Sunday, March 31, 2013

Graphlab Workshop on Large Scale Machine Learning 2013





You probably recall this entry on Why should you care about last year's GraphLab workshop, Well, the reasons you should care have not really changed that much, except that after the 300+ researchers from 100+ companies who made it a success last year, Danny Bickson and his crew are organizing a new workshop on July 1st in the Bay Area.

Registration is now open and if you register now with the   NuitBlanche discount code you'll get a 25% (30%) discount on your registration fee . The much preliminary agenda is here. I am on the program committee and if you want to be a sponsor of the meeting like these other folks, please let me know, I'll forward your interest to the organizers. Danny also tells me that this time, they will get some subcontractor to produce the videos of the talks. In the meantime, here are some related entries:
All the blog entries mentioning GraphLab on Nuit Blanche can be found at:

Saturday, March 30, 2013

Nuit Blanche in Review (March 2013)

If someone can take images from the Mars Curiosity website and stitch them together to create a panorama and get noticed by the interwebs in the process, do you think someone who would take on the Curiosity Super-Resolution Challenge and release a photo that not even NASA can provide, would get worldwide recognition. I am thinking yes, but then again, I am biased. 

Anyway, without further due, here are the exciting entries that sprung up since the last Nuit Blanche in Review for February 2013. We had six implementations made available by their authors. Let us note that we are now reaching the number 3 in the number of Analysis Operator Learning algorithms made available and we have close to that number in the number of algorithms dedicated to Sparse Subspace Clustering. Let's put this in perspective, six years ago to this day, there were only 3 reconstruction solvers available (besides CVX) in the field of compressive sensing The list has grown since and continues this month with SPASH and an Improved SL0. Other algorithms permit Spectral Compressive Sensing with Polar Interpolation or evaluate k-support Norm Regularized Risk Minimization

There were only two Sunday morning insights this month, one on Matrix Factorizations and the Grammar of Life and the other one on How to spot a compressive sensing system: there we looked into the case of the Randomized MALDI TOF MS/MS systems. Some feedback tells me that we'll see some action on this front in the future. Every month, there is a thematic that's forming under the weight of several publications/preprints. This month was no different, we saw much interest in phase transitions [see phase transition below and Living on the edge], the ever advances in MRI which accounts for a substantial number of papers that are truly innovative [Blind compressive sensing dynamic MRI below ] because some use the detection capabilities of compressive sensing as opposed to just reconstruction [ Magnetic resonance fingerprinting ]. I also noted the similarity between Well Logging and Nanopore Sequencing (more on that later) and that sometimes a least squares solution solves a different problem (see Convenience clouds your mind ).We also had some wonderful feedback from the readers as well as insightful blog entries from others, a few workshop announcements, videos and slides as well as two jobs announcements. Voila!

All other Nuit Blanche Monthly Reviews are at: 

Inplementations:
Blogs and Reader's Reviews
Workshop announcements, videos and slides:





Join the CompressiveSensing subreddit or the Google+ Community and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.

Friday, March 29, 2013

Videos: 2012 IPAM Graduate Summer School: Deep Learning, Feature Learning

From Yann LeCun's feed here are the videos of last summer's IPAM's grad school:


Graduate Summer School: Deep Learning, Feature Learning

July 9 - 27, 2012

UCLA Faculty Center
480 Charles E. Young Drive
California Room

Printable Version

Monday, July 09, 2012

Morning Session

8:00 - 8:45Check-In/Breakfast (Hosted by IPAM)
8:45 - 9:00Welcome and Opening Remarks
9:00 - 10:00
10:00 - 10:30Break
10:30 - 11:30
"PART 2: Using backpropagation for fine-tuning a generative model to be better at discrimination"
Play Video
11:30 - 12:00Break
12:00 - 1:00Joint talk: James Bergstra (Harvard), Clement Farabet (NYU)
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Deep Learning, Graphical Models, Energy-Based Models, Structured Prediction"

Play Video
3:30 - 4:00Break
4:00 - 5:00
"Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction (Part 2)"
Presentation (PDF File)
Play Video
5:00 - 6:30Reception (Hosted by IPAM)

Tuesday, July 10, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Deep Learning, Self-Taught Learning and Unsupervised Feature Learning (Part 1 Slides1-68; Part 2 Slides 69-109)"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Advanced topics + Research philosophy / Neural Networks: Representation"
Presentation (PDF File)
Play Video
11:30 - 12:00Break
12:00 - 1:00
"Non-linear hypotheses"
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Non-linear hypotheses (Part 2)"

Play Video
3:30 - 4:00Break
4:00 - 5:00Joint talk: James Bergstra (Harvard), Clement Farabet (NYU)

Wednesday, July 11, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Learning Hierarchies of Invariant Features (Parts 1 & 2)"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction (Part 3)"

Play Video
11:30 - 12:00Break
12:00 - 1:00Joint talk: James Bergstra (Harvard), Clement Farabet (NYU)
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"PART 3: Some applications of deep learning (Slides 1-38)"
Presentation (PDF File)
Play Video
3:30 - 4:00Break
4:00 - 5:00
"PART 4: A computational principle that explains sex, the brain, and sparse coding (Slides 39-92)"
Presentation (PDF File)
Play Video

Thursday, July 12, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Deep Learning Methods for Vision"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Deep Learning Methods for Vision (Part 2)"

Play Video
11:30 - 12:00Break
12:00 - 1:00
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Part 1"

Play Video
3:30 - 4:00Break
4:00 - 5:00Joint talk: James Bergstra (Harvard), Clement Farabet (NYU)

Friday, July 13, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
10:00 - 10:30Break
10:30 - 11:30
11:30 - 12:00Break
12:00 - 1:00
"Part 2"

Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Part 3"
Play Video
3:30 - 4:00Break
4:00 - 5:00
"Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction (Part 4)"

Play Video

Monday, July 16, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Part 1"
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Part 2"

Play Video
11:30 - 12:00Break
12:00 - 1:00
"Some Relevant Topics in Optimization (Part 1) - (Slides Cover Parts 1 & 2)"
Presentation (PDF File)
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Some Relevant Topics in Optimization (Part 2)"
Play Video
3:30 - 4:00Break
4:00 - 5:00
"A tutorial on sparse modeling."
Presentation (PDF File)
Play Video
5:00 - 6:30Reception (Hosted by IPAM)

Tuesday, July 17, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Sparse and Regularized Optimization Part 1 (Slides Cover Parts 1 & 2)"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Sparse and Regularized Optimization Part 2"
Presentation (PDF File)
Play Video
11:30 - 12:00Break
12:00 - 1:00
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Part 3"

Play Video
3:30 - 4:00Break
4:00 - 5:00
"Part 4"

Play Video

Wednesday, July 18, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Scattering Invariant Deep Networks for Classification "
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Scattering Invariant Deep Networks for Classification (Part 2)"

Play Video
11:30 - 12:00Break
12:00 - 1:00
"Part 1"
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Part 2"

Play Video
3:30 - 4:00Break
4:00 - 5:00
"Tutorial on Optimization methods for machine learning"
Presentation (PDF File)
Play Video

Thursday, July 19, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Tutorial on Optimization methods for machine learning (Part 2)"

Play Video
10:00 - 10:30Break
10:30 - 11:30
"Tutorial on Optimization methods for machine learning (Part 3)"

Play Video
11:30 - 2:00Lunch (on your own)

Afternoon Session

2:00 - 3:30
"Scattering Invariant Deep Networks for Classification (Part 3)"

Play Video
3:30 - 4:00Break
4:00 - 5:00
"An Algebraic Perspective on Deep Learning"
Presentation (PDF File)
Play Video

Friday, July 20, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"An Algebraic Perspective on Deep Learning (Part 2)"

Play Video
10:00 - 10:30Break
10:30 - 11:30
"An Algebraic Perspective on Deep Learning (Part 3)"

Play Video
11:30 - 12:00Break
12:00 - 1:00
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
3:30 - 4:00Break
4:00 - 5:00

Monday, July 23, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
10:00 - 10:30Break
10:30 - 11:30
11:30 - 12:00Break
12:00 - 1:00
"Deep Gated MRF's - part 1"
Presentation (PDF File)
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Deep Gated MRF's - part 2"
Presentation (PDF File)
Play Video
3:30 - 4:00Break
4:00 - 5:00
"Part 1"
Play Video
5:00 - 6:30Reception (Hosted by IPAM)
6:30 - 7:30

Tuesday, July 24, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Part 2"

Play Video
10:00 - 10:30Break
10:30 - 11:30
"Part 3"

Play Video
11:30 - 12:00Break
12:00 - 1:00
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"From natural scene statistics to models of neural coding and representation (part 1)"
Presentation (PDF File)
Play Video
3:30 - 4:00Break
4:00 - 5:00
"Large Scale Deep Learning"
Presentation (PDF File)
Play Video

Wednesday, July 25, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Deep learning in the visual cortex - Part 1"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Deep learning in the visual cortex - Part 2"
Presentation (PDF File)
Play Video
11:30 - 12:00Break
12:00 - 1:00
"Multiview Feature Learning - Part 1"
Presentation (PDF File)
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Multiview Feature Learning - Part 2"
Presentation (PDF File)
Play Video
3:30 - 4:00Break
4:00 - 5:00
"From natural scene statistics to models of neural coding and representation (part 2)"
Presentation (PDF File)
Play Video

Thursday, July 26, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"Introduction to MCMC for deep learning"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
11:30 - 12:00Break
12:00 - 1:00
"Part 1"
Play Video
1:00 - 2:30Lunch (on your own)

Afternoon Session

2:30 - 3:30
"Part 2"

Play Video
3:30 - 4:00Break
4:00 - 5:00
"Deep learning in the visual cortex - Part 3"
Presentation (PDF File)
Play Video

Friday, July 27, 2012

Morning Session

8:00 - 9:00Continental Breakfast
9:00 - 10:00
"An Informal Mathematical Tour of Feature Learning"
Presentation (PDF File)
Play Video
10:00 - 10:30Break
10:30 - 11:30
"Part 3"

Play Video
12:00 - 1:30Lunch (on your own)

Afternoon Session

1:30 - 2:30Panel Discussion: Nando de Freitas, Iain Murray, Bruno Olshausen, Ruslan Salakhutdinov, Roland Memisevic
2:30 - 3:00Closing Remarks by Russ Caflisch (IPAM Director)



Join the CompressiveSensing subreddit or the Google+ Community and post there !
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.

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