activity
20092019
most citedMinimax Optimal Online Stochastic Learning for Sequences of Convex Functions under Sub-Gradient Observation Failures

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

math.OC2019

Accelerating Min-Max Optimization with Application to Minimal Bounding Sphere

Hakan Gokcesu, Kaan Gokcesu, Suleyman Serdar Kozat

We study the min-max optimization problem where each function contributing to the max operation is strongly-convex and smooth with bounded gradient in the search domain. By smoothi…

cs.LG20191 cited

Minimax Optimal Online Stochastic Learning for Sequences of Convex Functions under Sub-Gradient Observation Failures

Hakan Gokcesu, Suleyman S. Kozat

We study online convex optimization under stochastic sub-gradient observation faults, where we introduce adaptive algorithms with minimax optimal regret guarantees. We specifically…

cs.LG2012

A Deterministic Analysis of an Online Convex Mixture of Expert Algorithms

Mehmet A. Donmez, Sait Tunc, Suleyman S. Kozat

We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to model an unknown desired signal. This…

cs.IT2012

Robust Estimation in Rayleigh Fading Channels Under Bounded Channel Uncertainties

Mehmet A. Donmez, Huseyin A. Inan, Suleyman S. Kozat

We investigate channel equalization for Rayleigh fading channels under bounded channel uncertainties. We analyze three robust methods to estimate an unknown signal transmitted thro…

cs.IT2009

An Information Theoretic Analysis of Single Transceiver Passive RFID Networks

Yucel Altug, S. Serdar Kozat, M. Kivanc Mihcak

In this paper, we study single transceiver passive RFID networks by modeling the underlying physical system as a special cascade of a certain broadcast channel (BCC) and a multiple…