Data Skeptic26 Juni 2015

[MINI] The Curse of Dimensionality

More features are not always better! With an increasing number of features to consider, machine learning algorithms suffer from the curse of dimensionality, as they have a wider set and often sparser coverage of examples to consider. This episode explores a real life example of this as Kyle and Linhda discuss their thoughts on purchasing a home.

The curse of dimensionality was defined by Richard Bellman, and applies in several slightly nuanced cases. This mini-episode discusses how it applies on machine learning.

This episode does not, however, discuss a slightly different version of the curse of dimensionality which appears in decision theoretic situations. Consider the game of chess. One must think ahead several moves in order to execute a successful strategy. However, thinking ahead another move requires a consideration of every possible move of every piece controlled, and every possible response one's opponent may take. The space of possible future states of the board grows exponentially with the horizon one wants to look ahead to. This is present in the notably useful Bellman equation.

Det här avsnittet är hämtat från ett öppet RSS-flöde och publiceras inte av Podme. Det kan innehålla reklam.

Avsnitt(601)

Github Network Analysis

In this episode we'll discuss how to use Github data as a network to extract insights about teamwork. Our guest, Gabriel Ramirez, manager of the notifications team at GitHub, will show how to apply ne...

22 Juni 202536min

Networks and Complexity

In this episode, Kyle does an overview of the intersection of graph theory and computational complexity theory. In complexity theory, we are about the runtime of an algorithm based on its input size....

14 Juni 202517min

Graphs for Causal AI

How to build artificial intelligence systems that understand cause and effect, moving beyond simple correlations? As we all know, correlation is not causation. "Spurious correlations" can show, for ex...

24 Maj 202541min

Power Networks

16 Maj 202541min

Unveiling Graph Datasets

8 Maj 202544min

Network Manipulation

In this episode we talk with Manita Pote, a PhD student at Indiana University Bloomington, specializing in online trust and safety, with a focus on detecting coordinated manipulation campaigns on soci...

30 Apr 202540min

The Small World Hypothesis

Kyle discusses the history and proof for the small world hypothesis.

21 Apr 202517min

Thinking in Networks

Kyle asks Asaf questions about the new network science course he is now teaching. The conversation delves into topics such as contact tracing, tools for analyzing networks, example use cases, and the...

12 Apr 202533min