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Efficient random number generation techniques for CMOS single-photon avalanche diode array exploiting fast time tagging units

Related publications (31)

Evaluating, Exploiting, and Hiding Power Side-Channel Leakage of Remote FPGAs

The pervasive adoption of field-programmable gate arrays (FPGAs) in both cyber-physical systems and the cloud has raised many security issues. Being integrated circuits, FPGAs are susceptible to fault and power side-channel attacks, which require physical ...

EPFL2023

Learning With Your PETS

Drazen Dujic, Andrea Cervone, Jules Christian Georges Macé, Max Dupont, Renan Pillon Barcelos

Recently, we published an article [1] presenting how the Power Electronics course at the bachelor level is organized by the Power Electronics Laboratory and taught at Ecole Polytechnique Fédérale de Lausanne, EPFL, Switzerland. For those avid readers who m ...

2023

A Visionary Look at the Security of Reconfigurable Cloud Computing

Francesco Regazzoni, Mirjana Stojilovic

Field-programmable gate arrays (FPGAs) have become critical components in many cloud computing platforms. These devices possess the fine-grained parallelism and specialization needed to accelerate applications ranging from machine learning to networking an ...

2023

Resource aware pricing for electric vehicle charging

Nils Gustav Nilsson

Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set b ...

PERGAMON-ELSEVIER SCIENCE LTD2023

STREAMING TENSOR TRAIN APPROXIMATION

Daniel Kressner

Tensor trains are a versatile tool to compress and work with high-dimensional data and functions. In this work we introduce the streaming tensor train approximation (STTA), a new class of algorithms for approximating a given tensor ' in the tensor train fo ...

Siam Publications2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Carmela González Troncoso, Bogdan Kulynych

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Guilherme Migliato Marega

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

EPFL2023

Exploration-based model learning with self-attention for risk-sensitive robot control

Sudong Lee

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

2023

Unraveling the Electrochemical Electrode Coupling in Integrated Organic Electrochemical Transistors

Matteo Cucchi, Hsin Tseng

Organic electrochemical transistors (OECTs) have gained enormous attention due to their potential for bioelectronics and neuromorphic computing. However, their implementation into real-world applications is still impeded by a lack of understanding of the c ...

WILEY-V C H VERLAG GMBH2023

Efficient random number generation techniques for CMOS single-photon avalanche diode array exploiting fast time tagging units

Evaluating, Exploiting, and Hiding Power Side-Channel Leakage of Remote FPGAs

Learning With Your PETS

A Visionary Look at the Security of Reconfigurable Cloud Computing

Resource aware pricing for electric vehicle charging

STREAMING TENSOR TRAIN APPROXIMATION

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Exploration-based model learning with self-attention for risk-sensitive robot control

Unraveling the Electrochemical Electrode Coupling in Integrated Organic Electrochemical Transistors

Graph Chatbot

Evaluating, Exploiting, and Hiding Power Side-Channel Leakage of Remote FPGAs

Learning With Your PETS

A Visionary Look at the Security of Reconfigurable Cloud Computing

New ultrahigh-speed device concepts: from THz nanoplasma devices to glass-like electronics for neuromorphic computation

Resource aware pricing for electric vehicle charging

STREAMING TENSOR TRAIN APPROXIMATION

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Exploration-based model learning with self-attention for risk-sensitive robot control

Unraveling the Electrochemical Electrode Coupling in Integrated Organic Electrochemical Transistors

New ultrahigh-speed device concepts: from THz nanoplasma devices to glass-like electronics for neuromorphic computation