6 citations · 11 across the 5 of their papers we have counts for
5 papers
Better Private Algorithms for Correlation Clustering
Daogao Liu
In machine learning, correlation clustering is an important problem whose goal is to partition the individuals into groups that correlate with their pairwise similarities as much a…
Multi-token Markov Game with Switching Costs
Jian Li, Daogao Liu
We study a general Markov game with metric switching costs: in each round, the player adaptively chooses one of several Markov chains to advance with the objective of minimizing th…
The Convergence Rate of SGD's Final Iterate: Analysis on Dimension Dependence
Daogao Liu, Zhou Lu
Stochastic Gradient Descent (SGD) is among the simplest and most popular methods in optimization. The convergence rate for SGD has been extensively studied and tight analyses have…
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan Kulkarni, Yin Tat Lee, Daogao Liu
We study the differentially private Empirical Risk Minimization (ERM) and Stochastic Convex Optimization (SCO) problems for non-smooth convex functions. We get a (nearly) optimal b…
Algorithms and Adaptivity Gaps for Stochastic -TSP
Haotian Jiang, Jian Li, Daogao Liu +1
Given a metric and a , the classic $\textsf{$k$-TSP}$ problem is to find a tour originating at the of minimum length that visits at lea…