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Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach

Description: Marhoefer Roberts presents ...Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach (Adaptive Computation and Machine Learning series) ISBN:0262047071 Author:Sugiyama, Masashi, Bao, Han, Ishida, Takashi, Lu, Nan, Sakai Publisher:The MIT Press Release Date:8/23/2022 Seller Category:1 Qty Available:4 Condition:Used: Excellent Sku: MIT-PB-LN-0262047071Notes: LIKE NEW!!! Has a red or black remainder mark on bottom/exterior edge of pages.Don't forget to check out other great deals in our eBay Store!!

Price: 23.92 USD

Location: Mckeesport, PA

End Time: 2024-12-01T14:20:32.000Z

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Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach

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Book Title: Machine Learning from Weak Supervision: An Empirical Risk Minimiz

Artist: Sugiyama, Masashi, Bao, Han, Ishida, Takashi, Lu, Nan, Sakai

Number of Pages: 320 Pages

Language: English

Publication Name: Machine Learning from Weak Supervision : an Empirical Risk Minimization Approach

Publisher: MIT Press

Subject: Game Theory, Programming / Algorithms, Intelligence (Ai) & Semantics, General

Publication Year: 2022

Item Height: 0.8 in

Type: Textbook

Item Weight: 26.3 Oz

Author: Tomoya Sakai, Han Bao, Masashi Sugiyama, Nan Lu, Takashi Ishida

Item Length: 9.3 in

Subject Area: Mathematics, Computers, Science

Series: Adaptive Computation and Machine Learning Ser.

Item Width: 7.2 in

Format: Hardcover

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