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We introduce transductive program synthesis, a new formulation of the program synthesis task that explicitly leverages test inputs during synthesis. While prior approaches to program synthesis--whether based on natural language descriptions…

Artificial Intelligence · Computer Science 2025-10-22 Kang-il Lee , Jahyun Koo , Seunghyun Yoon , Minbeom Kim , Hyukhun Koh , Dongryeol Lee , Kyomin Jung

With the outsourcing of design flow, ensuring the security and trustworthiness of integrated circuits has become more challenging. Among the security threats, IC counterfeiting and recycled ICs have received a lot of attention due to their…

Cryptography and Security · Computer Science 2020-10-27 Ashkan Vakil , Farzad Niknia , Ali Mirzaeian , Avesta Sasan , Naghmeh Karimi

In this paper, we study CPU utilization time patterns of several Map-Reduce applications. After extracting running patterns of several applications, the patterns with their statistical information are saved in a reference database to be…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-01-30 Nikzad Babaii Rizvandi , Javid Taheri , Albert Y. Zomaya , Reza Moraveji

Timing information leakage occurs whenever an attacker successfully deduces confidential internal information by observing some timed information such as events with timestamps. Timed automata are an extension of finite-state automata with…

Logic in Computer Science · Computer Science 2023-11-01 Étienne André , Engel Lefaucheux , Didier Lime , Dylan Marinho , Jun Sun

Continual learning on edge platforms remains challenging because recurrent networks depend on energy-intensive training procedures and frequent data movement that are impractical for embedded deployments. This work introduces M2RU, a…

Machine Learning · Computer Science 2025-12-29 Abdullah M. Zyarah , Dhireesha Kudithipudi

Recent studies have shown that the choice of activation function can significantly affect the performance of deep learning networks. However, the benefits of novel activation functions have been inconsistent and task dependent, and…

Machine Learning · Computer Science 2022-01-25 Garrett Bingham , Risto Miikkulainen

Information Flow Control (IFC) is a collection of techniques for ensuring a no-write-down no-read-up style security policy known as noninterference. Traditional methods for both static and dynamic IFC suffer from untenable numbers of false…

Cryptography and Security · Computer Science 2020-05-27 Maximilian Algehed , Cormac Flanagan

Inexact methods for model predictive control (MPC), such as real-time iterative schemes or time-distributed optimization, alleviate the computational burden of exact MPC by providing suboptimal solutions. While the asymptotic stability of…

Systems and Control · Electrical Eng. & Systems 2023-11-21 Aren Karapetyan , Efe C. Balta , Andrea Iannelli , John Lygeros

Increased connectivity and remote reprogrammability/reconfigurability features of embedded devices in current-day power systems (including interconnections between information technology -- IT -- and operational technology -- OT --…

Systems and Control · Electrical Eng. & Systems 2024-06-19 Prashanth Krishnamurthy , Ali Rasteh , Ramesh Karri , Farshad Khorrami

Static performance estimation is essential during compile-time analysis, yet traditional runtime-based methods are costly and platform-dependent. We investigate mems, the number of memory accesses, as a static and architecture-independent…

Software Engineering · Computer Science 2025-05-13 Liwei Zhang , Baoquan Cui , Xutong Ma , Jian Zhang

Microarchitectural timing channels are a major threat to computer security. A set of OS mechanisms called time protection was recently proposed as a principled way of preventing information leakage through such channels and prototyped in…

Operating Systems · Computer Science 2023-10-27 Scott Buckley , Robert Sison , Nils Wistoff , Curtis Millar , Toby Murray , Gerwin Klein , Gernot Heiser

A general procedure for introducing parametric, learned, nonlinearity into activation functions is found to enhance the accuracy of representative neural networks without requiring significant additional computational resources. Examples…

Machine Learning · Computer Science 2025-05-14 David Yevick

Side-channel and fault injection attacks reveal secret information by monitoring or manipulating the physical effects of computations involving secret variables. Circuit-level countermeasures help to deter these attacks, and traditionally…

Cryptography and Security · Computer Science 2021-06-28 Yuan Yao , Pantea Kiaei , Richa Singh , Shahin Tajik , Patrick Schaumont

We present a set of novel ideas on design and implementation of monitor objects for multi-threaded programs. Our approach has two main goals: (a) increase parallelism in monitor objects and thus provide performance gains (shorter runtimes)…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-08-06 Weil-Lun Hung , Himanshu Chauhan , Vijay K. Garg

This paper presents a novel approach to ensure the safety of continuous-time linear dynamical systems controlled by a neural network (NN) based state-feedback. Our method capitalizes on the use of continuous piece-wise affine (PWA)…

Systems and Control · Electrical Eng. & Systems 2023-12-20 Louis Jouret , Adnane Saoud , Sorin Olaru

Security vulnerability analysis of Integrated Circuits using conventional design-time validation and verification techniques (like simulations, emulations, etc.) is generally a computationally intensive task and incomplete by nature,…

Cryptography and Security · Computer Science 2021-04-22 Faiq Khalid , Imran Hafeez Abbassi , Semeen Rehman , Awais Mehmood Kamboh , Osman Hasan , Muhammad Shafique

Radar sensors offer power-efficient solutions for always-on smart devices, but processing the data streams on resource-constrained embedded platforms remains challenging. This paper presents novel techniques that leverage the temporal…

Machine Learning · Computer Science 2023-09-13 Max Sponner , Julius Ott , Lorenzo Servadei , Bernd Waschneck , Robert Wille , Akash Kumar

This paper introduces an open-source and reproducible implementation of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) Networks for time series forecasting. We evaluated LSTM and GRU networks because of their performance…

Machine Learning · Computer Science 2025-04-28 Gissel Velarde , Pedro Branez , Alejandro Bueno , Rodrigo Heredia , Mateo Lopez-Ledezma

This paper presents the research work on multicore microcontrollers using parallel, and time critical programming for the embedded systems. Due to the high complexity and limitations, it is very hard to work on the application development…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-04-13 Prerna Saini , Ankit Bansal , Abhishek Sharma

We introduce SPLASH units, a class of learnable activation functions shown to simultaneously improve the accuracy of deep neural networks while also improving their robustness to adversarial attacks. SPLASH units have both a simple…

Machine Learning · Computer Science 2020-06-17 Mohammadamin Tavakoli , Forest Agostinelli , Pierre Baldi
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