Reducing the Multiplicative Complexity in Logic Networks for Cryptography and Security Applications

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Contextual Stochastic Bilevel Optimization

Daniel Kuhn, Andreas Krause, Yifan Hu

We introduce contextual stochastic bilevel optimization (CSBO) -- a stochastic bilevel optimization framework with the lower-level problem minimizing an expectation conditioned on some contextual information and the upper-level decision variable. This fram ...

2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

Logic Synthesis From Incomplete Specifications Using Disjoint Support Decomposition

Giovanni De Micheli, Andrea Costamagna

Approximate logic synthesis is an emerging field that tolerates errors in the synthesized logic circuits for better optimization quality. Indeed, in many computing problems, the requirement of preserving the exact functionality either results in unnecessar ...

IEEE2022

Boolean Rewriting Strikes Back: Reconvergence- Driven Windowing meets Resynthesis

Giovanni De Micheli, Heinz Riener, Siang-Yun Lee

The paper presents a novel DAG-aware Boolean rewriting algorithm for restructuring combinational logic before technology mapping. The algorithm, called window rewriting, repeatedly selects small parts of the logic and replaces them with more compact implem ...

IEEE2022

Utilizing XMG-based Synthesis to Preserve Self-Duality for RFET-Based Circuits

Giovanni De Micheli, Heinz Riener, Alessandro Tempia Calvino, Akash Kumar

Individual transistors based on emerging reconfigurable nanotechnologies exhibit electrical conduction for both types of charge carriers. These transistors (referred to as Reconfigurable Field-Effect Transistors (RFETs)) enable dynamic reconfiguration to d ...

2022

A chance-constraint approach for optimizing Social Engagement-based services

Michel Bierlaire

Social Engagement is a novel business model transforming final users of a service from passive into active components. In this framework, people are contacted by a company and they are asked to perform tasks in exchange for a reward. This arises the compli ...

IEEE2022

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

IEEE2022

Improving the Training of Compact Neural Networks for Visual Recognition

Shuxuan Guo

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

EPFL2022

Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks

Chen Liu

In the last decade, deep neural networks have achieved tremendous success in many fields of machine learning. However, they are shown vulnerable against adversarial attacks: well-designed, yet imperceptible, perturbations can make the state-of-the-art deep ...

EPFL2022

Minimum Cost Intervention Design for Causal Effect Identification

Negar Kiyavash, Seyed Jalal Etesami, Sina Akbari

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the ...

PMLR2022

Electronic transport in graphene nanoribbon junctions

Kristians Cernevics

Graphene nanoribbons (GNRs) - one-dimensional strips of graphene - share many of the exciting properties of graphene, such as ballistic transport over micron dimensions, strength and flexibility, but more importantly, they exhibit a tunable band gap that d ...

EPFL2022