33 citations · 54 across the 34 of their papers we have counts for
10 papers · 1 filter
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…
Nonparametric Extrema Analysis in Time Series for Envelope Extraction, Peak Detection and Clustering
Kaan Gokcesu, Hakan Gokcesu
In this paper, we propose a nonparametric approach that can be used in envelope extraction, peak-burst detection and clustering in time series. Our problem formalization results in…
Generalized Huber Loss for Robust Learning and its Efficient Minimization for a Robust Statistics
Kaan Gokcesu, Hakan Gokcesu
We propose a generalized formulation of the Huber loss. We show that with a suitable function of choice, specifically the log-exp transform; we can achieve a loss function which co…
Optimally Efficient Sequential Calibration of Binary Classifiers to Minimize Classification Error
Kaan Gokcesu, Hakan Gokcesu
In this work, we aim to calibrate the score outputs of an estimator for the binary classification problem by finding an 'optimal' mapping to class probabilities, where the 'optimal…
Optimal and Efficient Algorithms for General Mixable Losses against Switching Oracles
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…
Cumulative Regret Analysis of the Piyavskii--Shubert Algorithm and Its Variants for Global Optimization
Kaan Gokcesu, Hakan Gokcesu
We study the problem of global optimization, where we analyze the performance of the Piyavskii--Shubert algorithm and its variants. For any given time duration , instead of the…