[CMU AI Seminar] Feb 22 at 12pm (Zoom) -- Gaurav Manek (CMU) -- Hough and Cover: 2D Bin Packing with Classic Computer Vision Techniques -- AI Seminar sponsored by Morgan Stanley

[Asher Trockman]

Hi all,

The seminar today by Gaurav Manek on the use of computer vision techniques
to solve bin packing problems is happening right now!

In case you are interested:
https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09

Thanks,
Asher

On Mon, Feb 21, 2022 at 4:40 PM Asher Trockman <ashert at cs.cmu.edu> wrote:

> Dear all,
>
> We look forward to seeing you *tomorrow,* *this Tuesday (2/22)* from *1**2:00-1:00
> PM (U.S. Eastern time)* for the next talk of our *CMU AI seminar*,
> sponsored by Morgan Stanley
> <https://www.morganstanley.com/about-us/technology/>.
>
> To learn more about the seminar series or see the future schedule, please
> visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.
>
> Tomorrow (2/22), *Gaurav Manek *(CMU) will be giving a talk titled *"**Hough
> and Cover: 2D Bin Packing with Classic Computer Vision Techniques**".*
>
> *Title*: Hough and Cover: 2D Bin Packing with Classic Computer Vision
> Techniques
>
> *Talk Abstract*: Classic computer vision has, unfortunately, fallen by
> the wayside in favor of neural networks. In this talk I introduce a novel
> use-case for some such techniques, applying them to 2D bin-packing. The 2D
> bin packing problem is a classic NP-hard optimization problem in which a
> number of rectangles need to be packed into a minimal number of larger
> rectangular bins. I present Hough and Cover, a technique that leverages
> transformations found in classic computer vision to greatly reduce the
> number of constraints of a novel integer linear programming (ILP)
> formulation. This approach is evaluated on classic datasets against a
> state-of-the-art ILP approach, where it achieves a speed-up of 5x in many
> cases. This problem has many industrial applications such as wood or glass
> industries, sheet metal fabrication, and even in scheduling heterogeneous
> resources. Solving this optimization problem optimally is important since
> it can save money, human resources, and time.
> *Presented in Partial Fulfillment of the CSD Speaking Skills Requirement.*
>
> *Speaker Bio*: Gaurav Manek is a PhD student at Carnegie Mellon
> University, advised by Zico Kolter. Gaurav's research centers around
> novel ways to learn dynamics models and value functions for reinforcement
> learning and similar applications, and to understand the subtle mechanisms
> at work when these models fail. His interests stretch from theoretical
> contributions to industry-facing applications. His personal website is at
> https://www.gauravmanek.com/.
>
> *Zoom Link*:
> https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09
>
> Thanks,
> Asher Trockman
>
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