We’ve shown that deep linear networks — as implemented using floating-point arithmetic — are not actually linear and can perform nonlinear computation. We used evolution strategies to find parameters in linear networks that exploit this trait, letting us solve non-trivial problems.
Neural networks consist of stacks of a linear layer followed by
We’ve shown that deep linear networks — as implemented using floating-point arithmetic — are not actually linear and can perform nonlinear computation. We used evolution strategies to find parameters in linear networks that exploit this trait, letting us solve non-trivial problems.
Neural networks consist of stacks of a linear layer followed by
Shape-shifting device from CSAIL can walk, roll, sail, and glide using recyclable exoskeletons.
As per professor Andrew machine learning is a revolution in history of man kind first one was where machines came and took our basic jobs to make us faster and our life easy. Now to me this second one is coming to make us lazy and heavily dependent. T…
Computer vision and machine learning expert Antonio Torralba to lead new artificial intelligence research lab.
Blockchain to transform financial services. Disruptive technologies transform traditional industries. The future computing will have extraordinary capabilities with expected factoring of a 3,000 digit number (40 power to 10) faster than today
New venture launched by MIT will support “tough-tech” companies at work on transformative ideas that take time to commercialize.
New research describes a price-optimization method to increase online retailers’ revenue, market share, and profit.
We’re releasing an algorithm which accounts for the fact that other agents are learning too, and discovers self-interested yet collaborative strategies like tit-for-tat in the iterated prisoner’s dilemma. This algorithm, Learning with Opponent-Learning Awareness (LOLA), is a small step towards agents that model other minds.
LOLA, a collaboration
We’re releasing an algorithm which accounts for the fact that other agents are learning too, and discovers self-interested yet collaborative strategies like tit-for-tat in the iterated prisoner’s dilemma. This algorithm, Learning with Opponent-Learning Awareness (LOLA), is a small step towards agents that model other minds.
LOLA, a collaboration
