activity
20122024
most citedData-Driven Gain Scheduling Control of Linear Parameter-Varying Systems using Quadratic Matrix Inequalities

39 citations · 157 across the 35 of their papers we have counts for

collaborators

37 papers

cs.CV2024★ 1 cited

3D-HGS: 3D Half-Gaussian Splatting

Haolin Li, Jinyang Liu, Mario Sznaier +1

Photo-realistic image rendering from 3D scene reconstruction has advanced significantly with neural rendering techniques. Among these, 3D Gaussian Splatting (3D-GS) outperforms Neu…

cs.CV2024★ 1 cited

Solving Masked Jigsaw Puzzles with Diffusion Vision Transformers

Jinyang Liu, Wondmgezahu Teshome, Sandesh Ghimire +2

Solving image and video jigsaw puzzles poses the challenging task of rearranging image fragments or video frames from unordered sequences to restore meaningful images and video seq…

math.OC2024

Data-Driven Superstabilizing Control under Quadratically-Bounded Errors-in-Variables Noise

Jared Miller, Tianyu Dai, Mario Sznaier

The Error-in-Variables model of system identification/control involves nontrivial input and measurement corruption of observed data, resulting in generically nonconvex optimization…

math.OC2024★ 1 cited

Unsafe Probabilities and Risk Contours for Stochastic Processes using Convex Optimization

Jared Miller, Matteo Tacchi, Didier Henrion +1

This paper proposes an algorithm to calculate the maximal probability of unsafety with respect to trajectories of a stochastic process and a hazard set. The unsafe probability esti…

cs.LG2023

Inferring Relational Potentials in Interacting Systems

Armand Comas-Massagué, Yilun Du, Christian Fernandez +4

Systems consisting of interacting agents are prevalent in the world, ranging from dynamical systems in physics to complex biological networks. To build systems which can interact r…

math.OC2023

Data-Driven Superstabilization of Linear Systems under Quantization

Jared Miller, Jian Zheng, Mario Sznaier +1

This paper focuses on the stabilization and regulation of linear systems affected by quantization in state-transition data and actuated input. The observed data are composed of tup…

cs.CV2023

Cross-view Action Recognition via Contrastive View-invariant Representation

Yuexi Zhang, Dan Luo, Balaji Sundareshan +2

Cross view action recognition (CVAR) seeks to recognize a human action when observed from a previously unseen viewpoint. This is a challenging problem since the appearance of an ac…

math.OC2023★ 1 cited

Peak Estimation of Time Delay Systems using Occupation Measures

Jared Miller, Milan Korda, Victor Magron +1

This work proposes a method to compute the maximum value obtained by a state function along trajectories of a Delay Differential Equation (DDE). An example of this task is finding…

math.OC2023

Data-Driven Control of Positive Linear Systems using Linear Programming

Jared Miller, Tianyu Dai, Mario Sznaier +1

This paper presents a linear-programming based algorithm to perform data-driven stabilizing control of linear positive systems. A set of state-input-transition observations is coll…

math.OC2023★ 2 cited

Peak Estimation of Hybrid Systems with Convex Optimization

Jared Miller, Mario Sznaier

Peak estimation of hybrid systems aims to upper bound extreme values of a state function along trajectories, where this state function could be different in each subsystem. This fi…

math.OC2023

Robust Data-Driven Safe Control using Density Functions

Jian Zheng, Tianyu Dai, Jared Miller +1

This paper presents a tractable framework for data-driven synthesis of robustly safe control laws. Given noisy experimental data and some priors about the structure of the system,…

math.OC2023

Peak Value-at-Risk Estimation of Stochastic Processes using Occupation Measures

Jared Miller, Matteo Tacchi, Mario Sznaier +1

This paper formulates algorithms to upper-bound the maximum Value-at-Risk (VaR) of a state function along trajectories of stochastic processes. The VaR is upper bounded by two meth…

math.OC2023★ 1 cited

Quantifying the Safety of Trajectories using Peak-Minimizing Control

Jared Miller, Mario Sznaier

This work quantifies the safety of trajectories of a dynamical system by the perturbation intensity required to render a system unsafe (crash into the unsafe set). Computation of t…

cs.CV2022

SAIF: Sparse Adversarial and Imperceptible Attack Framework

Tooba Imtiaz, Morgan Kohler, Jared Miller +5

Adversarial attacks hamper the decision-making ability of neural networks by perturbing the input signal. The addition of calculated small distortion to images, for instance, can d…

math.OC2022

Superstabilizing Control of Discrete-Time ARX Models under Error in Variables

Jared Miller, Tianyu Dai, Mario Sznaier

This paper applies a polynomial optimization based framework towards the superstabilizing control of an Autoregressive with Exogenous Input (ARX) model given noisy data observation…

math.OC2022★ 4 cited

Data-Driven Stabilizing and Robust Control of Discrete-Time Linear Systems with Error in Variables

Jared Miller, Tianyu Dai, Mario Sznaier

This work presents a sum-of-squares (SOS) based framework to perform data-driven stabilization and robust control tasks on discrete-time linear systems where the full-state observa…

math.OC2022★ 39 cited

Data-Driven Gain Scheduling Control of Linear Parameter-Varying Systems using Quadratic Matrix Inequalities

Jared Miller, Mario Sznaier

This paper synthesizes a gain-scheduled controller to stabilize all possible Linear Parameter-Varying (LPV) plants that are consistent with measured input/state data records. Inspi…

math.OC2022★ 1 cited

A Globally Convergent LP and SOCP-based algorithm for Semidefinite Programming

Biel Roig-Solvas, Mario Sznaier

Semidefinite programs (SDP) are one of the most versatile frameworks in numerical optimization, serving as generalizations of many conic programs and as relaxations of NP-hard comb…

math.OC2021★ 3 cited

Analysis and Control of Input-Affine Dynamical Systems using Infinite-Dimensional Robust Counterparts

Jared Miller, Mario Sznaier

Input-affine dynamical systems often arise in control and modeling scenarios, such as the data-driven case when state-derivative observations are recorded under bounded noise. Comm…

math.OC2021★ 16 cited

Bounding the Distance to Unsafe Sets with Convex Optimization

Jared Miller, Mario Sznaier

This work proposes an algorithm to bound the minimum distance between points on trajectories of a dynamical system and points on an unsafe set. Prior work on certifying safety of t…

cs.CV2021★ 1 cited

Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective

Armand Comas, Sandesh Ghimire, Haolin Li +2

Human interpretation of the world encompasses the use of symbols to categorize sensory inputs and compose them in a hierarchical manner. One of the long-term objectives of Computer…

math.OC2021

Peak Estimation for Uncertain and Switched Systems

Jared Miller, Didier Henrion, Mario Sznaier +1

Peak estimation bounds extreme values of a function of state along trajectories of a dynamical system. This paper focuses on extending peak estimation to continuous and discrete se…

eess.SY2021★ 4 cited

A Convex Optimization Approach to Learning Koopman Operators

Mario Sznaier

Koopman operators provide tractable means of learning linear approximations of non-linear dynamics. Many approaches have been proposed to find these operators, typically based upon…

eess.SY2020★ 1 cited

Peak Estimation and Recovery with Occupation Measures

Jared Miller, Didier Henrion, Mario Sznaier

Peak Estimation aims to find the maximum value of a state function achieved by a dynamical system. This problem is non-convex when considering standard Barrier and Density methods…