most citedOptimization and Abstraction: A Synergistic Approach for Analyzing Neural Network Robustness

84 citations · 129 across the 7 of their papers we have counts for

collaborators

8 papers

cs.PL201984 cited

Optimization and Abstraction: A Synergistic Approach for Analyzing Neural Network Robustness

Greg Anderson, Shankara Pailoor, Isil Dillig +1

In recent years, the notion of local robustness (or robustness for short) has emerged as a desirable property of deep neural networks. Intuitively, robustness means that small pert…

cs.PL20171 cited

Program Synthesis using Conflict-Driven Learning

Yu Feng, Ruben Martins, Osbert Bastani +1

We propose a new conflict-driven program synthesis technique that is capable of learning from past mistakes. Given a spurious program that violates the desired specification, our s…

cs.PL2017

Automated Migration of Hierarchical Data to Relational Tables using Programming-by-Example

Navid Yaghmazadeh, Xinyu Wang, Isil Dillig

While many applications export data in hierarchical formats like XML and JSON, it is often necessary to convert such hierarchical documents to a relational representation. This pap…

cs.PL201718 cited

Program Synthesis using Abstraction Refinement

Xinyu Wang, Isil Dillig, Rishabh Singh

We present a new approach to example-guided program synthesis based on counterexample-guided abstraction refinement. Our method uses the abstract semantics of the underlying DSL to…

cs.LO2017

Verifying Equivalence of Database-Driven Applications

Yuepeng Wang, Isil Dillig, Shuvendu K. Lahiri +1

This paper addresses the problem of verifying equivalence between a pair of programs that operate over databases with different schemas. This problem is particularly important in t…

cs.PL20173 cited

Synthesis of Data Completion Scripts using Finite Tree Automata

Xinyu Wang, Isil Dillig, Rishabh Singh

In application domains that store data in a tabular format, a common task is to fill the values of some cells using values stored in other cells. For instance, such data completion…