633 citations · 1.5k across the 68 of their papers we have counts for
5 papers · 1 filter
Mixing Times and Structural Inference for Bernoulli Autoregressive Processes
Dimitrios Katselis, Carolyn L. Beck, R. Srikant
We introduce a novel multivariate random process producing Bernoulli outputs per dimension, that can possibly formalize binary interactions in various graphical structures and can…
Optimal Heavy-Traffic Queue Length Scaling in an Incompletely Saturated Switch
Siva Theja Maguluri, Sai Kiran Burle, R. Srikant
We consider an input queued switch operating under the MaxWeight scheduling algorithm. This system is interesting to study because it is a model for Internet routers and data cente…
Why Deep Neural Networks for Function Approximation?
Shiyu Liang, R. Srikant
Recently there has been much interest in understanding why deep neural networks are preferred to shallow networks. We show that, for a large class of piecewise smooth functions, th…
On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression
Kobi Cohen, Angelia Nedic, R. Srikant
The problem of least squares regression of a -dimensional unknown parameter is considered. A stochastic gradient descent based algorithm with weighted iterate-averaging that use…
Double Thompson Sampling for Dueling Bandits
Huasen Wu, Xin Liu
In this paper, we propose a Double Thompson Sampling (D-TS) algorithm for dueling bandit problems. As indicated by its name, D-TS selects both the first and the second candidates a…