Some thoughts on teaching signals and systems

I’m teaching Linear Systems and Signals[*] (ECE 345) this semester at Rutgers. The course overall has 260+ students, split between two sections: I am teaching one section. This is my second time teaching it: last year I co-taught with Vishal Patel (who has decamped to Hopkins), and this semester I am co-teaching with Sophocles Orfanidis. I inherited a bit of a weird course: this is a 3-unit junior-level class with an associated 1-unit lab (ECE 347). Previous editions of the course had no recitations, which boggled my mind, since the recitation was where I really learned the material when I took the course (6.003 at MIT, with Greg Wornell as my recitation instructor). How are you supposed to understand how to do all these transforms without seeing some examples?

So this year we have turned ECE 347 into a recitation and moved the coding/simulation part of the course into the homework assignments. Due to the vagaries of university bureaucracy, however, we still have to assign a separate grade for the recitation (née lab). Moreover, there are some students who took the class without the lab and now just need to take 347! It’s a real mess. Hopefully it’s just one year of transition but this is also the year ABET [**] is showing up so we’ll see how things go.

After surveying a wide variety of textbook options for the course, we decided to go with the brand-new and free book by Ulaby and Yagle, Signals and Systems: Theory and Applications [***]. I really have to commend them on doing a fantastic job and making the book free, which is significantly better than $247 for the same book I used literally 20 years ago when I took this course. Actually, we mainly used another book, whose title/author eludes me now, but it had a green slipcover and was more analog control-focused (perhaps since Munther Dahleh was teaching).

One major difference I noticed between textbooks was the order of topics. Assuming you want to do convolution, Laplace (L), Z, Fourier Series (FS), and Fourier Transforms (FT), you can do a sort of back and forth between continuous time (CT) and discrete time (DT):

CT convolution, DT convolution, CTFS, DTFS, CTFT, DTFT, Laplace, Z
CT convolution, DT convolution, Laplace, Z, CTFS, DTFS, CTFT, DTFT

or do all one and then the other

CT convolution, Laplace, CTFS, CTFT, DT convolution, Z, DTFS, DTFT
DT convolution, Z, DTFS, DTFT, CT convolution, Laplace, CTFS, CTFT

I like the alternating version because it emphasizes the parallels between CT and DT, so if you cover sampling at the end you can kind of tie things together. This tends to give students a bit of whiplash, so we are going for:

CT convolution, DT convolution, Laplace, Z, CTFS, CTFT, DTFS, DTFT

It’s all a bit of an experiment, but the thing I find with all textbooks is that they are never as modular as one might like. That’s good for a book but maybe not as good for a collection of curricular units, which in the end is what a S & S [****] class is. CNX is one type of alternative, or maybe something like the interactive book that my colleague Roy Yates dreams of.

I find myself questioning my own choices of ordering and how to present things in the midst of teaching — it’s tempting to experiment mid-stream but I have to tamp down the urges so that I don’t lose the class entirely.

 

[*] You can tell by the word ordering that it was a control theorist who must have named the course.

[**] Accreditation seems increasingly like a scam these days.

[***] You can tell by the word ordering where the sympathies of the authors lie.

[****] Hedging my bets here.

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CFP: PPML Workshop at NIPS 2018

Privacy Preserving Machine Learning

NIPS 2018 Workshop

Montreal, December 8, 2018

Description

This one day workshop focuses on privacy preserving techniques for training, inference, and disclosure in large scale data analysis, both in the distributed and centralized settings. We have observed increasing interest of the ML community in leveraging cryptographic techniques such as Multi-Party Computation (MPC) and Homomorphic Encryption (HE) for privacy preserving training and inference, as well as Differential Privacy (DP) for disclosure. Simultaneously, the systems security and cryptography community has proposed various secure frameworks for ML. We encourage both theory and application-oriented submissions exploring a range of approaches, including:

  • secure multi-party computation techniques for ML
  • homomorphic encryption techniques for ML
  • hardware-based approaches to privacy preserving ML
  • centralized and decentralized protocols for learning on encrypted data
  • differential privacy: theory, applications, and implementations
  • statistical notions of privacy including relaxations of differential privacy
  • empirical and theoretical comparisons between different notions of privacy
  • trade-offs between privacy and utility

We think it will be very valuable to have a forum to unify different perspectives and start a discussion about the relative merits of each approach. The workshop will also serve as a venue for networking people from different communities interested in this problem, and hopefully foster fruitful long-term collaboration.

Submission Instructions

Submissions in the form of extended abstracts must be at most 4 pages long (not including references) and adhere to the NIPS format. We do accept submissions of work recently published or currently under review. Submissions should be anonymized. The workshop will not have formal proceedings, but authors of accepted abstracts can choose to have a link to arxiv or a pdf published on the workshop webpage.

Program Committee

  • Pauline Anthonysamy (Google)
  • Borja de Balle Pigem (Amazon)
  • Keith Bonawitz (Google)
  • Emiliano de Cristofaro (University College London)
  • David Evans (University of Virginia)
  • Irene Giacomelli (Wisconsin University)
  • Nadin Kokciyan (King’s College London)
  • Kim Laine (Microsoft Research)
  • Payman Mohassel (Visa Research)
  • Catuscia Palamidessi (Ecole Polytechnique & INRIA)
  • Mijung Park (Max Planck Institute for Intelligent Systems)
  • Benjamin Rubinstein (University of Melbourne)
  • Anand Sarwate (Rutgers University)
  • Philipp Schoppmann (HU Berlin)
  • Nigel Smart (KU Leuven)
  • Carmela Troncoso (EPFL)
  • Pinar Yolum (Utrecht University)
  • Samee Zahur (University of Virginia)

Organizers

  • Adria Gascon (Alan Turing Institute & Edinburgh)
  • Niki Kilbertus (MPI for Intelligent Systems & Cambridge)
  • Olya Ohrimenko (Microsoft Research)
  • Mariana Raykova (Yale)
  • Adrian Weller (Alan Turing Institute & Cambridge)

Signal boost: vote in the ITSOC BoG Election!

The IEEE Information Theory Society election of Members to the Board of Governors is now open.

We hope you will take the time to exercise your vote and help choose the future direction of the society. Let’s increase last year’s voting percentage of 23.1% by voting today! Your vote counts!

VOTE NOW at https://eballot4.votenet.com/IEEE

You will need your IEEE Account username/password to access the ballot. For quick reference, your username is asarwate@ece.rutgers.edu. If you do not remember your password, you may retrieve it on the voter login page.

Voting must be completed no later than 6 September 2018. Any returns received after this date will not be counted. The online voting site will close at 4:00 pm Eastern Time.

If you have any questions about the IEEE Information Theory Society voting process, please contact
ieee-itvote@ieee.org or +1 732 562 3904.

Thank you for your participation in this election.

Alon Orlitsky,
Chair, Nominations and Appointments Committee

Linkage

This NSF report from the Office of the Inspector General has some really horrendous examples of data fabrication, plagiarism, and other misconduct by PIs and graduate fellowship (GRFP) recipients. It’s true that bad behavior taints the whole program: how good is the GRFP selection process if students like this get awards?

This article on Bhagat Singh Thind is fascinating. We need a modern Ghadar Party here. But this is so bizarre: “[o]ut of necessity and ingenuity, Thind, along with several dozen South Asians during the interwar decades reinvented themselves as itinerant spiritual teachers and metaphysical lecturers who would travel from city to city, giving lectures and holding private classes.”

A photo gallery by Lotfi Zadeh: some of these are really beautiful portraits. Also the variety! I remember not really understanding portraiture when I was younger but I think I “get it” a bit more now. Or at least why it’s interesting. There’s even a photo of Claude Shannon… from the email:

Prof. Lotfi Zadeh, who passed away in 2017, was an avid photographer who grew up in a multicultural environment, surrounded himself with a cosmopolitan crowd, and always kept his mind open to new ideas. In the 1960s and 70s, he enjoyed capturing the people around him in a series of black and white portraits. His burgeoning career gave him access to a number of artists, academics, and dignitaries who, along with his colleagues, friends, and family, proved a great source of inspiration for him.

THE SQUIRCLE IS SO FASCINATING!

I helped organize a workshop at IPAM on privacy and genomics. Videos (raw) are up now.

What’s new is old in ethics and conduct

(h/t to Stark Draper, Elza Erkip, Allie Fletcher, Tara Javidi, and Tsachy Weissman for sources)

The IEEE Information Theory Society Board of Governors voted to approve the following statement to be included on official society events and on the website:

IEEE members are committed to the highest standards of integrity, responsible behavior, and ethical and professional conduct. The IEEE Information Theory Society reaffirms its commitment to an environment free of discrimination and harassment as stated in the IEEE Code of Conduct, IEEE Code of Ethics, and IEEE Nondiscrimination Policy. In particular, as stated in the IEEE Code of Ethics and Code of Conduct, members of the society will not engage in harassment of any kind, including sexual harassment, or bullying behavior, nor discriminate against any person because of characteristics protected by law. In addition, society members will not retaliate against any IEEE member, employee or other person who reports an act of misconduct, or who reports any violation of the IEEE Code of Ethics or Code of Conduct.

I guess the lawyers had to have a go at it, but this is essentially repeating that the IEEE already had rules and so here, we’re reminding you about the rules. This statement is saying “the new rules are the old rules.” We probably need more explicit new rules, however. In particular, many conferences have more detailed codes of conduct (NeurohackWeek, RSA,
Usenix, APEC) that provide more detail about how the principles espoused in the text above are implemented. Often, these conferences have formal reporting procedures/policies and sanctions for violations: many IEEE conferences do not. The NSF is now requiring reporting on PIs who are “found to have committed sexual harassment” so incidents at conferences where the traveler is presenting NSF-sponsored should also be reported, it seems.

While the ACM’s rules suggest making reporting procedures, perhaps a template (borrowed from another academic community?) could just become part of the standard operating procedure for running an IEEE conference. Just have a member of the organizing committee in charge, similar to having a local arrangements chair, publicity chair, etc. However, given the power dynamics of academic communities, perhaps people would feel more comfortable reporting incidents to someone outside the community.

Relatedly, The Society also approved creating an Ad Hoc Committee on Diversity and Inclusion (I’m not on it) who have already done a ton of work on this and will find other ways to make the ITSOC (even) more open and welcoming.