Before the expiration window passes, here are few more short takes from Allerton… for some talks I couldn’t take notes because I didn’t get a seat or I missed half the talk shuttling between sessions.

**The Gaussian Channel with Noisy Feedback: Near-Capacity Performance Via Simple Interaction**

*Assaf Ben-Yishai, Ofer Shayevitz*

This was a really nice talk by Ofer on trying to get practical codes for AWGN channels with noisy feedback by using the intuition given by the Schalkwijk-Kailath scheme plus some tricks from using the mod operation. This is reminiscent of lattices (which may be an interesting future direction). The SK scheme has a problem with noise accumulation, which they deal with using these mode operations, and can get to errors around 10^(-6) with around 19 rounds, or blocklength 19 at reasonable SNRs. Blocklength is misleading here since there is feedback every symbol. The other catch is that the feedback link must have much higher SNR than the forward link, but this is true in applications such as sensing, where the receiver may be plugged into the wall, but the transmitter may be on a swallowable medical monitoring device.

**Point-To-Point Codes for Interference Channels: A Journey Toward High Performance at Low Complexity**

*Young-Han Kim*

Continuing with my UCSD bias, I also wanted to mention Young-Han’s talk, which was on using COTS (commercial, off-the-shelf) coding schemes on the interference channel (in particular, the 2 user IC). He talked about rate splitting approaches and block Markov schemes. Much of this work is with Lele Wang, who may be graduating soon…

**Signal Detection on Graphs**

*Venkatesh Saligrama*

This was a hypothesis testing problem where the observations come from nodes on graph. Under the null, they are Gaussian noise, and under the other hypothesis, there is a connected subgraph with an elevated mean. How should we do detection in this scenario? This is a compound hypothesis testing problem because there are (too) many possible connected subgraphs to consider. He gets around this by looking at a convex program parameterized by a measure of the size/shape of the connected component. This is where my notes get messy though, so you might want to look at the paper if it sounds interesting to you…

**Hypercontractivity in Hamming Space**

*Yury Polyanskiy*

I’ve hypercontractivity before, and Yury talked about his paper on ArXiV, which is about functions on the binary hypercube. This talk felt more like a tour of results on hypercontractivity and less like a “here is my new result” talk, which I actually appreciated because I felt it tied together ideas well and made me realize how strange the hypercontractivity parameter of an operator is.