124 citations · 1.6k across the 112 of their papers we have counts for
8 papers · 1 filter
Spectral State Space Models
Naman Agarwal, Daniel Suo, Xinyi Chen +1
This paper studies sequence modeling for prediction tasks with long range dependencies. We propose a new formulation for state space models (SSMs) based on learning linear dynamica…
Playing Large Games with Oracles and AI Debate
Xinyi Chen, Angelica Chen, Dean Foster +1
We consider regret minimization in repeated games with a very large number of actions. Such games are inherent in the setting of AI Safety via Debate \cite{irving2018ai}, and more…
An Efficient Interior-Point Method for Online Convex Optimization
Elad Hazan, Nimrod Megiddo
A new algorithm for regret minimization in online convex optimization is described. The regret of the algorithm after time periods is - which is the minimu…
Online Learning for Obstacle Avoidance
David Snyder, Meghan Booker, Nathaniel Simon +4
We approach the fundamental problem of obstacle avoidance for robotic systems via the lens of online learning. In contrast to prior work that either assumes worst-case realizations…
Online Nonstochastic Model-Free Reinforcement Learning
Udaya Ghai, Arushi Gupta, Wenhan Xia +2
We investigate robust model-free reinforcement learning algorithms designed for environments that may be dynamic or even adversarial. Traditional state-based policies often struggl…
Optimal Rates for Bandit Nonstochastic Control
Y. Jennifer Sun, Stephen Newman, Elad Hazan
Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) control are foundational and extensively researched problems in optimal control. We investigate LQR and LQG pro…