b'Daniel Neider'

research

∙ 07/20/2023

Robust Alternating-Time Temporal Logic

In multi-agent system design, a crucial aspect is to ensure robustness, ...

0 Aniello Murano, et al. ∙

research

∙ 06/23/2023

Reinforcement Learning with Temporal-Logic-Based Causal Diagrams

We study a class of reinforcement learning (RL) tasks where the objectiv...

0 Yash Paliwal, et al. ∙

research

∙ 03/24/2023

Interpretable Anomaly Detection via Discrete Optimization

Anomaly detection is essential in many application domains, such as cybe...

0 Simon Lutz, et al. ∙

research

∙ 03/10/2023

Deep Anomaly Detection on Tennessee Eastman Process Data

This paper provides the first comprehensive evaluation and analysis of m...

0 Fabian Hartung, et al. ∙

research

∙ 12/02/2022

Learning Temporal Logic Properties: an Overview of Two Recent Methods

Learning linear temporal logic (LTL) formulas from examples labeled as p...

0 Jean-Raphaël Gaglione, et al. ∙

research

∙ 09/21/2022

Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise

Angluin's L* algorithm learns the minimal (complete) deterministic finit...

0 Igor Khmelnitsky, et al. ∙

research

∙ 09/06/2022

Learning Interpretable Temporal Properties from Positive Examples Only

We consider the problem of explaining the temporal behavior of black-box...

0 Rajarshi Roy, et al. ∙

research

∙ 06/14/2022

Specification sketching for Linear Temporal Logic

Virtually all verification and synthesis techniques assume that the form...

0 Simon Lutz, et al. ∙

research

∙ 04/22/2022

Robustness-by-Construction Synthesis: Adapting to the Environment at Runtime

While most of the current synthesis algorithms only focus on correctness...

0 Satya Prakash Nayak, et al. ∙

research

∙ 03/02/2022

Neuro-Symbolic Verification of Deep Neural Networks

Formal verification has emerged as a powerful approach to ensure the saf...

18 Xuan Xie, et al. ∙

research

∙ 01/18/2022

Robust Computation Tree Logic

It is widely accepted that every system should be robust in that "small"...

0 Satya Prakash Nayak, et al. ∙

research

∙ 11/12/2021

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

Apple recently revealed its deep perceptual hashing system NeuralHash to...

10 Lukas Struppek, et al. ∙

research

∙ 10/13/2021

Scalable Anytime Algorithms for Learning Formulas in Linear Temporal Logic

Linear temporal logic (LTL) is a specification language for finite seque...

0 Ritam Raha, et al. ∙

research

∙ 05/24/2021

Uncertainty-Aware Signal Temporal Logic Inference

Temporal logic inference is the process of extracting formal description...

0 Nasim Baharisangari, et al. ∙

research

∙ 04/30/2021

Learning Linear Temporal Properties from Noisy Data: A MaxSAT Approach

We address the problem of inferring descriptions of system behavior usin...

0 Jean-Raphaël Gaglione, et al. ∙

research

∙ 02/24/2021

Being correct is not enough: efficient verification using robust linear temporal logic

While most approaches in formal methods address system correctness, ensu...

0 Tzanis Anevlavis, et al. ∙

research

∙ 09/28/2020

Parameterized Synthesis with Safety Properties

Parameterized synthesis offers a solution to the problem of constructing...

0 Oliver Markgraf, et al. ∙

research

∙ 09/22/2020

Property-Directed Verification of Recurrent Neural Networks

This paper presents a property-directed approach to verifying recurrent ...

24 Igor Khmelnitsky, et al. ∙

research

∙ 09/18/2020

Probably Approximately Correct Explanations of Machine Learning Models via Syntax-Guided Synthesis

We propose a novel approach to understanding the decision making of comp...

0 Daniel Neider, et al. ∙

research

∙ 06/12/2020

A Formal Language Approach to Explaining RNNs

This paper presents LEXR, a framework for explaining the decision making...

0 Bishwamittra Ghosh, et al. ∙

research

∙ 02/10/2020

Learning Interpretable Models in the Property Specification Language

We address the problem of learning human-interpretable descriptions of a...

17 Rajarshi Roy, et al. ∙

research

∙ 12/10/2019

Optimally Resilient Strategies in Pushdown Safety Games

Infinite-duration games with disturbances extend the classical framework...

0 Daniel Neider, et al. ∙

research

∙ 09/17/2019

Robust, Expressive, and Quantitative Linear Temporal Logics: Pick any Two for Free

Linear Temporal Logic (LTL) is the standard specification language for r...

0 Daniel Neider, et al. ∙

research

∙ 09/12/2019

Joint Inference of Reward Machines and Policies for Reinforcement Learning

Incorporating high-level knowledge is an effective way to expedite reinf...

0 Zhe Xu, et al. ∙

research

∙ 01/21/2019

Learning-Based Synthesis of Safety Controllers

We propose a machine learning framework to synthesize reactive controlle...

0 Daniel Neider, et al. ∙

research

∙ 08/27/2018

Robust, Expressive, and Quantitative Linear Temporal Logics

Linear Temporal Logic (LTL) is the standard specification language for r...

0 Daniel Neider, et al. ∙

research

∙ 07/21/2018

Robust Monitoring of Linear Temporal Properties

Runtime verification is commonly used to detect and, if possible, react ...

0 Daniel Neider, et al. ∙

research

∙ 06/11/2018

Learning Linear Temporal Properties

We present two novel algorithms for learning formulas in Linear Temporal...

0 Daniel Neider, et al. ∙

research

∙ 12/26/2017

Horn-ICE Learning for Synthesizing Invariants and Contracts

We design learning algorithms for synthesizing invariants using Horn imp...

0 Deepak D'Souza, et al. ∙

research

∙ 12/15/2017

Invariant Synthesis for Incomplete Verification Engines

We propose a framework for synthesizing inductive invariants for incompl...

0 Daniel Neider, et al. ∙

research

∙ 09/14/2017

Synthesizing Optimally Resilient Controllers

Recently, Dallal, Neider, and Tabuada studied a generalization of the cl...

0 Daniel Neider, et al. ∙

Daniel Neider

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