Mostly here to share pretty maths/3D prints, sometimes sharing my research
We looked at the design of optimal fixed-point algorithms.
That is, seeking to approximately solve T(y)=y using as few evaluations of the operator T() as possible. Maximally efficient methods are "minimax optimal" 1/
We looked at the design of optimal fixed-point algorithms.
That is, seeking to approximately solve T(y)=y using as few evaluations of the operator T() as possible. Maximally efficient methods are "minimax optimal" 1/
Alas, the classic model of minimax optimal methods is overly conservative; it overfits to tune its worst-case.
We found a path forward 1/
Alas, the classic model of minimax optimal methods is overly conservative; it overfits to tune its worst-case.
We found a path forward 1/
We do away with ad hoc, characterizing optimal smoothings for convex cones and sublinear functions
We do away with ad hoc, characterizing optimal smoothings for convex cones and sublinear functions
This thread gives the puzzle, solution, and a 3D printed demo :)
This thread gives the puzzle, solution, and a 3D printed demo :)
Suppose you're a mathematical sailor at sea on a boat that has a perfectly cylindrical hole in the floor. All you brought is a collection of every p norm ball except p=2 (drat!). What do you do to cork the hole and save yourself?
Suppose you're a mathematical sailor at sea on a boat that has a perfectly cylindrical hole in the floor. All you brought is a collection of every p norm ball except p=2 (drat!). What do you do to cork the hole and save yourself?
youtu.be/K_dhTP2I2uo?...
"Near-Linear Runtime for a Classical Matrix Preconditioning Algorithm"
- Jason Altschuler
youtu.be/K_dhTP2I2uo?...
"Near-Linear Runtime for a Classical Matrix Preconditioning Algorithm"
- Jason Altschuler
www.youtube.com/watch?v=QNfq...
www.youtube.com/watch?v=QNfq...
Will share a link to the talk on YouTube after
Will share a link to the talk on YouTube after
www.quantamagazine.org/risky-giant-...
www.quantamagazine.org/risky-giant-...
Rockafellar+Wets's thick textbook is included for reference.
Rockafellar+Wets's thick textbook is included for reference.
We consider first-order methods for a ridiculously general model: minimizing a convex composition of functions g_j(x) that vary heterogeneously in whether they are smooth, nonsmooth, convex, strongly convex or anything in between.
We consider first-order methods for a ridiculously general model: minimizing a convex composition of functions g_j(x) that vary heterogeneously in whether they are smooth, nonsmooth, convex, strongly convex or anything in between.
Happy to chat!
academicjobsonline.org/ajo/jobs/29529
Happy to chat!
academicjobsonline.org/ajo/jobs/29529
I had the privilege to speak in the OPT-ML Workshop: neurips.cc/virtual/2024...
My talk presents a solution to the ''minimization game'' for smooth convex problems (ie a subgame perfect method that optimally adapts to any gradients seen)
I had the privilege to speak in the OPT-ML Workshop: neurips.cc/virtual/2024...
My talk presents a solution to the ''minimization game'' for smooth convex problems (ie a subgame perfect method that optimally adapts to any gradients seen)
She gives a novel primal-dual way to understand the classic (primal) subgradient method
Check it out: arxiv.org/abs/2305.17323
She gives a novel primal-dual way to understand the classic (primal) subgradient method
Check it out: arxiv.org/abs/2305.17323
Their unit balls are all Catalan solids (every face is the same). So the dual balls are all Archimedean solids (every corner is the same)
www.ams.jhu.edu/~grimmer/OWL...
Files to make your own: www.printables.com/model/113805...
Their unit balls are all Catalan solids (every face is the same). So the dual balls are all Archimedean solids (every corner is the same)
www.ams.jhu.edu/~grimmer/OWL...
Files to make your own: www.printables.com/model/113805...
First link gives some exposition on how this binary slide rule works.
Second link gives the design files if you want one. Many libraries have 3D printers to make this for you nowadays
www.ams.jhu.edu/~grimmer/Sli...
www.printables.com/model/113795...
First link gives some exposition on how this binary slide rule works.
Second link gives the design files if you want one. Many libraries have 3D printers to make this for you nowadays
www.ams.jhu.edu/~grimmer/Sli...
www.printables.com/model/113795...
I'm mass producing binary slide rules to give students on day one of my "Intro to Computational Math" this Spring :)
I'm mass producing binary slide rules to give students on day one of my "Intro to Computational Math" this Spring :)
We give unified analysis for variance-reduced prox-linear methods, identifying a neat Pareto frontier of state-of-the-art methods. Check it out:
arxiv.org/abs/2412.15008
We give unified analysis for variance-reduced prox-linear methods, identifying a neat Pareto frontier of state-of-the-art methods. Check it out:
arxiv.org/abs/2412.15008
I'll be giving a plenary at the OPT-ML workshop on optimizing GD steps and subgame perfect methods, all developed with Alex L Wang and Kevin Shu
I'll be giving a plenary at the OPT-ML workshop on optimizing GD steps and subgame perfect methods, all developed with Alex L Wang and Kevin Shu