Semanlink - Yoshua Bengio AND Machine learning

Machine learning for combinatorial optimization: A methodological tour d’horizon

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2022-12-09 About

Deep Learning for AI | July 2021 | Communications of the ACM

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2021-08-02 About

[2102.11107] Towards Causal Representation Learning

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2021-07-15 About

Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation | Frontiers in Computational Neuroscience

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2021-03-19 About

[1807.00082] Amanuensis: The Programmer's Apprentice

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**The use of natural language to facilitate communication
between the expert programmer and apprentice AI system.**

> an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon **insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems** that leverage and extend the state of the art in machine learning **by integrating human and machine intelligence**. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants.

> [#Dehaene](/tag/stanislas_dehaene)'s work extends the [#Global Workspace Theory](/tag/global_workspace_theory) of Bernard Baars. Dehaene’s version of the theory combined with Yoshua Bengio’s concept of a [#consciousness prior](/tag/consciousness_prior.html) and deep reinforcement learning suggest a model for constructing and maintaining the cognitive states that arise and persist during complex problem solving.

2019-11-12 About

Feature-wise transformations. A simple and surprisingly effective family of conditioning mechanisms. (2018)

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2019-10-07 About

Learning Structured Embeddings of Knowledge Bases (2011)

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2019-08-03 About

[1907.03950] Learning by Abstraction: The Neural State Machine

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