algorithm


Machine Learning using Advanced Algorithms and Visualization

@machinelearnbot

Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. Then, we'll walk you through the next example on letter recognition, where you will train a program to recognize letters using a support Vector machine, examine the results, and plot a confusion matrix. Tim Hoolihan currently works at DialogTech, a marketing analytics company focused on conversations. He is the Senior Director of Data Science there.


Artificial Intelligence penned an entire pop music album--and it's not actually that bad

#artificialintelligence

For those who criticize pop music for being manufactured and predictable--you're in for a treat. "Break Free" is the first song from Taryn Southern's new album. Southern's album, I AM AI, was created by Amper: an artificially intelligent music composer, producer, and performer. Unlike other music-making AIs--Orb Composer or JukeDeck, for instance--Amper can create sounds, chords progressions, and beats, and only needs human input to tweak the style or rhythm if necessary.


Machine Learning vs. Statistics: The Texas Death Match of Data Science

@machinelearnbot

Both Statistics and Machine Learning create models from data, but for different purposes. In conclusion, the Statistician is concerned primarily with model validity, accurate estimation of model parameters, and inference from the model. In Machine Learning, the predominant task is predictive modeling: the creation of models for the purpose of predicting labels of new examples. In predictive analytics, the ML algorithm is given a set of historical labeled examples.


Learning from Experience: FDA's Treatment of Machine Learning

#artificialintelligence

While the 21st Century Cures Act that passed last December exempted certain CDS from regulation and indeed FDA intends to exempt even more, FDA will continue to regulate high risk CDS. Initially such software was placed in class III – the highest regulatory oversight for products with the greatest risk – but more recently FDA has regulated that software in class II for products of only moderate risk. In the 2012 guidance documents, FDA lists information such as algorithm design, features, models, classifiers, the data sets used to train and test the algorithm, and the test data hygiene used. FDA has also begun to receive submissions to clear software that employs machine learning in what the agency refers to as "adaptive systems" – systems that evolve over time based on the new evidence collected in the field after the device goes to market.



Toward Algorithmic Transparency and Accountability

Communications of the ACM

The ACM U.S. Public Policy Council (USACM) was established in the early 1990s as a focal point for ACM's interactions with U.S. government organizations, the computing community, and the public in all matters of U.S. public policy related to information technology. USACM and EUACM have identified and codified a set of principles intended to ensure fairness in this evolving policy and technology ecosystem.a These are: (1) awareness; (2) access and redress; (3) accountability; (4) explanation; (5) data provenance; (6) audit-ability; and (7) validation and testing. As organizations deploy complex algorithms for automated decision making, system designers should build these principles into their systems. USACM and EUACM seek input and involvement from ACM's members in providing technical expertise to decision makers on the often difficult policy questions relating to algorithmic transparency and accountability, as well as those relating to security, privacy, accessibility, intellectual property, big data, voting, and other technical areas.


Story of Anima Anandkumar, the machine learning guru powering Amazon AI

#artificialintelligence

Our Techie Tuesdays protagonist of the week, Anima has worked towards establishing a strong collaboration between academia and industry. Anima worked on solving this problem of tracking end to end service level transactions. She wanted to design learning algorithms that can process at scale and make efficient inferences about the underlying hidden information. When Anima joined UC Irvine as a faculty, that time was the beginning of the big data revolution.


The Top 10 AI And Machine Learning Use Cases Everyone Should Know About

#artificialintelligence

Very basically, a machine learning algorithm is given a "teaching set" of data, then asked to use that data to answer a question. Many prestigious trading firms use proprietary systems to predict and execute trades at high speeds and high volume. Machine learning algorithms can process more information and spot more patterns than their human counterparts. Intelligent machine learning algorithms analyze your activity and compare it to the millions of other users to determine what you might like to buy or binge watch next.


Backprop is not just the chain rule

@machinelearnbot

Let's view the intermediate variables in our optimization problem as simple equality constraints in an equivalent constrained optimization problem. It turns out that the de facto method for handling constraints, the method Lagrange multipliers, recovers exactly the adjoints (intermediate derivatives) in the backprop algorithm! The standard way to solve a constrained optimization is to use the method Lagrange multipliers, which converts a constrained optimization problem into an unconstrained problem with a few more variables \(\boldsymbol{\lambda}\) (one per \(x_i\) constraint), called Lagrange multipliers. I described how we could use something we did learn from calculus 101, the method of Lagrange multipliers, to support optimization with intermediate variables.


Forgery Robots: AI and Identity Theft

#artificialintelligence

Another capability is Jeff Clune's and Evolving AI Lab's research which is working on image recognition capabilities in reverse. This means that by using neural networks trained in object recognition it can generate artificial images based solely on text description. That means that it relies on machine learning algorithms to take images and analyse them, quantifying the aspects of it observation. It's safe to say that Artificial Intelligence poses a serious concern for identity theft and forgery.