33 citations · 54 across the 34 of their papers we have counts for
34 papers
Sequential Linearithmic Time Optimal Unimodal Fitting When Minimizing Univariate Linear Losses
Kaan Gokcesu, Hakan Gokcesu
This paper focuses on optimal unimodal transformation of the score outputs of a univariate learning model under linear loss functions. We demonstrate that the optimal mapping betwe…
A Note On Nonlinear Regression Under L2 Loss
Kaan Gokcesu, Hakan Gokcesu
We investigate the nonlinear regression problem under L2 loss (square loss) functions. Traditional nonlinear regression models often result in non-convex optimization problems with…
Efficient Lipschitzian Global Optimization of Hölder Continuous Multivariate Functions
Kaan Gokcesu, Hakan Gokcesu
This study presents an effective global optimization technique designed for multivariate functions that are Hölder continuous. Unlike traditional methods that construct lower bound…
Formulation of Weighted Average Smoothing as a Projection of the Origin onto a Convex Polytope
Kaan Gokcesu, Hakan Gokcesu
Our study focuses on determining the best weight windows for a weighted moving average smoother under squared loss. We show that there exists an optimal weight window that is symme…
A 2-opt Algorithm for Locally Optimal Set Partition Optimization
Kaan Gokcesu, Hakan Gokcesu
Our research deals with the optimization version of the set partition problem, where the objective is to minimize the absolute difference between the sums of the two disjoint parti…
Data Dependent Regret Guarantees Against General Comparators for Full or Bandit Feedback
Kaan Gokcesu, Hakan Gokcesu
We study the adversarial online learning problem and create a completely online algorithmic framework that has data dependent regret guarantees in both full expert feedback and ban…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Efficient, Anytime Algorithms for Calibration with Isotonic Regression under Strictly Convex Losses
Kaan Gokcesu, Hakan Gokcesu
We investigate the calibration of estimations to increase performance with an optimal monotone transform on the estimator outputs. We start by studying the traditional square error…
Near-Linear Time Algorithm with Near-Logarithmic Regret Per Switch for Mixable/Exp-Concave Losses
Kaan Gokcesu, Hakan Gokcesu
We investigate the problem of online learning, which has gained significant attention in recent years due to its applicability in a wide range of fields from machine learning to ga…
Generalized Translation and Scale Invariant Online Algorithm for Adversarial Multi-Armed Bandits
Kaan Gokcesu, Hakan Gokcesu
We study the adversarial multi-armed bandit problem and create a completely online algorithmic framework that is invariant under arbitrary translations and scales of the arm losses…
A Quadratic Time Locally Optimal Algorithm for NP-hard Equal Cardinality Partition Optimization
Kaan Gokcesu, Hakan Gokcesu
We study the optimization version of the equal cardinality set partition problem (where the absolute difference between the equal sized partitions' sums are minimized). While this…
Efficient Locally Optimal Number Set Partitioning for Scheduling, Allocation and Fair Selection
Kaan Gokcesu, Hakan Gokcesu
We study the optimization version of the set partition problem (where the difference between the partition sums are minimized), which has numerous applications in decision theory l…