Constraints as Control

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Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

The expectation value of a smooth conformal line defect in a CFT is a conformal invariant functional of its path in space-time. For example, in large N holographic theories, these fundamental observables are dual to the open-string partition function in Ad ...

Type inference in the presence of first-class or "impredicative" second-order polymorphism a la System F has been an active research area for several decades, with original works dating back to the end of the 80s. Yet, until now many basic problems remain ...

This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances. A primal- ...

This work presents the initial studies on the requirements for the design of 3D coils on EU-DEMO. The use of 3D coils in present machines includes two main purposes: the first one is the Error Field Correction (EFC). The EFC aims at minimizing the intrinsi ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

The Dependent Object Type (DOT) calculus was designed to put Scala on a sound basis, but while DOT relies on structural subtyping, Scala is a fundamentally class-based language. This impedance mismatch means that a proof of DOT soundness by itself is ...

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly base ...

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

We present an automated approach to verify the correctness of programming assignments, such as the ones that arise in a functional programming course. Our approach takes as input student submissions and reference solutions, and uses equivalence checking to ...

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...

Adjustable robust minimization problems where the objective or constraints depend in a convex way on the adjustable variables are generally difficult to solve. In this paper, we reformulate the original adjustable robust nonlinear problem with a polyhedral ...

Type-level programming is becoming more and more popular in the realm of functional programming. However, the combination of type-level programming and subtyping remains largely unexplored in practical programming languages. This paper presents match types ...

Constraints as Control

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Scalable constrained optimization

Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking

Learning to Remove Cuts in Integer Linear Programming

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Bootstrapping smooth conformal defects in Chern-Simons-matter theories

When Subtyping Constraints Liberate A Novel Type Inference Approach for First-Class Polymorphism

Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

Studies on EU-DEMO 3D coils requirements and conceptual design for error field correction and plasma control

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Type-Preserving Compilation of Class-Based Languages

Simulating intra-household interactions for in- and out-of-home activity scheduling

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Proving and Disproving Equivalence of Functional Programming Assignments

Homothetic Tube Model Predictive Control With Multi-Step Predictors

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Scaling Language Features for Program Verification

Dual Approach for Two-Stage Robust Nonlinear Optimization

Type-Level Programming with Match Types