3 papers
cs.LG2026
Fixed Universal Transformers
Jingwen Liu, Alexandr Andoni, Daniel Hsu
We introduce \emph{universal transformers}: fixed transformers that can simulate any transformer in a given class via a suitable input embedding. Analogous to a universal Turing ma…
cs.LG2025
Fast attention mechanisms: a tale of parallelism
Jingwen Liu, Hantao Yu, Clayton Sanford +2
Transformers have the representational capacity to simulate Massively Parallel Computation (MPC) algorithms, but they suffer from quadratic time complexity, which severely limits t…
cs.LG2025
Group-wise oracle-efficient algorithms for online multi-group learning
Samuel Deng, Daniel Hsu, Jingwen Liu
We study the problem of online multi-group learning, a learning model in which an online learner must simultaneously achieve small prediction regret on a large collection of (possi…