EP4229559A4 - Systems and methods for providing a modified loss function in federated-split learning - Google Patents

Systems and methods for providing a modified loss function in federated-split learning

Info

Publication number
EP4229559A4
EP4229559A4 EP21880886.3A EP21880886A EP4229559A4 EP 4229559 A4 EP4229559 A4 EP 4229559A4 EP 21880886 A EP21880886 A EP 21880886A EP 4229559 A4 EP4229559 A4 EP 4229559A4
Authority
EP
European Patent Office
Prior art keywords
federated
systems
methods
providing
loss function
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21880886.3A
Other languages
German (de)
French (fr)
Other versions
EP4229559A1 (en
Inventor
Gharib Gharibi
Ravi Patel
Babak Poorebrahim Gilkalaye
Praneeth Vepakomma
Greg Storm
Riddhiman Das
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
TripleBlind Inc
Original Assignee
TripleBlind Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by TripleBlind Inc filed Critical TripleBlind Inc
Priority claimed from PCT/US2021/054518 external-priority patent/WO2022081539A1/en
Publication of EP4229559A1 publication Critical patent/EP4229559A1/en
Publication of EP4229559A4 publication Critical patent/EP4229559A4/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/098—Distributed learning, e.g. federated learning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L2209/00—Additional information or applications relating to cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
    • H04L2209/46—Secure multiparty computation, e.g. millionaire problem
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
    • H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
    • H04L9/0838—Key agreement, i.e. key establishment technique in which a shared key is derived by parties as a function of information contributed by, or associated with, each of these
    • H04L9/0841—Key agreement, i.e. key establishment technique in which a shared key is derived by parties as a function of information contributed by, or associated with, each of these involving Diffie-Hellman or related key agreement protocols
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
    • H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
    • H04L9/085—Secret sharing or secret splitting, e.g. threshold schemes

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Computer And Data Communications (AREA)
EP21880886.3A 2020-10-13 2021-10-12 Systems and methods for providing a modified loss function in federated-split learning Pending EP4229559A4 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US202063090904P 2020-10-13 2020-10-13
US202163226135P 2021-07-27 2021-07-27
PCT/US2021/054518 WO2022081539A1 (en) 2020-10-13 2021-10-12 Systems and methods for providing a modified loss function in federated-split learning

Publications (2)

Publication Number Publication Date
EP4229559A1 EP4229559A1 (en) 2023-08-23
EP4229559A4 true EP4229559A4 (en) 2024-04-17

Family

ID=87264196

Family Applications (1)

Application Number Title Priority Date Filing Date
EP21880886.3A Pending EP4229559A4 (en) 2020-10-13 2021-10-12 Systems and methods for providing a modified loss function in federated-split learning

Country Status (1)

Country Link
EP (1) EP4229559A4 (en)

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
BONAWITZ KEITH BONAWITZ@GOOGLE COM ET AL: "Practical Secure Aggregation for Privacy-Preserving Machine Learning", PROCEEDINGS OF THE 18TH ACM/IFIP/USENIX MIDDLEWARE CONFERENCE, ACMPUB27, NEW YORK, NY, USA, 30 October 2017 (2017-10-30), pages 1175 - 1191, XP058698077, ISBN: 978-1-4503-5525-4, DOI: 10.1145/3133956.3133982 *

Also Published As

Publication number Publication date
EP4229559A1 (en) 2023-08-23

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