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Modular Networks: Learning to Decompose Neural Computation
2.1 Learning Modular Networks. From a probabilistic modeling perspective the natural training objective is Modular layers can readily be used to update the state within an RNN. This allows us to model We introduced the modular gated recurrent unit, a modied GRU that enables minimalistic...


Writing Learning Outcomes | Sample Module Learning Outcomes .. 25
...credits and modular frameworks, leads to module/unit overload as too much is crammed into a 1 Taken from Kennedy, D. (2007) Writing and Using Learning Outcomes, Cork: Quality Promotion Unit, UCC. Module Learning Outcomes more logical to run two closely related actions into one learning...


Learning Modular Java Programming
Learning Modular Java Programming. Copyright © 2016 Packt Publishing. Unit testing using JUnit. Steps for writing a TestCase using annotation. Chapter 1, Introducing Modular Programming, starts with a discussion about Enterprise application, its architecture, and its development.


Learning Yii Testing | Writing maintainable unit tests
Writing maintainable unit tests. Summary. Chapter 6: Testing the API – PHPBrowser to the Rescue. Chapter 4, Isolated Component Testing with PHPUnit, demonstrates PHPUnit. The first unit tests are implemented in this chapter, with the help of data providers.


Aggregator Writers 184 Summary 186 ■■Chapter 8: Beyond the Basic API 187 Graph Mutations 188 The Mutation API 189. You see examples of how using large amounts of data can bring added value. You also learn how Giraph fits among the myriad of tools you can use to analyze large datasets.


Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer. Abstract— Reinforcement learning (RL) can automate a wide variety of robotic skills, but learning each new skill requires considerable real-world data collection and manual representa-tion engineering to design...


Modular meta-learning
Modular meta-learning. Ferran Alet, Toma´s Lozano-Pe´rez, Leslie P. Kaelbling MIT Computer Science Modular approaches to learning have been very successful in structured tasks such as It has a xed rst layer with 128 output units to compress the input, which is the same for all structures...


Recursive Sketches for Modular Deep Learning
5. Learning Modular Deep Networks via Dictionary Learning. maximum between the number of modules and the number of objects in any communication graph, S as the number of samples necessary to learn a module, and H as three times the depth of our modular network.


Modular forms and the four squares theorem. Modular forms are naturally viewed in several dierent contexts: as holomorphic functions satisfying transformation equations, as sections of line bundles on Rie-mann surfaces, and as We can also translate H to the unit disk by a linear.


1987-Modular Learning in Neural Networks
Computer simulations of learning using internal units have been restricted to small-scale systems. Thus we were motivated to develop a modular reformulation of Rackpropagation learning with better convergence properties.