"Crowd algorithms often assume workers are inexperienced and thus fail to adapt as workers in the crowd learn a task. These assumptions fundamentally limit the types of tasks that systems based on such algorithms can handle. This paper explores how the crowd learns and remembers over time in the context of human computation, and how more realistic assumptions of worker experience may be used when designing new systems. We first demonstrate that the crowd can recall information over time and discuss possible implications of crowd memory in the design of crowd algorithms. We then explore crowd learning during a continuous control task. Recent systems are able to disguise dynamic groups of workers as crowd agents to support continuous tasks, but have not yet considered how such agents are able to learn over time. We show, using a real-time gaming setting, that crowd agents can learn over time, and `remember' by passing strategies from one generation of workers to the next, despite high turnover rates in the workers comprising them. We conclude with a discussion of future research directions for crowd memory and learning."

"In this work we develop an algorithm for signal reconstruction from the magnitude of its Fourier transform in a situation where some (non-zero) parts of the sought signal are known. Although our method does not assume that the known part comprises the boundary of the sought signal, this is often the case in microscopy: a specimen is placed inside a known mask, which can be thought of as a known light source that surrounds the unknown signal. Therefore, in the past, several algorithms were suggested that solve the phase retrieval problem assuming known boundary values. Unlike our method, these methods do rely on the fact that the known part is on the boundary. Besides the reconstruction method we give an explanation of the phenomena observed in previous work: the reconstruction is much faster when there is more energy concentrated in the known part. Quite surprisingly, this can be explained using our previous results on phase retrieval with approximately known Fourier phase."

"This paper discusses a system that accelerates reinforcement learning by using transfer from related tasks. Without such transfer, even if two tasks are very similar at some abstract level, an extensive re-learning effort is required. The system achieves much of its power by transferring parts of previously learned solutions rather than a single complete solution. The system exploits strong features in the multi-dimensional function produced by reinforcement learning in solving a particular task. These features are stable and easy to recognize early in the learning process. They generate a partitioning of the state space and thus the function. The partition is represented as a graph. This is used to index and compose functions stored in a case base to form a close approximation to the solution of the new task. Experiments demonstrate that function composition often produces more than an order of magnitude increase in learning rate compared to a basic reinforcement learning algorithm."

Routine Matters: New Foundations for the Study of Recurring Organizational Action Patterns

"…Keep the faculty of effort alive in you by a little gratuitous exercise every day. That is, be systematically heroic in little unnecessary points, do every day or two something for no other reason than its difficulty, so that, when the hour of dire need draws nigh, it may find you not unnerved and untrained to stand the test."

"This is a guide to the R programming language."

"The Big Shift suggests we are moving away from a world where stocks of knowledge and short-lived transactions are the key to success. In its place, we find a world where participation in many, diverse flows of knowledge and long-term, trust-based relationships determine success. In this new world, shy people can be at a significant disadvantage. We run the risk of becoming increasingly stressed and marginalized by the extroverts who welcome the opportunity to broaden and deepen relationships. They thrive in crowded rooms while we are deeply uncomfortable with exposing and sharing."

"Brilliant … but what made Dr. K’s technique most insidiously evil and genius was, during the most technically difficult lecture of the entire quarter, there was no lie. At the end of the lecture in which he was not called on any lie, he offered the same challenge to work through the notes; on the following Monday, he fielded our theories for what the falsehood might be (and shooting them down “no, in fact that is true – look at “) for almost ten minutes before he finally revealed: “Do you remember the first lecture – how I said that ‘every lecture has a lie?’”"

"How fast is this going to happen? Well, Khan is already becoming famous. Last year CNN gave him airtime to explain the financial crisis. Why him, and not an economics Ph.D. type, you ask? Because he is understandable, and because some genius at CNN figured out that at least some of their viewers were able and willing to learn a little bit in order to understand what is going on."

"An appendix sketches connections between these results and the replicator dynamics of evolutionary theory."

"Yet, the co-training algorithm in this paper also makes the same assumptions (as it too has underlying naive Bayes clas- sifiers), but does not suffer from the violations. Thus we hypothesize that the co-training algorithm succeeds in part because it is more robust to the assumptions made by its underlying classifiers. This can be understood by looking at the differences in how EM and co-training use the underly- ing assumptions."

In case you, reader, cannot see where she is pointing into the corner at her genius: she is pointing at her context, her network, her friends and learning and colleagues and enemies, what she has read and who she has spoken to, what she has done and never noticed, and what she has heard and never noticed and who she has met and never noticed. You are the genius of others.

"One would be hard-pressed to disapprove of autodidacticism. Consider a list of notable alumni from the academy of the self-taught: René Descartes, Benjamin Franklin, Abraham Lincoln, William Blake. Michael Faraday apprenticed himself to a bookseller and read everything he could before going on to figure out electromagnetism. August Wilson schooled himself at the Carnegie Library in Pittsburgh after dropping out of the ninth grade. Arnold Schoenberg claimed to be an autodidact, and who are we to dispute it? Frank Zappa advised, “Forget about the senior prom and go to the library and educate yourself, if you’ve got any guts.” Hear, hear. (Though if the prom band is playing Frank Zappa songs, we’re donning a powder-blue brocade tux and we’re going.)"

"This series of games has a consistent size and format, and any four will fit neatly into The Games Collection Stand (Pin's part number 02705)."

"And I worry that the idea that learning in relation to history can easily be kept within some type of bounds implies, to a degree, that the importance of history is its factual content. Generations of captive history students, face-down and drooling on their desks, indicate that approaches of this nature are not only unfortunately limited, but also a fatal blow to any intrinsic interest in examining historical/cultural change."

"Why should a young aspiring software professional spend four years and $200K+ to attend an institution that will teach them less about their chosen profession than 3 months of working on a real project with talented mentors? Indeed, why should employers pay $50K for undertrained programmers who are sure to make horrific messes for the next three years of their career?

Consider instead a team of craftspeople. At the center of this team is a master programmer. This is someone who has been programming for two decades or more. This person understand systems at a gut level, and can quickly make technical judgements without agonizing over them. Such a person can direct a team with the kind of calm confidence that only comes with years of experience and seasoning."

If you want to buy me a present, buy me this. The whole set.

"I am mainly interested in how scientific method could possibly lead us to true generalizations about Nature; generalizations that extend infinitely beyond our current, finite perspective. Standard philosophy of science sidesteps this question by asking, instead, about the meanings of "justification" and "rationality" a different matter entirely. I put the former question front and center, so that methodological normativity must be traced back to truth-finding efficacy, rather than to sociological generalizations about scientific practice. In this respect, my approach to epistemology closely parallels work in theoretical computer science and the foundations of mathematics, in which the central question is existence of a reliable procedure for finding the right answer to a question. The shift in emphasis results in a fresh, new perspective on a number of standard issues in epistemology and the philosophy of science, such as:..."

"Grad school was even worse. At that level, a self-selected bunch of failure avoiders competed for faculty approval in a pretty airless environment for years. By the end, it took an act of will just to put together a declarative sentence. The most damning insult in grad school was “naive,” which was typically applied to anyone who actually made some sort of positive claim. (“Naive realism” was the worst, since it implied the unforgivable sin of claiming to actually know something about something.) Self-doubt can be taught.

In grad school, too, I recall the faculty being perplexed as to why so many doctoral students seemed oddly hesitant and overly deferential during oral exams. At one panel of grad student papers, I recall noticing that every single grad student started her presentation with “this is a work in progress.” Translated, that means “please don't attack me.” These habits are learned...."

"A buccaneer-scholar is anyone whose love of learning is not muzzled, yoked or shackled by any institution or authority; whose mind is driven to wander and find its own voice and place in the world."

True for nearly every discipline beside "painting" as well. Including the ones where one may be "more successful". I know a lot of useless computer scientists, for example.

"I have for all my mature life been impressed by people's tenacity, and in no specific more than discussion, whether in electronic forums or newspapers' letters to the editor..."

via: boingboing

"Logic stays true, wherever you may go,
So logic never tells you where you live."

"We aren't enchanted by Bayesian methods merely because they're beautiful. The beauty is a side effect."

"When the basic problem is your ignorance, clever strategies for bypassing your ignorance lead to shooting yourself in the foot"

"Books have led some to learning, and others to madness..."

"When the mind fixates on absolute discontinuities, mischief is often in the offing..."

"We need to unfocus, to rely more on the network or tribe to surface things of importance, and remain open to new opportunities: these are potentially more important than the work on the desk. Don't sharpen the knife too much."

Probably won't be able to attend.

Been using Quicksilver for months; time to take it to the next level.

Half of the inevitable cycle of lumping and splitting, in the context of machine learning....

Teaching agility