Head, Torso and Tail - Performance for modeling real data, Alex Smola

Автор: MMDS Foundation

Загружено: 2016-10-15

Просмотров: 1082

Описание: Real data is high dimensional and multi variate. A naive application of optimization techniques leads to rather poor performance, due to large memory footprint, latency and network cost. In this talk I will address how to overcome these constraints by design that takes advantage of distributional properties of real data for recommendation, classification and modeling.

Не удается загрузить Youtube-плеер. Проверьте блокировку Youtube в вашей сети.
Повторяем попытку...

Head, Torso and Tail - Performance for modeling real data, Alex Smola

Доступные форматы для скачивания:

Скачать видео

Информация по загрузке:

Скачать аудио

Похожие видео

The Union of Intersections Method, Kristopher Bouchard

The Union of Intersections Method, Kristopher Bouchard

Is manifold learning for toy data only?, Marina Meila

Is manifold learning for toy data only?, Marina Meila

Restricted Strong Convexity Implies Weak Submodularity, Alex Dimakis

Restricted Strong Convexity Implies Weak Submodularity, Alex Dimakis

Fast, flexible, and interpretable regression modeling, Daniela Witten

Fast, flexible, and interpretable regression modeling, Daniela Witten

Но что такое нейронная сеть? | Глава 1. Глубокое обучение

Но что такое нейронная сеть? | Глава 1. Глубокое обучение

But what is a convolution?

But what is a convolution?

Understanding GD&T

Understanding GD&T

Randomized Low-Rank Approximation and PCA: Beyond Sketching, Cameron Musco

Randomized Low-Rank Approximation and PCA: Beyond Sketching, Cameron Musco

Теорема Байеса, геометрия изменения убеждений

Теорема Байеса, геометрия изменения убеждений

Variational Autoencoders

Variational Autoencoders