It takes the average reader 2 hours and 20 minutes to read Optimization Algorithms for Distributed Machine Learning by Gauri Joshi
Assuming a reading speed of 250 words per minute. Learn more
This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.
Optimization Algorithms for Distributed Machine Learning by Gauri Joshi is 137 pages long, and a total of 35,209 words.
This makes it 46% the length of the average book. It also has 43% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 3 hours and 12 minutes to read Optimization Algorithms for Distributed Machine Learning aloud.
Optimization Algorithms for Distributed Machine Learning is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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