This paper focuses on optimal unimodal transformation of the score outpu...
We investigate the nonlinear regression problem under L2 loss (square lo...
This study presents an effective global optimization technique designed ...
Our study focuses on determining the best weight windows for a weighted
...
Our research deals with the optimization version of the set partition
pr...
We study the adversarial online learning problem and create a completely...
In this work, we propose a meta algorithm that can solve a multivariate
...
We investigate an auto-regressive formulation for the problem of smoothi...
In this work, we propose an efficient minimax optimal global optimizatio...
We study the sequential calibration of estimations in a quantized isoton...
We propose a decomposition method for the spectral peaks in an observed
...
We study the problem of expert advice under partial bandit feedback sett...
We propose a multi-tone decomposition algorithm that can find the
freque...
We propose a new tournament structure that combines the popular knockout...
We propose a nearest neighbor based clustering algorithm that results in...
We study the problem of multiway number partition optimization, which ha...
We investigate the optimal selection of weight windows for the problem o...
We propose an extended generalization of the pseudo Huber loss formulati...
In this work, we propose a computationally efficient algorithm for the
p...
We investigate the calibration of estimations to increase performance wi...
We investigate the problem of online learning, which has gained signific...
We study the adversarial multi-armed bandit problem and create a complet...
We study the optimization version of the equal cardinality set partition...
We study the optimization version of the set partition problem (where th...
In this paper, we propose a nonparametric approach that can be used in
e...
We propose a generalized formulation of the Huber loss. We show that wit...
In this work, we study the problem of global optimization in univariate ...
In this work, we aim to calibrate the score outputs of an estimator for ...
We investigate the problem of online learning, which has gained signific...
Sequential learning systems are used in a wide variety of problems from
...
In this work, we aim to create a completely online algorithmic framework...
We investigate the adversarial bandit problem with multiple plays under
...
We study the min-max optimization problem where each function contributi...
In this paper, we address the scheduling problem in wireless ad hoc netw...