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Rob Aldridge
Works at GCS Agile
Attended Heatherhill High School
Lives in Melbourne, Victoria
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Rob Aldridge

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GCS Agile is proud to sponsor the first event of a series of AIIA industry events on the 18th of March at the RACV Club.  This luncheon event will focus on the Airport and Utilities sectors and explore the application of 'Intelligent Operations', where 'intelligent' technology, including big data and predictive analytics, can be used by business to drive operational efficiencies, productivity and the customer experience. A range of industry experts including Atakan Cetinsoy a key representative from our partner Big ML will present their experiences and also invite the audience to share their views.
For further information and registration please refer to the link.
http://www.aiia.com.au/events/event_details.asp?id=606806&group=
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One of the rare but brilliant conversations on latent variable estimation, distributed representations, neural networks and "deep learning" among other things from some of the pioneers in this field!

The interesting stuff starts at 12:00. #machinelearning

http://www.thetalkingmachines.com/blog/2015/2/26/the-history-of-machine-learning-from-the-inside-out 
In episode five of Talking Machines, we hear the first part of our conversation with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). Ryan introduces us to the ideas in tensor factorization methods for learning latent variable models (which is both a tongue twister and and one of the new tools in ML). To find out more on the topic, the paper Tensor decomposit...
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Rob Aldridge

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The abstract of DeepMind's recent publication in Nature [2] on learning to play video games claims: "While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces.” It also claims to bridge "the divide between high-dimensional sensory inputs and actions.” Similarly, the first sentence of the abstract of the earlier tech report version [1] of the article [2] claims to "present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning.”

However, the first such system [3] was created earlier at the Swiss AI Lab IDSIA, former affiliation of three authors of the Nature paper [2].

The system [3] indeed was able to "learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning” (quote from the abstract [2]), without any unsupervised pre-training. It was successfully applied to various problems such as video game-based race car driving from raw high-dimensional visual input streams.

It uses recent compressed recurrent neural networks [4] to deal with sequential video inputs in partially observable environments, while DeepMind's system [2] uses more limited feedforward networks for fully observable environments and other techniques from over two decades ago, namely, CNNs [5,6], experience replay [7], and temporal difference-based game playing like in the famous self-teaching backgammon player [8], which 20 years ago already achieved the level of human world champions (while the Nature paper [2] reports "more than 75% of the human score on more than half of the games”).

Neuroevolution also successfully learned to play Atari games [9].

The article [2] also claims "the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks”. Since other learning systems also can solve quite diverse tasks, this claim seems debatable at least.

Numerous additional relevant references can be found in Sec. 6 on "Deep Reinforcement Learning” in a recent survey [10]. A recent TED talk [11] suggests that the system [1,2] was a reason why Google bought DeepMind, indicating commercial relevance of this topic.

References

[1] V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, M. Riedmiller. Playing Atari with Deep Reinforcement Learning. Tech Report, 19 Dec. 2013, http://arxiv.org/abs/1312.5602

[2] V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, S.  Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, D. Hassabis. Human-level control through deep reinforcement learning. Nature, vol. 518, p 1529, 26 Feb. 2015.
http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html

[3] J. Koutnik, G. Cuccu, J. Schmidhuber, F. Gomez. Evolving Large-Scale Neural Networks for Vision-Based Reinforcement Learning. In Proc. Genetic and Evolutionary Computation Conference (GECCO), Amsterdam, July 2013. http://people.idsia.ch/~juergen/gecco2013torcs.pdf
Overview: http://people.idsia.ch/~juergen/compressednetworksearch.html

[4] J. Koutnik, F. Gomez, J. Schmidhuber. Evolving Neural Networks in Compressed Weight Space. In Proc. Genetic and Evolutionary Computation Conference (GECCO-2010), Portland, 2010. http://people.idsia.ch/~juergen/gecco2010koutnik.pdf

[5] K. Fukushima, K. (1979). Neural network model for a mechanism of pattern recognition unaffected by shift in position - Neocognitron. Trans. IECE, J62-A(10):658–665.

[6] Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel. Back-propagation applied to handwritten zip code recognition. Neural Computation, 1(4):541–551, 1989

[7] L. Lin. Reinforcement Learning for Robots Using Neural Networks. PhD thesis, Carnegie Mellon University, Pittsburgh, 1993.

[8]  G. Tesauro. TD-gammon, a self-teaching backgammon program, achieves master-level play. Neural Computation, 6(2):215–219, 1994.

[9] M. Hausknecht, J. Lehman, R. Miikkulainen, P. Stone. A Neuroevolution Approach to General Atari Game Playing. IEEE Transactions on Computational Intelligence and AI in Games, 16 Dec. 2013.

[10] J. Schmidhuber. Deep Learning in Neural Networks: An Overview. Neural Networks, vol. 61, 85-117, 2015 (888 references, published online in 2014). http://people.idsia.ch/~juergen/deep-learning-overview.html

[11] L. Page. Where’s Google going next? Transcript of TED event, 2014
https://www.ted.com/talks/larry_page_where_s_google_going_next/transcript?language=en


#machinelearning
#artificialintelligence
#computervision
#deeplearning
http://people.idsia.ch/~juergen/naturedeepmind.html
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PAPIs.io is a unique event in that it has been able to bring together data scientists, developers and practitioners from 20+ countries representing many different industries and educational institutions.

#papis2015   #machinelearning  
Following up on the success of its inaugural event last year, PAPIs.io 2015 is fast approaching upon us. This year’s event will take place in down under in the beautiful "harbour city” of Sydney.  ...
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Rob Aldridge

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You sometimes hear from some old-fashioned statisticians that data scientists know nothing about statistics, and that them - the statisticians - know everything. Here we prove that actually it is the exact opposite: data science has its own core of statistical science research, in addition to data plumbing, statistical API's, and business / competitive intelligence research. Here we highlight 11 major data science contributions to statistical science. I am not aware of any statistical science contribution to data science, but if you know one, you are welcome to share.
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Face detection software has slowly crept into mainstream use, but new research looks set to move the technology on significantly. Scientists have come up with a new approach that can regsiter face...
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Microsoft is building fast, low-power neural networks with FPGAs. "Microsoft claims that new FPGA designs provide greatly improved processing speed over earlier versions while consuming a fraction of the power of GPUs. This type of work could represent a big shift in deep learning if it catches on, because for the past few years the field has been largely centered around GPUs as the computing architecture of choice."

"If there's a major caveat to Microsoft's efforts, it might have to do with performance. While Microsoft's research shows FPGAs consuming about one-tenth the power of high-end GPUs (25W compared with 235W), GPUs still process images at a much higher rate."
Microsoft on Monday released a white paper explaining a current effort to run convolutional neural networks — the deep learning technique responsible for record-setting computer vision algorithms — on FPGAs rather than GPUs. Microsoft claims that new FPGA designs provide greatly improved processing speed over earlier versions while consuming a fraction of the power of…
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An interview with Geoff Hinton, Yoshua Bengio and Yann LeCun in the latest talking machines podcast (by my good friends +Ryan Adams and Katy Gorman)
http://www.thetalkingmachines.com/
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GCS Agile is proud continue our association with PAPIs.io as a sponsor of the 2015 Sydney conference, which will be convened on the 6th - 7th of August.  If you would like to submit a proposal or receive updates please feel free to click on the link below. 
If you would like to know more the website also contains videos of the 2014 presentations. Please refer to "Past Events"  We hope to see you there.

http://www.papis.io/#about
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Rob Aldridge

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Back in the 1940s before the polio vaccine was invented, the disease caused a lot of anxiety among parents of small children. How could you reduce your child’s risk of contracting this nasty illness? Some misguided public health experts apparently recommended avoiding ice cream, thanks to a study that showed a correlation between ice cream consumption and polio outbreaks. This study fortunately was BS. Yes, there was a correlation between ice cream consumption and polio outbreaks, but that was because both were common in the summer months. The authors of the study had mistaken correlation (ice cream consumption and polio are more common at the same time) with causation (ice cream increases your risk of disease).

Medical researchers often trawl through data sets to try and figure out what environmental factors cause chronic disease. Unfortunately, these kinds of studies sometimes make the same kinds of mistakes as the ice cream and polio study. Doctor and researcher John Ioannidis got a lot of people all riled up when he claimed in 2005 that “most published research findings are false“, and as controversial as his main claim might be, he was absolutely right when he pointed out there are some serious problems with the way statistics are often used — and some medical research studies are misleading or flawed as a result. Popular science articles in the media and on the Internet compound this problem by ignoring the limitations of the study they’re reporting. Fortunately you don’t have to be a math major to spot these kinds of problems; just some basic critical thinking skills will do. Here are six ways people sometimes misuse statistics and how to spot them.
Back in the 1940s before the polio vaccine was invented, the disease caused a lot of anxiety among parents of small children. How could you reduce your child's risk of contracting this nasty illnes...
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Researchers from the Ramón Llull University (Spain) have created a system capable of geolocating some videos by comparing their images and audio with a worldwide multimedia database, for cases where textual metadata is not available or relevant.

In the future, this could help to find people who have gone missing after posting images on social networks, or even to recognize locations of terrorist executions by organizations such as ISIS.
Eight randomly chosen keyframes of videos contained in the video/sound geotagged database used in this research (credit: Xavier Sevillano et al./Information
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Education
  • Heatherhill High School
    1991
  • Monash University
    Applied Science, 1991 - 1995
    Computer Science, Physics, Machine Vision
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Male
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Robert
Work
Occupation
Solution Architect
Employment
  • GCS Agile
    Practice Lead, 2014 - present
  • Artis Group
    Technical Lead, 2013 - 2014
  • Praxa Limited
    Senior Consultant, 2008 - 2013
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Melbourne, Victoria
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Chennai
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