10 citations · 21 across the 8 of their papers we have counts for
19 papers
An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen, Johann Demetrio Gaebler, Matt Peng +2
Value iteration is a well-known method of solving Markov Decision Processes (MDPs) that is simple to implement and boasts strong theoretical convergence guarantees. However, the co…
Distributed stochastic optimization with large delays
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos +2
One of the most widely used methods for solving large-scale stochastic optimization problems is distributed asynchronous stochastic gradient descent (DASGD), a family of algorithms…
Fisher Markets with Linear Constraints: Equilibrium Properties and Efficient Distributed Algorithms
Devansh Jalota, Marco Pavone, Qi Qi +1
The Fisher market is one of the most fundamental models for resource allocation problems in economic theory, wherein agents spend a budget of currency to buy goods that maximize th…
The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
In this paper, we study the bandits with knapsacks (BwK) problem and develop a primal-dual based algorithm that achieves a problem-dependent logarithmic regret bound. The BwK probl…
Distributionally Robust Local Non-parametric Conditional Estimation
Viet Anh Nguyen, Fan Zhang, Jose Blanchet +2
Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications in engineering, social…
A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions
Masoud Badiei Khuzani, Yinyu Ye, Sandy Napel +1
We develop and analyze a projected particle Langevin optimization method to learn the distribution in the Schönberg integral representation of the radial basis functions from train…