Probabilistic Graphical Models: Principles and Techniques (Hardcover)

Today: $130.92
Free Shipping*
ONLY 1 LEFT!

Club O Gold Members Earn

$6.55 | 5% Rewards*

Rewards

GOLD

$19.95/yr.

5% Rewards

Earn even faster

Free Shipping

Never pay extra*

Exclusive Rewards

Save big-- up to 40%

Exclusive Offers

Straight to your inbox

5% Dining Rewards

Get paid to go out tonight

ITEM# 12027338
  • Delivery Estimate

    Select a Product Option to view shipping

      **Delivery date is approximate and not guaranteed. Estimates include processing and shipping times, and are only available in US (excluding APO/FPO and PO Box addresses). Final shipping costs are available at checkout.

    • Notifications

    Love this item?

    Save it to a list so you can find it anytime!


    Oops,

    something went wrong.

    Please refresh the page and try again.


    Details

    ITEM#: 12027338

    Daphne Koller is Professor in the Department of Computer Science at Stanford University. Nir Friedman is Professor in the Department of Computer Science and Engineering at Hebrew University.

    Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.

    Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Specs

    ISBN 9780262013192
    Genre COMPUTERS / Machine Theory
    Format Hardcover
    Pages 1231
    Publisher Date 2009-08-31 00:00:00.0
    Publisher Mit Pr
    Copyright Year 2009
    Height 9.25 in
    Wdth 8.25 in
    Thickness 2.0 in
    Unit weight 4.65 lb
    Language English
    Subtitle Principles and Techniques
    Series Name Adaptive Computation and Machine Learning
    Audience College/higher education
    Authors Koller, Daphne
    Country of Origin United States
    Club O Silver

    Club O members earn Club O Rewards for writing reviews.

    Questions & Answers

    Yay! Be the first to ask a question about this product.

    Shopping Tips & Inspiration

    Shipping & Returns

    Contact Information
    Shipping:

    This item will be delivered to you via USPS Trackable Media Mail or UPS Mail Innovations and will take from 2 days to 3 weeks from the time the item leaves our warehouse. *

    This product is not yet released, and is expected to ship on Mar. 11, 2016.

    This date is subject to change. In order to assure you receive Overstock.com's low price on this item, your credit card will be charged upon order placement. The item will ship immediately upon release.

    Standard Return Policy:

    Items must be returned in new or unused condition and contain all original materials included with the shipment. More Details

    FINAL SALE EXCLUSION: Items marked as FINAL SALE are not returnable unless the problem you experience is the result of our error.

    For your protection, all orders are screened for security purposes. If your order is selected for review, our Loss Prevention Team may contact you by phone or email. There may be a two business day delay to process your order.

    ** Most Oversize orders are delivered within 1-4 weeks. Some orders may take 6 weeks to be delivered.

    Advertisement