6 citations · 6 across the 2 of their papers we have counts for
4 papers
Nearest Neighbor Search for Hyperbolic Embeddings
Xian Wu, Moses Charikar
Embedding into hyperbolic space is emerging as an effective representation technique for datasets that exhibit hierarchical structure. This development motivates the need for algor…
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
Guy Bresler, Prateek Jain, Dheeraj Nagaraj +2
We study the problem of least squares linear regression where the data-points are dependent and are sampled from a Markov chain. We establish sharp information theoretic minimax lo…
Local Density Estimation in High Dimensions
Xian Wu, Moses Charikar, Vishnu Natchu
An important question that arises in the study of high dimensional vector representations learned from data is: given a set of vectors and a query , estimate the n…
Near-Optimal Time and Sample Complexities for Solving Discounted Markov Decision Process with a Generative Model
Aaron Sidford, Mengdi Wang, Xian Wu +2
In this paper we consider the problem of computing an -optimal policy of a discounted Markov Decision Process (DMDP) provided we can only access its transition function through…