collaborators

8 papers

eess.SY2026

Conformal Predictive Programming for Chance Constrained Optimization

Yiqi Zhao, Xinyi Yu, Matteo Sesia +2

We propose conformal predictive programming (CPP), a framework to solve chance constrained optimization problems, i.e., optimization problems with constraints that are functions of…

cs.LG2026

Vision-Based Runtime Monitoring under Varying Specifications using Semantic Latent Representations

Bardh Hoxha, Oliver Schön, Hideki Okamoto +2

We study certified runtime monitoring of past-time signal temporal logic (ptSTL) from visual observations under partial observability. The monitor must infer safety-relevant quanti…

stat.ML2026

Multi-Variable Conformal Prediction: Optimizing Prediction Sets without Data Splitting

Laura Lützow, Simone Garatti, Marco C. Campi +2

Conformal prediction constructs prediction sets with finite-sample coverage guarantees, but its calibration stage is structurally constrained to a scalar score function and a singl…

eess.SY2026

Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints

Junyang Cai, Weimin Huang, Brendan Long +4

Motion-planning problems with temporal-logic or chance constraints are often encoded as mixed-integer linear programs (MILPs). Although these encodings provide rigorous specificati…

eess.SY2026

When Environments Shift: Safe Planning with Generative Priors and Robust Conformal Prediction

Kaizer Rahaman, Jyotirmoy V. Deshmukh, Ashish R. Hota +1

Autonomous systems operate in environments that may change over time. An example is the control of a self-driving vehicle among pedestrians and human-controlled vehicles whose beha…

cs.AI2025

Conformal Predictive Monitoring for Multi-Modal Scenarios

Francesca Cairoli, Luca Bortolussi, Jyotirmoy V. Deshmukh +2

We consider the problem of quantitative predictive monitoring (QPM) of stochastic systems, i.e., predicting at runtime the degree of satisfaction of a desired temporal logic proper…