Thursday, April 5, 2012
Conference paper deadline: MLSP 2012
The deadline for submitting papers to the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2012 is 7 May 2012. This workshop will be held in Santanda, Spain, 23-26 September 2012.
Wednesday, April 4, 2012
Deadline extended: Special Issue: Applications of ECoS
The deadline for submitting papers to the special issue of Evolving Systems on Applications of Evolving Connectionist Systems has been extended to 14 May 2012.
Reminder: paper submission deadline for UKCI 2012
A reminder that the paper submission deadline for the 12th UK Annual Workshop on Computational Intelligence (UKCI) 2012 is May 1, 2012. This workshop will be held in Edinburgh, Scotland, UK, 5-7 September, 2012.
Tuesday, April 3, 2012
Open source textbooks
The principle of Open Source Software (OSS) has been established for a long time. The Linux OS (or GNU/Linux, for the purists out there) made the idea of freely giving away software and source code respectable. Concerns about the quality of the software, and whether or not companies could make money from open source, have all been washed away over the years. OSS tends to be more stable, has bugs fixed faster, and evolves faster than commercial software. Also, companies have been making money from OSS for years: Red Hat being just one example.
In this pod cast transcript Steven Cherry from IEEE Spectrum talks with Richard Baraniuk of Rice University about Open Source Textbooks (OST). Baraniuk has founded the Connexions platform, a platform for developing open source textbooks.
I can think of several objections to the idea of OST, but I believe that, in common with OSS, these objections are not insurmountable problems:
Firstly, there is the issue of quality control. When an author submits a book proposal to a publisher, the publisher will send the outline and a sample chapter to reviewers. But, the reviewers tend to be people the author knows, as unlike anonymous peer review of journal articles, a textbook author can often nominate the reviewers of their proposal.
Secondly, there is the issue of formatting the book. If you use an authoring system like LaTeX, formatting a book isn't really that hard (certainly easier than formatting a book in Word). Publishers tend to only provide an author with a template, anyway.
Thirdly, advertising the book. This seems to vary fairly widely between different publishers, with some putting a lot of effort into it, and others doing much less. With the reach that the Internet provides people now, I don't see advertising as a large issue. If you have a blog, website, or networking profile (and I think that a serious academic should have all of these), you can advertise your book there. If you can afford it, you can buy some ads through Google or one of the other advertising services. It takes a bit of work, but not as much as writing the book in the first place.
Fourthly, producing the book. If you are going entirely for a soft-copy, open-source approach, that's not a problem: just whack the book up on a website, and let people download it. If you want to sell hard copies, then you can go with a publishing-on-demand (POD) service like lulu.com. Using POD has the advantage that you don't need to pay for inventory before you can start selling copies. That is, while most traditional publishers like to produce the hard copies themselves, they also like to print several thousand copies, and then sell them. With POD, copies are printed as they are sold. No inventory, so no big pile of books (money!) sitting in a warehouse where they might get sold later on. If the publisher doesn't decide to kill the book, or sell the lot off at a loss, or just pulp them.
Finally, money! Traditional publishers take a big chunk of the sale price of a book for themselves: around 90%, or more. Combined with the relatively small number of copies that most textbooks sell, an author isn't going to make a lot of money from the exercise (there are exceptions, but it's a pretty long tail: most textbook authors will make very little money, and just a few will make a lot). If you publish open-source, then there are other ways of making money from the book - advertising on the website you host it on, soliciting donations, and selling hard copies via POD services, which tend to give larger shares to the authors. For an early-career author like myself, the biggest problem I face isn't missing out on a royalty cheque, it's obscurity.
I've come to realise that, in common with the problems with academic journal publishers, textbook publishers really don't add that much value. Sure, there is the cachet associated with publishing with certain publishers, just as there is with publishing with certain journals, but is that enough of a reason to put up with their disadvantages?
An OST system like Connexions also solve most of the objections I listed above: material that is submitted to Connexions is subject to peer review, it is becoming well-established as a place to go to for OST, and they sell hard copies. I really do think that, just as open access journals are the future for publishing papers, open source textbooks are the future of textbooks, and that within a generation (certainly within my working lifetime) we will see traditional text book publishers diminish in importance.
Is Connexions to OST as Source Forge is to OSS? Would you spend money to buy a hard-copy of an OST textbook? Would you contribute money in other ways to support the work of an OST author? Would you assign an OST as a class textbook?
In this pod cast transcript Steven Cherry from IEEE Spectrum talks with Richard Baraniuk of Rice University about Open Source Textbooks (OST). Baraniuk has founded the Connexions platform, a platform for developing open source textbooks.
I can think of several objections to the idea of OST, but I believe that, in common with OSS, these objections are not insurmountable problems:
Firstly, there is the issue of quality control. When an author submits a book proposal to a publisher, the publisher will send the outline and a sample chapter to reviewers. But, the reviewers tend to be people the author knows, as unlike anonymous peer review of journal articles, a textbook author can often nominate the reviewers of their proposal.
Secondly, there is the issue of formatting the book. If you use an authoring system like LaTeX, formatting a book isn't really that hard (certainly easier than formatting a book in Word). Publishers tend to only provide an author with a template, anyway.
Thirdly, advertising the book. This seems to vary fairly widely between different publishers, with some putting a lot of effort into it, and others doing much less. With the reach that the Internet provides people now, I don't see advertising as a large issue. If you have a blog, website, or networking profile (and I think that a serious academic should have all of these), you can advertise your book there. If you can afford it, you can buy some ads through Google or one of the other advertising services. It takes a bit of work, but not as much as writing the book in the first place.
Fourthly, producing the book. If you are going entirely for a soft-copy, open-source approach, that's not a problem: just whack the book up on a website, and let people download it. If you want to sell hard copies, then you can go with a publishing-on-demand (POD) service like lulu.com. Using POD has the advantage that you don't need to pay for inventory before you can start selling copies. That is, while most traditional publishers like to produce the hard copies themselves, they also like to print several thousand copies, and then sell them. With POD, copies are printed as they are sold. No inventory, so no big pile of books (money!) sitting in a warehouse where they might get sold later on. If the publisher doesn't decide to kill the book, or sell the lot off at a loss, or just pulp them.
Finally, money! Traditional publishers take a big chunk of the sale price of a book for themselves: around 90%, or more. Combined with the relatively small number of copies that most textbooks sell, an author isn't going to make a lot of money from the exercise (there are exceptions, but it's a pretty long tail: most textbook authors will make very little money, and just a few will make a lot). If you publish open-source, then there are other ways of making money from the book - advertising on the website you host it on, soliciting donations, and selling hard copies via POD services, which tend to give larger shares to the authors. For an early-career author like myself, the biggest problem I face isn't missing out on a royalty cheque, it's obscurity.
I've come to realise that, in common with the problems with academic journal publishers, textbook publishers really don't add that much value. Sure, there is the cachet associated with publishing with certain publishers, just as there is with publishing with certain journals, but is that enough of a reason to put up with their disadvantages?
An OST system like Connexions also solve most of the objections I listed above: material that is submitted to Connexions is subject to peer review, it is becoming well-established as a place to go to for OST, and they sell hard copies. I really do think that, just as open access journals are the future for publishing papers, open source textbooks are the future of textbooks, and that within a generation (certainly within my working lifetime) we will see traditional text book publishers diminish in importance.
Is Connexions to OST as Source Forge is to OSS? Would you spend money to buy a hard-copy of an OST textbook? Would you contribute money in other ways to support the work of an OST author? Would you assign an OST as a class textbook?
Monday, April 2, 2012
Reminder: paper submission deadline SEAL 2012
A reminder that the deadline for submitting papers to the 9th International Conference on Evolution and Learning (SEAL) 2012 is 1 May 2012. This conference will be held in Hanoi, Vietnam, 16-19 December, 2012.
Thursday, March 29, 2012
Reminder: paper submission deadline for AI'12
A reminder that the deadline for submitting papers to the 25th Australasian Joint Conference on Artificial Intelligence (AI) 2012 is 29 June, 2012. This conference will be held in Sydney, Australia, 4-7 December, 2012.
Squirrel detection with SVM
Below is an entertaining video explaining how to automatically squirt squirrels with a water gun. What's interesting about this is that the presenter used a Support Vector Machine (SVM) to classify the images from the camera as either a squirrel or not a squirrel. I haven't talked about SVM on this blog much, but they are very powerful, learning algorithms that often outperform neural networks in classification applications.
He starts talking about the details of squirrel detection about the 7:30 mark - before that he describes the image processing toolkit he used to segment the images from the camera into blobs, where each blob needed to be classified as either a squirrel or not a squirrel. I was particularly interested in how he used three different kinds of features as inputs to the SVM: size of the blob segmented from the image; the colour histogram of the blob; and the entropy of the blob, where entropy is used as a measure of the "fuzziness" of the blob - squirrels have fuzzy, furry tails, while birds do not. This shows that careful thought is always required when selecting the inputs to a classifier or a learning algorithm. You can't just throw everything in and hope to get something useful out!
He starts talking about the details of squirrel detection about the 7:30 mark - before that he describes the image processing toolkit he used to segment the images from the camera into blobs, where each blob needed to be classified as either a squirrel or not a squirrel. I was particularly interested in how he used three different kinds of features as inputs to the SVM: size of the blob segmented from the image; the colour histogram of the blob; and the entropy of the blob, where entropy is used as a measure of the "fuzziness" of the blob - squirrels have fuzzy, furry tails, while birds do not. This shows that careful thought is always required when selecting the inputs to a classifier or a learning algorithm. You can't just throw everything in and hope to get something useful out!
Wednesday, March 28, 2012
Scientific Writing
Adam Ruben has a written a rather tongue-in-cheek essay on How to Write Like a Scientist. He asks why can't we scientists write the way other people write? Why are scientific papers written the way they are?
Scientific papers are written the way the are because of their purpose. The whole point of a paper is to describe what the authors did and what they found, and to communicate this as widely as possible, to readers who may not have English as a first language, or who may be approaching the paper from a different field. If papers are going to do this effectively, they have to be unambiguous. The problem with being unambiguous in English is that there are so many words that have the same, or nearly the same, meaning - only, lone, sole, and so on.
Papers use the past tense because you are describing what you have done, not what you are doing or what you will do. Papers have used the passive voice for a long time, but I've noticed a change to active voice recently, and I'm trying to move to active voice in my own writing (my current supervisor once admonished me with "No-one in my lab uses the passive voice!"). The same thing applies to using "we" or "the author" instead of "I" - it's been the fashion to not use "I", but that's changing. If the work was done by more than one person, then it's entirely appropriate to use "we".
I especially liked his comments about the use of "obviously" and I'll admit I've used it a few times myself. Not to demonstrate my intellectual superiority, but to forestall comments from reviewers: the times when I've not inserted a phrase like "obviously, ovens can be hot"*, at least one reviewer has pointed it out.
The use of idioms should be avoided. Idioms can be highly specific to a certain culture. For example, Australians and New Zealanders both speak English. Also, the New Zealand accent is close enough to the Australian accent that most of the time, when I speak, I can pass for a local. The one thing that gives me away as a New Zealander in Australia is the idioms I use: I use New Zealand idioms that just aren't used in Australia. Now, imagine I used those idioms in a paper read by people all over the world: how many people would understand it?**
I've touched on this issues in a previous post, as well as common grammatical errors to avoid and ten rules for good writing. I think papers can be made more accessible without losing clarity, but it's going to take time, and a lot more work from authors.
*This refers to a sign on the oven in the tea room shared by the IT staff at Lincoln University: "Warning: Oven may be hot". Other signs in the area read "Warning: fridge may be cold" and "Warning: floor".
**That said, I have recently used the term "munted" in a paper - look it up if you want to know what it means!
Scientific papers are written the way the are because of their purpose. The whole point of a paper is to describe what the authors did and what they found, and to communicate this as widely as possible, to readers who may not have English as a first language, or who may be approaching the paper from a different field. If papers are going to do this effectively, they have to be unambiguous. The problem with being unambiguous in English is that there are so many words that have the same, or nearly the same, meaning - only, lone, sole, and so on.
Papers use the past tense because you are describing what you have done, not what you are doing or what you will do. Papers have used the passive voice for a long time, but I've noticed a change to active voice recently, and I'm trying to move to active voice in my own writing (my current supervisor once admonished me with "No-one in my lab uses the passive voice!"). The same thing applies to using "we" or "the author" instead of "I" - it's been the fashion to not use "I", but that's changing. If the work was done by more than one person, then it's entirely appropriate to use "we".
I especially liked his comments about the use of "obviously" and I'll admit I've used it a few times myself. Not to demonstrate my intellectual superiority, but to forestall comments from reviewers: the times when I've not inserted a phrase like "obviously, ovens can be hot"*, at least one reviewer has pointed it out.
The use of idioms should be avoided. Idioms can be highly specific to a certain culture. For example, Australians and New Zealanders both speak English. Also, the New Zealand accent is close enough to the Australian accent that most of the time, when I speak, I can pass for a local. The one thing that gives me away as a New Zealander in Australia is the idioms I use: I use New Zealand idioms that just aren't used in Australia. Now, imagine I used those idioms in a paper read by people all over the world: how many people would understand it?**
I've touched on this issues in a previous post, as well as common grammatical errors to avoid and ten rules for good writing. I think papers can be made more accessible without losing clarity, but it's going to take time, and a lot more work from authors.
*This refers to a sign on the oven in the tea room shared by the IT staff at Lincoln University: "Warning: Oven may be hot". Other signs in the area read "Warning: fridge may be cold" and "Warning: floor".
**That said, I have recently used the term "munted" in a paper - look it up if you want to know what it means!
Thursday, March 22, 2012
Reminder: paper submission deadline for AIAA 2012
A reminder that the deadline for submitting papers to the 7th International Symposium Advances in Artificial Intelligence and Applications (AIAA) 2012 is 22 April 2012. This conference will be held in Wroclaw, Poland, 9-12 September, 2012.
Wednesday, March 21, 2012
Reminder: paper submission deadline for iCAST 2012
A reminder that the deadline for submitting papers to the 4th International Conference on Awareness Science and Technology (iCAST) 2012 is 15 April 2012. The conference will be held in Seoul, Korea, 21-24 August, 2012.
Tuesday, March 20, 2012
Call for papers: Applications of ECoS
Special issue of Evolving Systems on
Applications of Evolving Connectionist Systems
Guest Editor
Scope
The topic of this special issue is “Applications of Kasabov’s Evolving Connectionist Systems”.
In modern society, the volume and rate of data production are huge and set to increase. To process and utilise this avalanche of data, methods are needed that can rapidly and accurately model it as it becomes available. These models must be able to learn throughout their lifetimes, without forgetting what they have previously learned, and be able to explain themselves.
Kasabov’s Evolving Connectionist Systems (ECoS) are able to fulfil each of these requirements. They are a class of constructive neural networks that learn via structural growth and adaptation. They have a fast, one-pass learning algorithm, where all that can be learnt from the data is learned in the first training pass. Because of their open structure, they exhibit continuous, life-long learning whereby the structure expands as necessary to accommodate new data. Finally, they have a strong resistance to catastrophic forgetting following additional training on new data.
Examples of ECoS networks include the Evolving Fuzzy Neural Network (EFuNN), which was the first ECoS network published and is characterised by embedded fuzzy logic elements. There is also the Simple Evolving Connectionist System (SECoS), which is essentially an EFuNN with the fuzzy elements removed, and the Dynamic Evolving Fuzzy Inference System (DENFIS) for discovering Takagi-Sugeno style fuzzy rules. Many ECoS networks use fuzzy rule extraction algorithms that allow for the explanation of what the networks have learned, in a comprehensible manner.
ECoS networks are well suited to applications that are dealing with new data continuously and that have dynamic, time-critical aspects. Previous applications of ECoS include:
- Stock market prediction and macroeconomic modelling
- Speech recognition, especially multi-speaker speech recognition
- Bioinformatics and medical modelling
- Image and video parsing
- Robot control
- Information system security
The special issue is concerned with all aspects of the application of ECoS networks to real-life problems and data sets. Topics of interest include, but are not limited to:
- Applications of ECoS to real-world problems
- Data mining of complex data sets using ECoS
- Comparisons of ECoS with other algorithms over real-world data sets
- Modifications of ECoS algorithms to fit them to real-world problems
Proposed Schedule
- Submission due date: 16 April, 2012
- Preliminary notification of acceptance: 4 June, 2012
- Revised manuscripts due: 9 July, 2012
- Final acceptance notification: 6 August, 2012
- Final version due: 3 September, 2012
- Intended publication date: January, 2013
Submission
The special issue invites original contributions within the specified scope. Manuscripts must not be under review elsewhere, nor can they have been previously published. Extended conference papers must contain at least 30% new material. Please format all manuscripts according to the Instructions for Authors:
Please submit all papers via the online submission system:
Monday, March 19, 2012
Reminder: conference paper deadline for IJCCI 2012
A reminder that the deadline for submitting papers to the International Joint Conference on Computational Intelligence (IJCCI) 2012 is 19 April 2012. This conference will be held in Barcelona, Spain, 5-7 October, 2012.
Friday, March 16, 2012
Reminder: paper submission deadline for ISICA 2012
A reminder that the deadline for papers submitted to the International Symposium on Intelligence Computing and Applications (ISICA) 2012 is 15 April 2012. This conference will be held in Wuhan, China, 27-28 October, 2012.
Thursday, March 15, 2012
Reminder: paper deadline for ICCCI 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Collective Intelligence (ICCCI) 2012 is 15 April 2012. This conference will be held in Ho Chi Minh City, Vietnam, 28-30 November, 2012.
Wednesday, March 14, 2012
Reminder: paper submission deadline: IEEE CIG 2012
A reminder that the deadline for submitting papers to the IEEE Conference on Computational Intelligence in Games (IEEE CIG) 2012 is 15 April 2012. This conference will be held in Granada, Spain, 12-15 September, 2012.
Tuesday, March 13, 2012
Reminder: paper submission deadline for CBR-MD 2012
A reminder that the deadline for submitting papers to the International Workshop Case-Based Reasoning (CBR-MD) 2012 is 13 April 2012. This workshop will be held in Berlin, Germany, 20 July 2012.
Friday, March 9, 2012
Publishing or perishing 3
Following this previous post, I've found a few more articles about the dismissal of staff from the University of Sydney, for not publishing at least four papers in three years. This article is scathing of the university management, while Alex Burns, in this post, is in a similar vein to what I wrote: that four papers in three years is not an excessive number and that most academics should be able to meet it.
The most interesting post I found was this one, from David McGloin at the University of Dundee, where he lists a number of reasons someone might not reach the target number of publications. This is useful, as it informs as to what strategies academics could follow to avoid finding themselves in this sort of situation. Below, I reproduce each of his points, along with my responses:
It could be that you’re on the brink of some big breakthrough and the focus of this has taken many years to complete.
It is very dangerous for any academic to focus on one project to the exclusion of all others. Also, any project can be broken up into small, publishable chunks. That is, rather than writing up a single magnum opus of a paper at the end of the project, one should publish several smaller papers during the course of the work. This is more likely to make funding agencies happy as well, as it shows them that you are being consistently productive.
It may be that you’ve had bad luck with papers getting accepted, or have been doing good work, but maybe aiming to high up the journal league table.
Reformatting a rejected paper for another journal doesn't take very long. Waiting for reviews takes a long time (six months or more for some of my papers) but again, no academic should be working on just one project at a time. Everyone gets a period of bad luck with getting papers accepted (I had a long string of rejections throughout 2010 - I made up for it in 2011). The important thing is to have more than one project on the go at any one time, and to have a fast turn-around on rejected papers. If you follow a journal article submission strategy similar to the one I suggest, you should already have a good idea of other journals you could submit to.
It could be that you have had a run of poor luck on grant funding, and have not had the support to do your work and write up results, in terms of PhD students, postdocs, or simply a lack of equipment.
I do tend to agree with this point, especially for fields that need a lot of equipment to get results. I will point out, though, that having a good publication record will help with getting research grants.
Maybe a series of experiments didn’t work, but the next one will (and it will win a Nobel Prize).
Again, it is very important to pursue more than one research project at a time. That way, if one set of experiments doesn't work out, you can still publish the results from another.
Maybe your research output is highly subjective (think works by artists) and the critics didn’t like your last show.
This is more of a problem for researchers in the humanities. As a scientist I can't really comment on this, other than to point again to my responses above.
Maybe your research rivals knew about your employment conditions and decided to reject your last paper (to make it to the magic four) to get you sacked.
This is the most frightening point. Not only is such behavior completely unethical, it undermines the entire peer-review process. Anyone engaging in such behavior - rejecting papers just because the author is a rival - should be sacked immediately. If this does happen, it is also a failure on the part of the journal editors. Most journal submission systems allow the authors to list reviewers they are opposed to. Any editor who sends a paper to a reviewer who they have reasonable suspicion is a rival of the author, is failing to do their job.
Or maybe, just maybe you didn’t feel the need to publish every last little bit of work to avoid saturating the journals and keep the overall quality of published work high enough to make it bearable to read them.
This is a non sequitor. Submitting a lot of papers does not mean a lack of quality in the papers. As I mentioned above, you can break your project up into smaller, publishable chunks and submit a paper on each. Planning your research program is an essential skill for the professional researcher. Also, if the quality of the paper is so low that it's unreadable, how would it get published to begin with?
Maybe you published one Nature paper a year over the last three years and nothing else, and they each got 500 citations
This is one of those situations that could occur, but is really unlikely. The people I know who do publish in Nature, are the people who publish 20+ papers (journal articles) per year! I really can't see how anyone could be good enough to publish three papers in a row in Nature yet not be good enough to get one more paper published in another journal.
Publish or perish is the rule of academia, and has been for a long time. Sensible and positive ways you can publish without perishing are:
The most interesting post I found was this one, from David McGloin at the University of Dundee, where he lists a number of reasons someone might not reach the target number of publications. This is useful, as it informs as to what strategies academics could follow to avoid finding themselves in this sort of situation. Below, I reproduce each of his points, along with my responses:
It could be that you’re on the brink of some big breakthrough and the focus of this has taken many years to complete.
It is very dangerous for any academic to focus on one project to the exclusion of all others. Also, any project can be broken up into small, publishable chunks. That is, rather than writing up a single magnum opus of a paper at the end of the project, one should publish several smaller papers during the course of the work. This is more likely to make funding agencies happy as well, as it shows them that you are being consistently productive.
It may be that you’ve had bad luck with papers getting accepted, or have been doing good work, but maybe aiming to high up the journal league table.
Reformatting a rejected paper for another journal doesn't take very long. Waiting for reviews takes a long time (six months or more for some of my papers) but again, no academic should be working on just one project at a time. Everyone gets a period of bad luck with getting papers accepted (I had a long string of rejections throughout 2010 - I made up for it in 2011). The important thing is to have more than one project on the go at any one time, and to have a fast turn-around on rejected papers. If you follow a journal article submission strategy similar to the one I suggest, you should already have a good idea of other journals you could submit to.
It could be that you have had a run of poor luck on grant funding, and have not had the support to do your work and write up results, in terms of PhD students, postdocs, or simply a lack of equipment.
I do tend to agree with this point, especially for fields that need a lot of equipment to get results. I will point out, though, that having a good publication record will help with getting research grants.
Maybe a series of experiments didn’t work, but the next one will (and it will win a Nobel Prize).
Again, it is very important to pursue more than one research project at a time. That way, if one set of experiments doesn't work out, you can still publish the results from another.
Maybe your research output is highly subjective (think works by artists) and the critics didn’t like your last show.
This is more of a problem for researchers in the humanities. As a scientist I can't really comment on this, other than to point again to my responses above.
Maybe your research rivals knew about your employment conditions and decided to reject your last paper (to make it to the magic four) to get you sacked.
This is the most frightening point. Not only is such behavior completely unethical, it undermines the entire peer-review process. Anyone engaging in such behavior - rejecting papers just because the author is a rival - should be sacked immediately. If this does happen, it is also a failure on the part of the journal editors. Most journal submission systems allow the authors to list reviewers they are opposed to. Any editor who sends a paper to a reviewer who they have reasonable suspicion is a rival of the author, is failing to do their job.
Or maybe, just maybe you didn’t feel the need to publish every last little bit of work to avoid saturating the journals and keep the overall quality of published work high enough to make it bearable to read them.
This is a non sequitor. Submitting a lot of papers does not mean a lack of quality in the papers. As I mentioned above, you can break your project up into smaller, publishable chunks and submit a paper on each. Planning your research program is an essential skill for the professional researcher. Also, if the quality of the paper is so low that it's unreadable, how would it get published to begin with?
Maybe you published one Nature paper a year over the last three years and nothing else, and they each got 500 citations
This is one of those situations that could occur, but is really unlikely. The people I know who do publish in Nature, are the people who publish 20+ papers (journal articles) per year! I really can't see how anyone could be good enough to publish three papers in a row in Nature yet not be good enough to get one more paper published in another journal.
Publish or perish is the rule of academia, and has been for a long time. Sensible and positive ways you can publish without perishing are:
- pursuing more than one research project at a time
- collaborating widely (this is pretty easy to do in computational intelligence, as our algorithms are so widely applicable
- breaking your research into small, publishable chunks
- rapid turn-around on rejected papers
Thursday, March 8, 2012
Reminder: paper submission deadline for CISE 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Intelligence and Software Engineering (CISE) 2012 is 11 June 2012. This conference will be held in Wuhan, China, December 14-16, 2012.
Wednesday, March 7, 2012
Conference paper deadline: IDA 2012
The deadline for submitting papers to the Eleventh International Symposium on Intelligence Data Analysis (IDA) 2012 is 12 May 2012. This symposium will be held in Helsinki, Finland, 27-27 October, 2012.
Tuesday, March 6, 2012
Call for papers: ELM 2012
The deadline for submitting papers to the International Symposium on Extreme Learning Machines (ELM) 2012 is 1 June, 2012. This symposium will be held in Singapore 11-13 December, 2012.
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