Natali Ruchansky

21 papers A* 3A 5Misc 1Journal 8Unranked 1
YearRankTypeTitle / Venue / Authors
2023 — ed.
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VI
ECML/PKDD (6)
Gianmarco De Francisci Morales, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis, Francesco Bonchi
2023 — ed.
Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part VII
ECML/PKDD (7)
Gianmarco De Francisci Morales, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis, Francesco Bonchi
2019 J jnl
Combating Fake News: A Survey on Identification and Mitigation Techniques.
CoRR
Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
2019 J jnl
Combating Fake News: A Survey on Identification and Mitigation Techniques.
ACM Trans. Intell. Syst. Technol.
Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
2018 A conf
Matrix completability analysis via graph k-connectivity.
AISTATS
Dehua Cheng, Natali Ruchansky, Yan Liu
2017 A conf
CSI: A Hybrid Deep Model for Fake News Detection.
CIKM
Natali Ruchansky, Sungyong Seo, Yan Liu
2017 J jnl
CSI: A Hybrid Deep Model for Fake News.
CoRR
Natali Ruchansky, Sungyong Seo, Yan Liu
2017 J jnl
Matrix completion with queries.
CoRR
Natali Ruchansky, Mark Crovella, Evimaria Terzi
2017 A conf
Targeted matrix completion.
SDM
Natali Ruchansky, Mark Crovella, Evimaria Terzi
2017 J jnl
Targeted matrix completion.
CoRR
Natali Ruchansky, Mark Crovella, Evimaria Terzi
2017 A conf
To Be Connected, or Not to Be Connected: That is the Minimum Inefficiency Subgraph Problem.
CIKM
Natali Ruchansky, Francesco Bonchi, David García-Soriano, Francesco Gullo, Nicolas Kourtellis
2017 J jnl
To Be Connected, or Not to Be Connected: That is the Minimum Inefficiency Subgraph Problem.
CoRR
Natali Ruchansky, Francesco Bonchi, David García-Soriano, Francesco Gullo, Nicolas Kourtellis
2016 — —
Matrix completion with structure
Natali Ruchansky
2015 A* conf
Matrix Completion with Queries.
KDD
Natali Ruchansky, Mark Crovella, Evimaria Terzi
2015 — conf
The Minimum Wiener Connector Problem.
SIGMOD Conference
Natali Ruchansky, Francesco Bonchi, David García-Soriano, Francesco Gullo, Nicolas Kourtellis
2015 J jnl
The Minimum Wiener Connector.
CoRR
Natali Ruchansky, Francesco Bonchi, David García-Soriano, Francesco Gullo, Nicolas Kourtellis
2013 A* conf
A (not) NICE way to verify the openflow switch specification: formal modelling of the openflow switch using alloy.
SIGCOMM
Natali Ruchansky, Davide Proserpio
2012 J jnl
Inferring Visibility: Who's (Not) Talking to Whom?
Tiny Trans. Comput. Sci.
Gonca Gürsun, Natali Ruchansky, Evimaria Terzi, Mark Crovella
2012 A* conf
Inferring visibility: who's (not) talking to whom?
SIGCOMM
Gonca Gürsun, Natali Ruchansky, Evimaria Terzi, Mark Crovella
2012 A conf
Routing state distance: a path-based metric for network analysis.
Internet Measurement Conference
Gonca Gürsun, Natali Ruchansky, Evimaria Terzi, Mark Crovella
2011 Misc conf
Monitoring workspace activities using accelerometers.
ICASSP
Natali Ruchansky, Claire Lochner, Elizabeth Do, Tremaine Rawls, Mohamed Nabil Hajj Chehade, Jay Chien, Gregory J. Pottie, William J. Kaiser
redb/extractors/macho_extractors/__init__.py
← Index redb/extractors/macho_extractors/__init__.py python 
# MachO extractors package

from .macho_features import MachOFeaturesExtractor
from .macho_segments import MachOSegmentExtractor
from .macho_imports import MachOImportExtractor
from .macho_exports import MachOExportExtractor
from .macho_dylibs import MachODylibExtractor
from .macho_signature import MachOSignatureExtractor
from .macho_similarity_hashes import MachOSimilarityHashExtractor
# MachOUniversalExtractor is deprecated - FAT binary relationships are now
# tracked via parent_sha256 column in redb_basic_properties
# from .macho_universal import MachOUniversalExtractor

__all__ = [
    'MachOFeaturesExtractor',
    'MachOSegmentExtractor',
    'MachOImportExtractor',
    'MachOExportExtractor',
    'MachODylibExtractor',
    'MachOSignatureExtractor',
    'MachOSimilarityHashExtractor',
    # 'MachOUniversalExtractor',  # Deprecated
]