Travelled to:1 × Austria
1 × Canada
1 × Russia
1 × United Kingdom
Collaborated with:P.Madhusudan P.Garg C.Löding ∅ P.Tabuada Pranav Garg 0001 A.Weinert M.Z.0002 D.Roth P. Ezudheen D.D'Souza B.Bollig J.Katoen C.Kern M.Leucker D.R.Piegdon
Talks about:learn (5) invari (4) framework (2) synthes (2) robust (2) linear (2) ice (2) counterexampl (1) structur (1) reachabl (1)
Person: Daniel Neider
DBLP: Neider:Daniel
Contributed to:
201420132010
2010
20162018
2018
2016Wrote 8 papers:
- CAV-2014-0001LMN #framework #invariant #learning #named #robust
- ICE: A Robust Framework for Learning Invariants (PG, CL, PM, DN), pp. 69–87.
- CAV-2013-0001LMN #data type #invariant #learning #linear #quantifier
- Learning Universally Quantified Invariants of Linear Data Structures (PG, CL, PM, DN), pp. 813–829.
- CAV-2010-BolligKKLNP #automaton #framework #learning #named
- libalf: The Automata Learning Framework (BB, JPK, CK, ML, DN, DRP), pp. 360–364.
- CIAA-2010-Neider #automation #game studies #graph #reachability
- Reachability Games on Automatic Graphs (DN), pp. 222–230.
- CSL-2016-TabuadaN #linear #logic #robust
- Robust Linear Temporal Logic (PT, DN), p. 21.
- CSL-2018-NeiderW0
- Synthesizing Optimally Resilient Controllers (DN, AW, MZ0), p. 17.
- OOPSLA-2018-EzudheenND0M #contract #invariant #learning
- Horn-ICE learning for synthesizing invariants and contracts (PE, DN, DD, PG0, PM), p. 25.
- POPL-2016-0001NMR #invariant #learning #using
- Learning invariants using decision trees and implication counterexamples (PG0, DN, PM, DR), pp. 499–512.