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Tobias J. Oechtering

8 accepted papers

2025

An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces

ICASSP 2025accepted

This paper studies the Bayesian regret of the Thompson Sampling algorithm for bandit problems, building on the information-theoretic framework introduced by Russo and Van Roy [1]. Specifically, it extends the rate-distortion analysis of Dong and Van Roy [2], which provides near-optimal bounds for li…

Cited by 0SourceScholar
2025

Enhancing Network Calibration for Low-Cost Gas Sensor Networks Through Adaptive Similarity Search

ICASSP 2025accepted

IoT-based low-cost gas sensors networks are important for environmental monitoring, but their regular calibrations are needed to achieve acceptable sensing performance. A critical step in network calibration is identifying when sensors within the network are sensing the same phenomenon, which is ess…

Cited by 0SourceScholar
2025

Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality

ICASSP 2025accepted

We study agents acting in an unknown environment where the agent’s goal is to find a robust policy. We consider robust policies as policies that achieve high cumulative rewards for all possible environments. To this end, we consider agents minimizing the maximum regret over different environment par…

Cited by 0SourceScholar
2022

Private Learning Via Knowledge Transfer with High-Dimensional Targets

ICASSP 2022accepted

Preventing unintentional leakage of information about the training set has high relevance for many machine learning tasks, such as medical image segmentation. While differential privacy (DP) offers mathematically rigorous protection, the high output dimensionality of segmentation tasks prevents the…

Cited by 0SourceScholar
2020

On Design of Optimal Smart Meter Privacy Control Strategy Against Adversarial Map Detection

ICASSP 2020accepted

We study the optimal control problem of the maximum a posteriori (MAP) state sequence detection of an adversary using smart meter data. The privacy leakage is measured using the Bayesian risk and the privacy-enhancing control is achieved in real-time using an energy storage system. The control strat…

Cited by 0SourceScholar
2017

Optimal transmit strategy for MIMO channels with joint sum and per-antenna power constraints

ICASSP 2017accepted

This paper studies optimal transmit strategies for multiple-input multiple-output (MIMO) Gaussian channels with joint sum and per-antenna power constraints. It is shown that if an unconstraint optimal allocation for an antenna exceeds a per-antenna power constraint, then the maximal power for this a…

Cited by 0SourceScholar