Conventional methods for query autocompletion aim to predict which compl...
This paper studies offline Imitation Learning (IL) where an agent learns...
This paper studies Imitation Learning from Observations alone (ILFO) whe...
Motivated by modern applications, such as online advertisement and
recom...
Most computer science conferences rely on paper bidding to assign review...
In offline reinforcement learning (RL), the goal is to learn a successfu...
There is a stark disparity between the step size schedules used in pract...
Momentum based stochastic gradient methods such as heavy ball (HB) and
N...
Given a matrix A∈R^n× d and a vector b
∈R^d, we show how to compute an ϵ...
For many applications, an ensemble of base classifiers is an effective
s...
This work provides a simplified proof of the statistical minimax optimal...
There is widespread sentiment that it is not possible to effectively uti...
This work characterizes the benefits of averaging techniques widely used...
We show that there is a largely unexplored class of functions (positive
...