization to a linear lattice is necessary and the resulting lattice-supported distributions are suitably smoothed after convolution."

"The most recent version of Protovis, the open-source visualization library that uses JavaScript and SVG, was just released not too long ago - this time with more layout and examples. This is especially helpful since Protovis was "designed to be learned by example." Among the new stuff is the ever popular streamgraphs, along with the force-directed layout. With only 10 to 20 lines of code, you'll have your viz, so lots of bang for the buck."

"Everything we create should aspire to this, should leave us – as programmers – wondering if that’s all and if we shouldn’t perhaps add a bit more. Scott Berkun (a genius and a craftsman) said all of this more than ten years ago and I’ve known about it for at least half that time, but it hasn’t really changed the way I write software because it’s too hard to just know when something’s simple enough."

"Since multivariate Boltzmann samplers can be obtained in any situation where the distribution is well-concentrated, one may envision extensions to other classes, including constrained trees, permu- tations with a fixed number of cycles, functional graphs with a controlled number of components.…"

"We've all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O'Reilly said that "data is the next Intel Inside." But what does that statement mean? Why do we suddenly care about statistics and about data?

In this post, I examine the many sides of data science -- the technologies, the companies and the unique skill sets."

"Central Force Optimization is a global search and optimization algorithm that searches a decision space be flying "probes" whose trajectories are deterministically computed using two equations of motion. Because it is possible for a probe to fly outside the domain of feasible solutions, a simple errant probe retrieval method has been used previously that does not include the directional information contained in a probe's acceleration vector. This note investigates the effect of adding directionality to the "repositioning factor" approach. As a general proposition, it appears that doing so does not improve convergence speed or accuracy. In fact, adding directionality to the original errant probe retrieval scheme appears to be highly inadvisable. Nevertheless, there may be alternative probe retrieval schemes that do benefit from directional information, and the results reported here may assist in or encourage their development."

"Complexity of global optimization algorithms makes implementation of the algorithms difficult and leads the algorithms to require more computer resources for the optimization process. The ability to explore the whole solution space without increasing the complexity of algorithms has a great importance to not only get reliable results but so also make the implementation of these algorithms more convenient for higher dimensional and complex-real world problems in science and engineering. In this paper, we present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique that is designed into a group architecture similar to the architecture of Cooperative Coevolutionary Algorithms.…"

"The Prediction API allows you to get more from your data and makes its patterns more accessible. Specifically, the Prediction API leverages Google's machine learning infrastructure to give you the tools to better analyze your data and reveal patterns that are often difficult to manually discover. The API also enables you to use those patterns to predict new outcomes, which facilitates the development of all types of software, from textual analysis systems to recommendation systems. Because the Prediction API is a RESTful HTTP service, you can easily access it from Google App Engine, Apps Script, and other Internet-connected desktop applications."

"The performance assessment of algorithms for multiobjective optimization problems is far from being a trivial issue. Recent results indicate that unary performance measures, i.e. performance measures which assign a single value to each non-dominated point set, are inherently limited in their inferential power. Despite these limitations, the hypervolume indicator (also known as Lebesgue measure or S metric) is still considered to possess some reasonable properties, having also been proposed as a guidance criterion for accepting solutions in Multiobjective Evolutionary Algorithms. Therefore, the computational time taken for computing the hypervolume indicator is a crucial factor for the performance of such algorithms.…"

"An easy game: Only paper and pencil needed. A game for one player.
And an open game: Will you improve one of the current world records???"

"Hardware has become irrelevant. It’s here because we need it, but we don’t learn anything from it, and thus the UI is everything."

"CouchDB provides a bulk insert/update feature. To use this, you make a POST request to the URI /{dbname}/_bulk_docs, with the request body being a JSON document containing a list of new documents to be inserted or updated."

"In the spirit of sparse representation, we chose to use a syntax tree as the internal data structure for our symbolic calculator. A syntax tree is a kind of tree, which in turn is a kind of linked data structure. Briefly, a linked data structure is an object which contains references, or links, to other like objects. A simple example is a linked list, where each element contains the data for it list entry and a link to the next list element. A tree is a linked structure that starts with a single "root" node. One or more "child" nodes are referenced from the root node, and each of these child nodes may in turn have children of their own. This linking pattern produces a branching data structure, as seen in the following diagram; hence the name "tree"."

"The YouTube Nonprofit Program provides for extra benefits like branding capabilities, increased uploading capacity, and call-to-action overlays. Non-profits can use the call-to-action feature to drive sign-ups, donations, website traffic, and any other response in which users take action. This feature was effectively used by the World Food Programme to raise $36,000 on World Food Day with this video.…"

"The study of high-dimensional differential equations is challenging and difficult due to the analytical and computational intractability. Here, we significantly improve the speed of waveform relaxation (WR), a method to simulate high-dimensional differential-algebraic equations. This new method termed adaptive waveform relaxation (AWR) is tested on a communication network example. Further we analyze different heuristics for computing graph partitions tailored to adaptive waveform relaxation."

"The requirements for building R vary, depending whether the build machine is an Intel-based or PowerPC-based Mac and whether universal build is desired. The following description shows the minimum requirements for building R.…"

"The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-sets are needed to properly train these algorithms. The challenge is available at www.hep.anl.gov/SNchallenge, and the due date for classifications is May 1, 2010."

"…We can also consider what happens when instead of only considering a single type of shuffling we consider combining the j! different shuffling rules that come from all the possible rearrangements of the ordering of the labels. And of course, perhaps the most important thing missing right now is a good magic trick that can be performed using this shuffling rule, which was the original motivation of Larry Carter and J.-C. Reyes who first suggested this problem!"

"Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This paper will provide an overview of underlying concepts, along with algorithms commonly used for image enhancement. The paper focuses on spatial domain techniques for image enhancement, with particular reference to point processing methods and histogram processing."

"Beginning with a historical account of the spectral classification, its refinement through additional criteria is presented. The line strengths and ratios used in two dimensional classifications of each spectral class are described. A parallel classification scheme for metal-poor stars and the standards used for classification are presented. The extension of spectral classification beyond M to L and T and spectroscopic classification criteria relevant to these classes are described. Contemporary methods of classifications based upon different automated approaches are introduced."

"We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural network is trained on a subset of objects classified by the human eye and we test whether the machine learning algorithm can reproduce the human classifications for the rest of the sample. We find that the success of the neural network in matching the human classifications depends crucially on the set of input parameters chosen for the machine-learning algorithm. The colours and parameters associated with profile-fitting are reasonable in separating the objects into three classes. However, these results are considerably improved when adding adaptive shape parameters as well as concentration and texture. …"

via: Genetic Argonaut

"This paper briefly highlights the features of the software tool [RadPat4W], named after Radiation Patterns for Windows but also compatible with the [Wine] environment of Linux. The tool is a stand-alone part of a freeware suite that is based on an alternative exposition of fundamental Antenna Theory and is under active development for many years now. Nevertheless, [RadPat4W] source code has been now released as FLOSS Free Libre Open Source Software and thus it may be freely used, copied, modified or redistributed, individually or cooperatively, by the interested user to suit her/his personal needs for reliable antenna applications from the simplest to the more complex."

"In this Challenge, participants are asked to reconstruct, using any combination of available prior and concurrent information, segments of signals that have been removed from multiparameter recordings of patients in intensive care units (ICUs)."

"NArray is an Numerical N-dimensional Array class. Supported element types are 1/2/4-byte Integer, single/double-precision Real/Complex, and Ruby Object. This extension library incorporates fast calculation and easy manipulation of large numerical arrays into the Ruby language. NArray has features similar to NumPy, but NArray has vector and matrix subclasses."

"We consider the computation of the volume of the union of high-dimensional geometric objects. While showing that this problem is #P-hard already for very simple bodies (i.e., axis-parallel boxes), we give a fast FPRAS for all objects where one can: (1) test whether a given point lies inside the object, (2) sample a point uniformly, (3) calculate the volume of the object in polynomial time. All three oracles can be weak, that is, just approximate. This implies that Klee's measure problem and the hypervolume indicator can be approximated efficiently even though they are #P-hard and hence cannot be solved exactly in time polynomial in the number of dimensions unless P=NP. Our algorithm also allows to approximate efficiently the volume of the union of convex bodies given by weak membership oracles. "

"lazy.rb provides lazy evaluation and futures in Ruby.

For lazy evaluation, the facilities are similar to those provided by R5 Scheme. There are two functions: Kernel.promise (similar to Scheme’s delay) which takes a block for later evaluation, and Kernel.demand (similar to Scheme’s force), which forces its evaluation (if necessary) and returns its cached result."

"Hook into the rendering pipeline to create special effect. Use low level rendering commands to achieve exactly what you want."

"Google SketchUp is software that you can use to create 3D models of anything you like. With its embedded Ruby application programming interface (API), you can extend and customize the program to suit your needs. If you love SketchUp but ever thought "I just wish it did XYZ," then there's a good chance the Ruby API can make it happen. "

"cocoaNEC 2.0 is a Mac OS X application intended primarily for the design and modeling of antennas.

cocoaNEC 2.0 is a Universal Binary Cocoa based application. It runs natively on both Intel based and PowerPC based Macintosh computers that use Mac OS X 10.4 (Tiger) or newer.

The application is free and it can be downloaded from the Download tab button at the top of this page.

Online tutorials, reference manuals and example files for the application are available through the User's Manual tab button. The What's New page lists features that have changed since the previously released version of cocoaNEC 2.0. "

awesome

"The purpose of this site is to provide a comprehensive list of links related to optics and optical simulation in general. Topics include optical design, optical engineering, illumination, Laser, optical materials, thin film coatings, and many more subjects needed to build and analyze complex optical systems."

"BiotSavart is an application for Mac OS X and Windows XP that calculates the magnetic field resulting from general 3-D configurations of current-carrying conductors. It has proven useful in the design of superconducting and copper coil systems in physics laboratories worldwide. With BiotSavart, you design the conductors while you view them on the screen."

"NArray is an Numerical N-dimensional Array class. Supported element types are 1/2/4-byte Integer, single/double-precision Real/Complex, and Ruby Object. This extension library incorporates fast calculation and easy manipulation of large numerical arrays into the Ruby language. NArray has features similar to NumPy, but NArray has vector and matrix subclasses."

"To investigate the optimal shape a 3-D panel might take in order to harvest the most light, scientists used a "genetic algorithm" to evolve solar panels in a computer simulation.

The model they developed randomly generated jumbles of flat, triangular double-sided solar panels and analyzed which generated the most power as a virtual sun moved across the sky. The best ones were then "mated" together for "offspring" that combined features of each with "mutations" that varied their structures. This process was then repeated for up to millions of generations, all in order to see what might evolve."

"Every human likes choices. But today's fast route planning algorithms usually compute just a single route between source and target. There are beginnings to compute alternative routes, but this topic has not been studied thoroughly. Often, the aspect of meaningful alternative routes is neglected from a human point of view. We fill in this gap by suggesting mathematical definitions for such routes. As a second contribution we propose heuristics to compute them, as this is NP-hard in general."

"Based on key investment criteria including valuation and management quality, we listed a few companies in the Capital Goods sector that appear to be attractive as well as a few that do not."

Want to breed replacements for the models in Section 4

"This looks a whole lot like the initializer block in Rails 2.3, but the Application object, not a global configuration object, now has the configuration information. Similarly, routes.rb now begins YourApp::Application.routes.draw. The application object lives in the center of Railties in Rails 3, providing a core object that the rest of the frameworks can build on."

"Suppose you are given a simple closed curve in the plane. (“Simple” means the curve does not intersect itself, “closed” means the curve ends at the same point where it begins.) Can you always find four points on the curve which form the vertices of a square?"

"The mean spectra were provided as input sequences to the Implicit Context Representation Cartesian Genetic Programming algorithm (IRCGP)[14,15]. IRCGP uses evolutionary computing methodology to learn classifiers that are capable of distinguishing between data classes. Induced classifiers take the form of programmatic expressions applied to particular offsets within the input data sequences. These expressions are composed from a set of simple mathematical functions. Both the choice and connectivity of the functions, and the choice of offsets used within the input sequences, are determined by the algorithm's evolutionary process. The input sequences were divided equally into training and test sets. To prevent over-learning, training of the classifiers was stopped once classification accuracy of the test sequences started to fall."

things to do

"The i7 even represents a sizable (35%) performance increase over the i5 model and costs only $200 more. In fact, the i7 iMac benchmarks compare favorably to 2.93Ghz Quad-Core Mac Pro which costs significantly more."

"Norgate Investor Services provides quality end-of-day data for stock markets in Australia (ASX), Asia (SGX) and USA (NASDAQ, NYSE, NYSE Amex, NYSE Arca, OTC-BB, PinkSheets). Extensive historical data is available. Hourly snapshot data is available for the ASX and SGX. Data is provided in a "MetaStock™ compatible" data format.

Stock data is organised into security types (equities, indices, warrants, options) and can be organised into custom folders which allow you to segregate such as index participation, sector, industry group, dividend-paying-shares. World Indices are provided free with any subscription."

[R tools for financial time-series analysis, among other things]

"Causal state reconstruction has an important advan- tage over VLMM methods. Each state in a VLMM is represented by a single suffix, and consists of all and only the histories ending in that suffix. For many pro- cesses, the causal states contain multiple suffixes. In these cases, multiple “contexts” are needed to repre- sent a single causal state, so VLMMs are generally more complicated than the HMMs we build. The causal state model is the same as the minimal VLMM if and only if every causal state contains a single suffix. This is the case for the process in Fig. 3, where CSSR and VLMM methods will give the same results."

"Zimpl is a little language to translate the mathematical model of a problem into a linear or (mixed-) integer mathematical program expressed in .lp or .mps file format which can be read and (hopefully) solved by a LP or MIP solver."

"Consider the following optimization problem: we are given n jobs, a time horizon T, and one machine M with processing capacity Cap >= 2. Each job has a processing time (pj), release date (rj), due date (dj), machine utilization (cj), and weight (wj). We would like to schedule all the jobs on machine M while making sure that: (i) all jobs obey their execution window [rj,dj] (to a certain extent; see possible objectives), and (ii) we respect the machine capacity at all times (i.e., given a time 0 <= t <= T, the sum of cj over all jobs running at time t is always less than or equal to Cap). Possible objective functions are: minimize makespan, minimize total (weighted) tardiness, minimize total number of late jobs, minimize total (weighted) delay, etc."

"There is no required textbook for this class; I will post electronic copies of relevant papers to this web site as the course progresses. Meanwhile, here is a list of background references, primarily surveys and textbooks. Key references for the course are hilighted. Many of the other references focus on material that we will not cover at all in the course; I include them primarily to give some sense of the diversity of the field."

"This specification defines an API that allows Web application authors to spawn background workers running scripts in parallel to their main page. This allows for thread-like operation with message-passing as the coordination mechanism."

"It's been too long since I've sat down to benchmark CouchDB. I'm working on the High Performance CouchDB chapter in the book, so I needed some numbers."

"PMML uses XML to represent mining models. The structure of the models is described by an XML Schema. One or more mining models can be contained in a PMML document. A PMML document is an XML document with a root element of type PMML. The general structure of a PMML document is:..."