We present an implementation of an online optimization algorithm for hit...
We study causal effect estimation from a mixture of observational and
in...
In many applications, learning systems are required to process continuou...
In this paper, we present a method for table tennis ball trajectory filt...
We consider adaptive decision-making problems where an agent optimizes a...
We consider the problem of minimizing a non-convex function over a smoot...
We exploit analogies between first-order algorithms for constrained
opti...
Recurrent neural networks are capable of learning the dynamics of an unk...
We analyze the convergence rates of stochastic gradient algorithms for s...
We introduce a class of first-order methods for smooth constrained
optim...
We analyze the convergence rate of various momentum-based optimization
a...
In addition to providing high-profile successes in computer vision and
n...
We present a dynamical system framework for understanding Nesterov's
acc...
In this work, a dynamic system is controlled by multiple sensor-actuator...