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Posts Tagged ‘math’

Ramanujan’s Deathbed Conjecture Finally Proven

December 27th, 2012 12:51 admin View Comments

Math

jomama717 writes “Another chapter in the fascinating life of Srinivasa Ramanujan appears to be complete: ‘While on his death bed, the brilliant Indian mathematician Srinivasa Ramanujan cryptically wrote down functions he said came to him in dreams, with a hunch about how they behaved. Now 100 years later, researchers say they’ve proved he was right. “We’ve solved the problems from his last mysterious letters. For people who work in this area of math, the problem has been open for 90 years,” Emory University mathematician Ken Ono said. Ramanujan, a self-taught mathematician born in a rural village in South India, spent so much time thinking about math that he flunked out of college in India twice, Ono said.’”

Source: Ramanujan’s Deathbed Conjecture Finally Proven

Ask Slashdot: Math and Science iOS Apps For Young Kids?

November 23rd, 2012 11:59 admin View Comments

IOS

Oyjord writes “I have a very smart and curious 3-year-old daughter. Before anyone tries to derail my query, yes, we get a lot of play time outside with soccer and baseballs, and inside with blocks, Hot Wheels, PlayDoh, etc. However, on the rare occasion that we do sit down with my iPad, I’d like to solicit recommendations for good Math and Science apps for kids. There are hundreds of horribly gender-biased baking apps and Barbie apps for young girls, but they turn my stomach. She has a wonderfully curious mind, and really likes SkyView already, but I feel lost in a sea of pink and Hello Kitty apps.”

Source: Ask Slashdot: Math and Science iOS Apps For Young Kids?

Fujitsu Building Robot To Pass Math Exams

September 10th, 2012 09:06 admin View Comments

Math

itwbennett writes “Pity those poor Japanese students who attend cram schools, either full time or in addition to their regular schooling, to have a shot at passing the grueling math entrance exams for Tokyo University. If Fujitsu has its way, those students will be upstaged by a robot. The company has set a goal for the year 2021 of building an artificial intelligence robot that can pass the exams.”

Source: Fujitsu Building Robot To Pass Math Exams

Ask Slashdot: How Many of You Actually Use Math?

August 9th, 2012 08:48 admin View Comments

Math

An anonymous reader writes with a question that makes a good follow-on to the claim that mathematics requirements in U.S. schools unnecessarily limit students’ educational choices: “I’m a high school student who is interested in a career in a computer science or game development related position. I’ve been told by teachers and parents that math classes are a must for any technology related career. I’ve been dabbling around Unity3D and OGRE for about two years now and have been programming for longer than that, but I’ve never had to use any math beyond trigonometry (which I took as a Freshman). This makes me wonder: will I actually use calculus and above, or is it just a popular idea that you need to be a mathematician in order to program? What are your experiences?”

Source: Ask Slashdot: How Many of You Actually Use Math?

Ask Slashdot: What To Do With a Math Degree?

June 1st, 2012 06:24 admin View Comments

Math

First time accepted submitter badmojo17 writes “After achieving her lifelong dream of becoming a public school math teacher, my wife has found the profession to be much more frustrating than she ever expected. She could deal with having a group of disrespectful criminals as students if she had competent administrators supporting her, but the sad truth is that her administration causes more problems on a daily basis than her students do. Our question is this: what other professions are open to a bright young woman with a bachelor’s degree in math and a master’s degree in education? Without further education, what types of positions or companies might be interested in her as an employee?”

Source: Ask Slashdot: What To Do With a Math Degree?

Why You Don’t Want a $99 Xbox 360

May 8th, 2012 05:10 admin View Comments

Microsoft

itwbennett writes “Peter Smith has done the math on Microsoft’s $99 Xbox 360 — 4GB model (no hard drive) and a Kinect sensor. Here’s why it’s a bad deal: ‘You’ll be paying $99 + $359.76 in monthly fees, or $458.76 over the course of two years. Compare that with (I’m using prices from Amazon that were accurate as of May 7th, 2012) $287.70 for an Xbox 360 4GB + Kinect bundle, and two 12-month Xbox Live Gold cards at $48.41 each, a total of $384.52. So you’re paying almost $75 for the privilege of laying out small cash now.’ And then there’s the not insignificant matter of early termination fees.”

Source: Why You Don’t Want a $99 Xbox 360

Brain Scan Can Predict Math Mistakes

April 23rd, 2012 04:25 admin View Comments

Math

itwbennett writes “Computer Science Ph.D. candidate Federico Cirett says that he can predict with 80 percent accuracy when someone is about to make a mistake on a math question. Using an EEG machine, Cirett can identify the patterns in a volunteer’s thinking that are likely to result in an error 20 seconds or so before it’s made. ‘If we can detect when they are going to fail, maybe we can change the text or switch the question to give them another one at a different level of difficulty, but also to keep them engaged,’ Cirett said. ‘Brain wave data is the nearest thing we have to really know when the students are having problems.’ He will present a paper on his findings at the User Modeling, Adaptation and Personalization conference in July.”

Source: Brain Scan Can Predict Math Mistakes

What You Can Learn From Kaggle’s Top 10 Data Scientists

April 12th, 2012 04:30 admin View Comments

kaggle-150.jpgWhat do a Russian math professor, a Harvard neurobiologist, a French actuary and British finance quant all have in common? They all were recently identified as some of the top 10 Kaggle data scientists.

Each received the designation as part of their efforts in developing some of the best solutions to the website’s crowdsourcing analytics competitions. Learn why three of them participate in Kaggle, and how they became the alpha data geeks that they are:

  • Tim Salimans, a 26-year-old Ph.D. candidate in econometrics at Erasmus University Rotterdam in the Netherlands,
  • David Slate, an older computer programmer from the Chicago area, and
  • Jason Tigg, a 43-year-old with a Ph.D. in elementary particle physics from Oxford who is based in London, where he works trading statistical arbitrage in finance.

Salimans, who runs and plays a number of competitive sports, finds that “It’s mostly the competitive element of Kaggle that motivates me. I just like to be challenged this way.” The online leaderboard is another way. “The direct feedback it provides is quite unique in the area of data analysis and gives you a lot of motivation.”

But it helps to have some fame, too. After he won his first competition (a chess rating challenge), he was contacted by Thore Graepel of Microsoft Research, and ended up interning with him. But Kaggle also shortcuts the traditional academic review process to publish his work: “Publishing an academic article is a very slow and tedious process that commonly takes over a year in my field, while the descriptions of my winning entries in the Kaggle competitions get read by a similar number of people and only take an hour to write.”

Another top 10 winner is David Slate. He has been a computer programmer for nearly 50 years after getting degrees in physics. He has been doing predictive analytics for several decades and is retired now. His team at Northwestern University won the World Computer Chess Championship from 1977 to 1980. He developed a credit-card fraud detection system that is still in commercial use. Most of his contests have been jointly entered with Peter Frey under the team name “Old Dogs With New Tricks.”
kaggle process.jpg
“Every contest is fun and has interesting data. I like to apply my skills to solve some real problems and especially in the medical area.” Slate is in his 60s, which he touts as an advantage. “We can bring an impressive amount of geezer power to bear on the problem,” he told me. “We have also developed our own software tools for predictive analytics, too.”

It also helps to be persistent because “there is a lot of trial and error, and the contests require a fair amount of time to spend on them.” Slate mentions that he often tweaks his algorithms daily, trying new tactics. It certainly helps not having a day job to distract him from his contests!

Kaggle has been around for two years now and has had more than 33,000 participants from around the world. Competitions may have cash prizes attached to them, or can be used by college students as part of an in-class homework assignment. We have written about them before doing some very innovative things. Naming their top 10 scientists just seems so appropriate, given how they instantly track the leading entries to all of their contests.

Back when I was in my graduate statistics classes, I had no idea that the world of data science could be the wonderful and exciting place that it is now. In that era, we were slaves to problem sets, basically an upgrade to fifth-grade arithmetic homework assignments where you got a problem and had to show your work toward the solution. Can you say boring? It is no wonder that even Barbie thinks math is too tough.

shutterstock_61771345.jpgBut thanks to Kaggle in Class, students around the world have the opportunity to make math more fun, or at least more socially engaging. Salimans told me that he “first used Kaggle in Class last year, and I have never seen the students so enthusiastic about a class assignment. A lot of them worked on it for two weeks straight up to the deadline, while I had had trouble motivating them for some of the earlier assignments. An in-class competition is also great at getting the students to develop some real practical understanding of the different methods, in a way that most computer assignments fail to do.”

Jason Tigg, meahwhile, started doing assembly language programming as a teen, building a program to play Othello. He has done well on several Kaggle contests, including Photo Quality Prediction competition and the Claim Prediction Challenge.

“My two biggest motivations are fun and learning,” he said. “I feel lucky to be living through this chapter in history where machine intelligence is ramping up so rapidly. I feel a buzz around the area, which I imagine was how physics felt around the turn of the last century. People are trying out new ideas, and no one knows for sure where we will all end up.” He has entered a variety of competitions, with the goal of increasing his knowledge about new machine-learning techniques. That said, he looks at the leaderboard because it is “extremely useful for judging how much you are missing, and how much you need to learn.”

Tigg also busted the myth about how much computing power you need to solve the contest’s problems, “Do not worry about needing huge amounts of compute power, it is possible to do well in these competitions with very cheap setups.”

So good work to everyone who has entered Kaggle and other data science contests. Hopefully you can find inspiration from these three who have risen to the top!

Image courtesy of Shutterstock.com

Source: What You Can Learn From Kaggle’s Top 10 Data Scientists

What You Can Learn From Kaggle’s Top 10 Data Scientists

April 12th, 2012 04:30 admin View Comments

kaggle-150.jpgWhat do a Russian math professor, a Harvard neurobiologist, a French actuary and British finance quant all have in common? They all were recently identified as some of the top 10 Kaggle data scientists.

Each received the designation as part of their efforts in developing some of the best solutions to the website’s crowdsourcing analytics competitions. Learn why three of them participate in Kaggle, and how they became the alpha data geeks that they are:

  • Tim Salimans, a 26-year-old Ph.D. candidate in econometrics at Erasmus University Rotterdam in the Netherlands,
  • David Slate, an older computer programmer from the Chicago area, and
  • Jason Tigg, a 43-year-old with a Ph.D. in elementary particle physics from Oxford who is based in London, where he works trading statistical arbitrage in finance.

Salimans, who runs and plays a number of competitive sports, finds that “It’s mostly the competitive element of Kaggle that motivates me. I just like to be challenged this way.” The online leaderboard is another way. “The direct feedback it provides is quite unique in the area of data analysis and gives you a lot of motivation.”

But it helps to have some fame, too. After he won his first competition (a chess rating challenge), he was contacted by Thore Graepel of Microsoft Research, and ended up interning with him. But Kaggle also shortcuts the traditional academic review process to publish his work: “Publishing an academic article is a very slow and tedious process that commonly takes over a year in my field, while the descriptions of my winning entries in the Kaggle competitions get read by a similar number of people and only take an hour to write.”

Another top 10 winner is David Slate. He has been a computer programmer for nearly 50 years after getting degrees in physics. He has been doing predictive analytics for several decades and is retired now. His team at Northwestern University won the World Computer Chess Championship from 1977 to 1980. He developed a credit-card fraud detection system that is still in commercial use. Most of his contests have been jointly entered with Peter Frey under the team name “Old Dogs With New Tricks.”
kaggle process.jpg
“Every contest is fun and has interesting data. I like to apply my skills to solve some real problems and especially in the medical area.” Slate is in his 60s, which he touts as an advantage. “We can bring an impressive amount of geezer power to bear on the problem,” he told me. “We have also developed our own software tools for predictive analytics, too.”

It also helps to be persistent because “there is a lot of trial and error, and the contests require a fair amount of time to spend on them.” Slate mentions that he often tweaks his algorithms daily, trying new tactics. It certainly helps not having a day job to distract him from his contests!

Kaggle has been around for two years now and has had more than 33,000 participants from around the world. Competitions may have cash prizes attached to them, or can be used by college students as part of an in-class homework assignment. We have written about them before doing some very innovative things. Naming their top 10 scientists just seems so appropriate, given how they instantly track the leading entries to all of their contests.

Back when I was in my graduate statistics classes, I had no idea that the world of data science could be the wonderful and exciting place that it is now. In that era, we were slaves to problem sets, basically an upgrade to fifth-grade arithmetic homework assignments where you got a problem and had to show your work toward the solution. Can you say boring? It is no wonder that even Barbie thinks math is too tough.

shutterstock_61771345.jpgBut thanks to Kaggle in Class, students around the world have the opportunity to make math more fun, or at least more socially engaging. Salimans told me that he “first used Kaggle in Class last year, and I have never seen the students so enthusiastic about a class assignment. A lot of them worked on it for two weeks straight up to the deadline, while I had had trouble motivating them for some of the earlier assignments. An in-class competition is also great at getting the students to develop some real practical understanding of the different methods, in a way that most computer assignments fail to do.”

Jason Tigg, meahwhile, started doing assembly language programming as a teen, building a program to play Othello. He has done well on several Kaggle contests, including Photo Quality Prediction competition and the Claim Prediction Challenge.

“My two biggest motivations are fun and learning,” he said. “I feel lucky to be living through this chapter in history where machine intelligence is ramping up so rapidly. I feel a buzz around the area, which I imagine was how physics felt around the turn of the last century. People are trying out new ideas, and no one knows for sure where we will all end up.” He has entered a variety of competitions, with the goal of increasing his knowledge about new machine-learning techniques. That said, he looks at the leaderboard because it is “extremely useful for judging how much you are missing, and how much you need to learn.”

Tigg also busted the myth about how much computing power you need to solve the contest’s problems, “Do not worry about needing huge amounts of compute power, it is possible to do well in these competitions with very cheap setups.”

So good work to everyone who has entered Kaggle and other data science contests. Hopefully you can find inspiration from these three who have risen to the top!

Image courtesy of Shutterstock.com

Source: What You Can Learn From Kaggle’s Top 10 Data Scientists

The Numbers Behind the Copyright Math

March 20th, 2012 03:14 admin View Comments

Math

TheUnknownCoder writes “The MPAA claims $58 billion in actual U.S. economic losses and 373,000 lost jobs due to piracy. Where are these numbers coming from? Rob Reid puts these numbers into perspective in this TED Talk, leaving us even more puzzled about the math behind copyright laws. ‘Ignoring improbabilities like pirated steaks and daffodils, I looked at actual employment and headcount in actual content industries, and found nothing approaching the claimed losses. There are definitely concrete and quantifiable piracy-related losses in the American music industry. The Recording Industry Association’s website has a robust and credible database that details industry sales going back to 1973, which any researcher can access for a few bucks (and annoying as I’ve found the RIAA to be on certain occasions, I applaud them for making this data available). I used it to compare the industry’s revenues in 1999 (when Napster debuted) to 2010 (the most recent available data). Sales plunged from $14.6 billion down to $6.8 billion — a drop that I rounded to $8 billion in my talk. This number is broadly supported by other sources, and I find it to be entirely credible. But this pattern just isn’t echoed in other major content industries.’”

Source: The Numbers Behind the Copyright Math

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