2 citations · 3 across the 5 of their papers we have counts for
8 papers
LogosQ: A High-Performance and Type-Safe Quantum Computing Library in Rust
Shiwen An, Jiayi Wang, Konstantinos Slavakis
Developing robust and high performance quantum software is challenging due to the dynamic nature of existing Python-based frameworks, which often suffer from runtime errors and sca…
Kernel Regression of Multi-Way Data via Tensor Trains with Hadamard Overparametrization: The Dynamic Graph Flow Case
Duc Thien Nguyen, Konstantinos Slavakis, Eleftherios Kofidis +1
A regression-based framework for interpretable multi-way data imputation, termed Kernel Regression via Tensor Trains with Hadamard overparametrization (KReTTaH), is introduced. KRe…
Nonconvex Regularization for Feature Selection in Reinforcement Learning
Kyohei Suzuki, Konstantinos Slavakis
This work proposes an efficient batch algorithm for feature selection in reinforcement learning (RL) with theoretical convergence guarantees. To mitigate the estimation bias inhere…
Robust Invariant Representation Learning by Distribution Extrapolation
Kotaro Yoshida, Konstantinos Slavakis
Invariant risk minimization (IRM) aims to enable out-of-distribution (OOD) generalization in deep learning by learning invariant representations. As IRM poses an inherently challen…
Nonparametric Bellman Mappings for Value Iteration in Distributed Reinforcement Learning
Yuki Akiyama, Konstantinos Slavakis
This paper introduces novel Bellman mappings (B-Maps) for value iteration (VI) in distributed reinforcement learning (DRL), where agents are deployed over an undirected, connected…
Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation
Guang Lin, Duc Thien Nguyen, Zerui Tao +3
Deep neural networks are known to be vulnerable to well-designed adversarial attacks. Although numerous defense strategies have been proposed, many are tailored to the specific att…