JAX-Privacy: A library for differentially private machine learning Ryan McKenna, Galen Andrew, Borja Balle, Vadym Doroshenko, Arun Ganesh, Weiwei Kong, Alex Kurakin, Brendan McMahan, Mikhail Pravilov http://arxiv.org/abs/2602.17861

Cameron Seth is breaking down the world’s hardest CS problem piece by piece. “What I’m doing is looking at a series of smaller problems related to the broader P vs. NP problem. Essentially, what I’m asking is if we can solve these other related problems,” Cam says. uwaterloo.ca/news/mathema...

Spectral Perturbation Bounds for Low-Rank Approximation with Applications to Privacy Phuc Tran, Nisheeth K. Vishnoi, Van H. Vu http://arxiv.org/abs/2510.25670

A little-known algorithmic process called “differential privacy” helps keep census data anonymous. Conservatives want it gone.

Announcing (w @adamsmith.xyz @thejonullman.bsky.social) the 2025 edition of the Foundations of Responsible Computing Job Market Profiles! Check out 40 job market candidates in mathematical research in computation and society writ large! Link: drive.google.com/file/d/1zvsr...

150 years ago the first women were enrolled at University of Copenhagen. To celebrate, four of my awesome BARC colleagues are arranging the WAVE workshop on October 10th. Amazing speakers and panelists, full-day catering, and Copenhagen culture night in the evening! Join us! t.co/zIeUnYVXMC

Normalized Square Root: Sharper Matrix Factorization Bounds for Differentially Private Continual Counting Monika Henzinger, Nikita P. Kalinin, Jalaj Upadhyay http://arxiv.org/abs/2509.14334

📢Adam Smith, @gautamkamath.com, and I are putting together a list of job market candidates in Foundations of Responsible Computing! Last year's list was a great success so we're keeping it going! If you want to be included, or nominate someone, see link in the replies!

Differentially Private Synthetic Graphs Preserving Triangle-Motif Cuts Pan Peng, Hangyu Xu http://arxiv.org/abs/2507.14835

Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrović, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu http://arxiv.org/abs/2507.01873

On Design Principles for Private Adaptive Optimizers Arun Ganesh, Brendan McMahan, Abhradeep Thakurta http://arxiv.org/abs/2507.01129

ICML's election for their board of directors has begun. I've thrown my hat in the ring. Please consider voting for Gautam Kamath. I have experience with the governance of TMLR, COLT, and ALT, and I think I've demonstrated myself as a consciencious and engaged community member.

This year TCS for All Inspiration talk will be given by Sofya Raskhodnikova, Boston University on June 27th at our STOC 2025 TCS for All Meeting. Join us. We are relocating the TCS for All Rising Star Workshop to FOCS 2025 this year. Stay tuned. SIGACT.org/tcsforall/ #stoc2025 @ccanonne.github.io

Correlated Noise Mechanisms for Differentially Private Learning Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Arun Ganesh, Monika Henzinger, Jonathan Katz, Ryan McKenna, H. Brendan McMahan, Keith Rush, Thomas Steinke, Ab... http://arxiv.org/abs/2506.08201

DIMACS workshop on fine grained hardness of approximation, July 21-23 Information and registration here, looks interesting! dmac.rutgers.edu/events/detai...

Differentially Private Matchings Michael Dinitz, George Z. Li, Quanquan C. Liu, Felix Zhou http://arxiv.org/abs/2501.00926

Looking for a PhD position or a post-doc position in theoretical computer science? Consider applying to one of our calls, closing January 10! barc.ku.dk/career/

Happy new year! Guest post on my blog by Abhradeep Thakurta, featuring his perspective on interviewing/hiring for faculty and industry research positions in CS/ML. I add some of my own comments at the end. Comments and perspectives welcome! kamathematics.wordpress.com/2025/01/02/g...

Streaming Private Continual Counting via Binning Joel Daniel Andersson, Rasmus Pagh http://arxiv.org/abs/2412.07093

Another cool work by Joel Andersson and @rasmuspagh.net on low-space continual counting. This result is more general than that in the recent FOCS paper. arxiv.org/abs/2412.07093

If you are on the job market, and work on the kinds of topics that might be published in FORC ("Foundations of Responsible Computing"), fill out this form and get on the job list. This covers mathematical research on privacy, fairness, and related topics.