Understandable Artificial Intelligence
Sept 2019
EDS Tool Overview
Stochastic Gradient Descent
Stochastic Gradient Descent
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What Is It?

Often referred to as SGD
 This method is an iterative approach to optimization
 This approach can be traced back to at least 1951

Two parts:
 Stochastic = random starting position
 Gradient Descent = the approach used to optimize
 This method is so popular it is a default tool in Microsoft Excel
Basic Gradient Descent
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Assumes All TradeOffs Are Smooth
 A seeker finds the most benefit per unit of uncertainty
 It does this by 'rolling' along the line
Yup, found the best
Stochastic Gradient Descent
©2019 Economic Data Sciences
Why Does this Matter? Part I: Rough Tradeoffs
 The real world isn't like theory, it's messier
 SGD sends several 'seekers' to find the best option given the complexities of the real world
I'm The Best!
I'm The Best!
I'm The Best!
I'm The Best!
I'm The Best!
Only This is Truly The Best
Stochastic Gradient Descent
©2019 Economic Data Sciences
Why Does this Matter? Part II: Many Different Risks & Goals
 Risk, uncertainty, and opportunities come in many different forms
 A technique like SGD is needed to consider all of these simultaneously
Does It Work?
©2019 Economic Data Sciences
Proof Is In The Pudding
 Forgetting about all of these details the important question is:
 Does it work?
 EDS has now conduct 30+ projects
 In 100% of cases, improvements have been made after the analysis
 How?
 In essence, the ability to consider more factors and information leads to more informed decisions
 Simply, more informed decision making leads to better outcomes
Why Doesn't Everyone Do It?
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A Natural Question is to Ask Why Haven't You Seen This Before
 The simple answer is many have tried
 Using SGD means it is difficult to be 'sure' the solution is best
 Past solutions haven't been able to solve this issue
 In short, it is easy to do poorly
 Only the EDS technology can provide consistent and confident results
 Our distributed approach coordinates a single problem across a cluster of computers
What Is So Special About EDS?
©2019 Economic Data Sciences
Distributed, Coordinated, & Informed
 A real world problem usually includes:
 100s of important factors
 Qualitative & Quantitative
 1000s of potential investments
 100s of important factors
 EDS's technology has three key pillars for success:
 Distributed: Only distributed systems can handle problems of this size
 Coordinated: Working with a distributed system means that all of the distributed workers must be coordinated
 Informed: Keeping a memory of what solutions work best means EDS can solve these problems faster
©2019 Economic Data Sciences
On The Shoulders Of Giants
 Building on current methods adds interpretability and transparency
 Extendable frameworks allow inclusions from other models and insights
 TailRisk, Diversification Ratio, BlackLitterman, etc.
1950s
1980s
2010s
An Extendable
Framework
EDS's mathematical insights extend current best practices
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