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20182023
most citedGeneralized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics

33 citations · 54 across the 34 of their papers we have counts for

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Showing 2022Show all

13 papers · 1 filter

math.OC2022

to : A Meta Algorithm for Multivariate Global Optimization via Univariate Optimizers

Kaan Gokcesu, Hakan Gokcesu

In this work, we propose a meta algorithm that can solve a multivariate global optimization problem using univariate global optimizers. Although the univariate global optimization…

cs.LG2022

An Auto-Regressive Formulation for Smoothing and Moving Mean with Exponentially Tapered Windows

Kaan Gokcesu, Hakan Gokcesu

We investigate an auto-regressive formulation for the problem of smoothing time-series by manipulating the inherent objective function of the traditional moving mean smoothers. Not…

cs.LG2022

Efficient Minimax Optimal Global Optimization of Lipschitz Continuous Multivariate Functions

Kaan Gokcesu, Hakan Gokcesu

In this work, we propose an efficient minimax optimal global optimization algorithm for multivariate Lipschitz continuous functions. To evaluate the performance of our approach, we…

cs.LG2022

A Log-Linear Time Sequential Optimal Calibration Algorithm for Quantized Isotonic L2 Regression

Kaan Gokcesu, Hakan Gokcesu

We study the sequential calibration of estimations in a quantized isotonic L2 regression setting. We start by showing that the optimal calibrated quantized estimations can be acqui…

eess.SP2022

Robust, Nonparametric, Efficient Decomposition of Spectral Peaks under Distortion and Interference

Kaan Gokcesu, Hakan Gokcesu

We propose a decomposition method for the spectral peaks in an observed frequency spectrum, which is efficiently acquired by utilizing the Fast Fourier Transform. In contrast to th…

cs.LG2022

Second Order Regret Bounds Against Generalized Expert Sequences under Partial Bandit Feedback

Kaan Gokcesu, Hakan Gokcesu

We study the problem of expert advice under partial bandit feedback setting and create a sequential minimax optimal algorithm. Our algorithm works with a more general partial monit…

eess.SP2022

Blind Source Separation for Mixture of Sinusoids with Near-Linear Computational Complexity

Kaan Gokcesu, Hakan Gokcesu

We propose a multi-tone decomposition algorithm that can find the frequencies, amplitudes and phases of the fundamental sinusoids in a noisy observation sequence. Under independent…

cs.GT2022★ 1 cited

Merging Knockout and Round-Robin Tournaments: A Flexible Linear Elimination Tournament Design

Kaan Gokcesu, Hakan Gokcesu

We propose a new tournament structure that combines the popular knockout tournaments and the round-robin tournaments. As opposed to the extremes of divisive elimination and no elim…

cs.DS2022

Natural Hierarchical Cluster Analysis by Nearest Neighbors with Near-Linear Time Complexity

Kaan Gokcesu, Hakan Gokcesu

We propose a nearest neighbor based clustering algorithm that results in a naturally defined hierarchy of clusters. In contrast to the agglomerative and divisive hierarchical clust…

cs.DS2022

A Linearithmic Time Locally Optimal Algorithm for the Multiway Number Partition Optimization

Kaan Gokcesu, Hakan Gokcesu

We study the problem of multiway number partition optimization, which has a myriad of applications in the decision, learning and optimization literature. Even though the original m…

stat.ML2022★ 1 cited

Smoothing with the Best Rectangle Window is Optimal for All Tapered Rectangle Windows

Kaan Gokcesu, Hakan Gokcesu

We investigate the optimal selection of weight windows for the problem of weighted least squares. We show that weight windows should be symmetric around its center, which is also i…

stat.ML2022

Nonconvex Extension of Generalized Huber Loss for Robust Learning and Pseudo-Mode Statistics

Kaan Gokcesu, Hakan Gokcesu

We propose an extended generalization of the pseudo Huber loss formulation. We show that using the log-exp transform together with the logistic function, we can create a loss which…

cs.LG2022

Low Regret Binary Sampling Method for Efficient Global Optimization of Univariate Functions

Kaan Gokcesu, Hakan Gokcesu

In this work, we propose a computationally efficient algorithm for the problem of global optimization in univariate loss functions. For the performance evaluation, we study the cum…