Reads from the first half of 2009

Some reads from the first half of this year, in no particular order…

American Karma (Sunil Bhatia) — A qualitative study of a professional South Asian community in New England. Bhatia explores issues like how home/work are separated, how South Asian identity is maintained, and the stresses faced by these corporate employees. Of particular interest was how many would take accent reduction classes to move up the corporate ladder and the ways in which they would justify or apologize for their co-workers’ tokenization of them. There was also a lot about how the families interacted via their children with the school district. I thought it was a worthwhile read for people who are interested in South Asian American studies, but it might be a bit jargon-laden for some.

Funny You Don’t Look Like One (Drew Hayden Taylor) — This was a collection of essays by Ojibway writer Drew Hayden Taylor, collated from several different publications. I lacked context for a lot of what he talked about, such as Oka (warning, Wikipedia article is highly contested) and the Akwesasne cigarette “smuggling” debate. He is an engaging writer, and I enjoyed reading this book — it spurred me to read a bit more about the context, and that’s always a good thing.

The Karma of Brown Folk (Vijay Prashad) — Unlike Amardeep, I still think this book has a lot to offer South Asian Americans in terms of contextualizing the ties between India and the US diaspora and the ties that should exists between South Asians and other people of color in the US. Prashad paints a rather dire picture of things, but I think what is most lacking in South Asian youth is critical thinking, and this book does a good job of questioning the sociopolitical underpinnings of South Asian American culture, especially among the professional diaspora. Maybe it’s not a great book to teach from, and for sure it it biased, but it’s a groundbreaking work, I think. It has aged a bit (I last read it around when it came out), but I think it’s still valuable.

Making Money (Terry Pratchett) — This was a Discworld novel, this time sending up the banking industry. It was topical given the current crisis, and I found it entertaining in its formulaic way…

Steppin’ on a Rainbow (Kinky Friedman) — A sort of gonzo mystery novel set in Hawaii and full of schlock pulpy native stereotypes. Avoid.

Love Medicine (Louise Erdrich) — I really enjoyed this multi-generational novel about an extended Ojibwe family. It was a bit difficult to get into at first, but it definitely hooked me. What got me was how Erdrich gets under the complicated ways in which people show their love for each other and how inexplicable actions can make sense with the proper context…

Never Let Me Go (Kazuo Ishiguro) — This novel came highly recommended but I have to say that I wasn’t as enthralled with it. Ishiguro wrote an engrossing pseudo-dystopian narrative but the complacency of the narrator, rather than being harrowing, was simply disappointing. It did remind me a bit of some of the chapters in Cloud Atlas, but in the end I felt like the novel failed to make me care, somehow. Which is sad, because I really should care about these people. Maybe it’s more of a judgement on me…

Fifth Business (Roberton Davies) — This was also a recommendation, and I liked it, although not as much as R. Fifth Business is a memoir of a school teacher who grew up in a small town in Canada, fought through WWI and has the scars to show it. Although I did find the narrator a bit tiresome at times, I did like the form of a life-long bildungsroman.

The Ghost Brigades (John Scalzi) — This is a sequel to Old Man’s War and I didn’t like it as much as the original. Scalzi is often called the modern Heinlein, and like Heinlein, I found it a bit repetitive and was not too keen on its politics, such as they were.

Unruly Immigrants (Monisha Das Gupta) — This is a study of alternative social/political/economic movements within the South Asian American community. In particular, she looks at feminist, queer, and labor groups. She uses the phrases “place makers” to describe their activities versus the “place taker” actions that often characterize the majority South Asian community. I liked that turn of phrase. The book relies a lot on her own experiences with some of the groups as well as extensive interviews. One thing that pops out is the complexity of relations between South Asians from Asia and from the Caribbean and Africa, between different economic class groups when trying to organize domestic workers, and gender differences in labor and queer groups. It’s definitely worth reading for those who are interested in activism in the South Asian American community.


ISIT 2009 : talks part three

This is the penultimate post on papers I saw at ISIT 2009 that I thought were interesting and on which I took some notes. I think I’m getting lazier and lazier with the note taking — I went to lots more talks than these, but I’m only writing about a random subset.

Existence and Construction of Capacity-Achieving Network Codes for Distributed Storage
Yunnan Wu

This paper looked at the distributed storage problem using the framework of network coding that Alex has worked on. The basic idea is that you have a bunch of drives redundantly storing some information (say n drives and you can query any k to reconstruct the data). You want to make it so that if any drive fails, it can be replaced by a new drive so that the new drive doesn’t have to download too much data to maintain the “k out of n” property. The problem can be translated into a network code on an infinite graph. This paper talked about how to achieve the optimal tradeoff between the bandwidth needed to repair the code and the storage efficiency/redundancy. The key thing is that even though the network graph is infinite, the network code can be constructed over a field whose size only depends on the number of active disks. Schwartz-Zippel reared its head again in the proof…

Achievability Results for Statistical Learning under Communication Constraints
Maxim Raginsky

This talk was on how to learn a classifier when the data-label pairs (X_i, Y_i) must be compressed. Max talked about two different scenarios, one in which you can use R bits per pair, and the other in which only the labels Y_i must be sent. He defined a rate-distortion-like function where the generalization error the classifier played the role of the distortion. In the first case it’s easier for the encoder to learn the classifier itself and send the classifier over — this takes 0 bits per sample, asympotically, and incurs no extra generalization error. In the second case he uses a kind of Wyner-Ziv-like scheme which is a bit more involved. Compression is not a thing many machine learning folks think about, so I think there’s a lot of interesting stuff in this direction.

On Feedback in Network Source Coding
Mayank Bakshi, Michelle Effros

This paper was about how feedback can help in distributed source coding. In some lossless and lossy problems, feedback can strictly increase the rate region. Some of these problems took the form of “helper” scenarios where the decoder wants one of the sources but gets coded side information from another source. They show that this scenario holds more generally, and so feedback helps in general in network source coding.

Feedback Communication over Individual Channels
Power Adaptive Feedback Communication over an Additive Individual Noise Sequence Channel

Yuval Lomnitz, Meir Feder

These talks were near and dear to my heart since they dealt with coding over channels which are basically unknown. The basic idea is that you know only X^n and Y^n, the inputs and outputs of the channel. The trick is then to define a corresponding “achievable rate.” They define an empirical mutual information and show that it is asymptotically achievable under some circumstances. The scheme is based on random coding plus maximum mutual information (MMI) decoding. When feedback is present they can do some rateless coding. There’s a full version on ArXiV.

Upper Bounds to Error Probability with Feedback
Barış Nakiboğlu, Lizhong Zheng

Baris gave a nice talk on his approach to modifying the Gallager exponent bounds to the case when feedback is available. The encoder constantly adapts to force the decoder into a decision. The upper bound is based on a one-step/channel-use reduction to show an exponentially decaying error probability. One nice thing he mentioned is that at rates below capacity we can get a better error exponent by not using the capacity-achieving input distribution. Even though I read the paper and Barış explained it to me very patiently, I still don’t quite get what is going on here. That’s probably because I never really worked on error exponents…