{ "item_title" : "Algebraic Geometry and Statistical Learning Theory", "item_author" : [" Sumio Watanabe "], "item_description" : "Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/52/186/467/0521864674_b.jpg", "price_data" : { "retail_price" : "111.00", "online_price" : "111.00", "our_price" : "111.00", "club_price" : "111.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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