391 citations · 881 across the 63 of their papers we have counts for
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Minimax Optimal Algorithms for Adversarial Bandit Problem with Multiple Plays
N. Mert Vural, Hakan Gokcesu, Kaan Gokcesu +1
We investigate the adversarial bandit problem with multiple plays under semi-bandit feedback. We introduce a highly efficient algorithm that asymptotically achieves the performance…
Stability of the Decoupled Extended Kalman Filter Learning Algorithm in LSTM-Based Online Learning
Nuri Mert Vural, Fatih Ilhan, Suleyman S. Kozat
We investigate the convergence and stability properties of the decoupled extended Kalman filter learning algorithm (DEKF) within the long-short term memory network (LSTM) based onl…
An Efficient and Effective Second-Order Training Algorithm for LSTM-based Adaptive Learning
N. Mert Vural, Salih Ergüt, Suleyman S. Kozat
We study adaptive (or online) nonlinear regression with Long-Short-Term-Memory (LSTM) based networks, i.e., LSTM-based adaptive learning. In this context, we introduce an efficient…
Universal Online Convex Optimization with Minimax Optimal Second-Order Dynamic Regret
Hakan Gokcesu, Suleyman S. Kozat
We introduce an online convex optimization algorithm which utilizes projected subgradient descent with optimal adaptive learning rates. Our method provides second-order minimax-opt…
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…
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…