International audienceMany fields are now snowed under with an avalanche of data, which raises considerable challenges for computer scientists. Meanwhile, robotics (among other fields) can often only use a few dozen data points because acquiring them involves a process that is expensive or time-consuming. How can an algorithm learn with only a few data points
Data is driving the future of computation: analysis, visualization, and learning algorithms power sy...
[[abstract]]Many studies about learning in limited data were made in recent years. Without double, s...
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...
International audienceMany fields are now snowed under with an avalanche of data, which raises consi...
Over the past decade, deep learning has pro- foundly transformed the landscape of science and tech-...
While robotics has made tremendous progress over the last few decades, most success stories are stil...
The availability of large labelled datasets has played a crucial role in the recent success of deep ...
Being able to learn from small amounts of data is a key characteristic of human intelligence, but ex...
International audienceMost policy search algorithms require thousands of training episodes to find a...
iii The volume of data that humans create has increased explosively as information science and techn...
The Problem: Learning from data with both labeled training points (x,y pairs) and unlabeled training...
Machine learning is widely regarded as a tool for overcoming the bottleneck in knowledge acquisition...
Data science has gained importance since available data and hardware facilities have been ubiquitous...
Technology drives advances in science. Giving scientists access to more powerful tools for collectin...
Abstract:- Many studies about learning in limited data were made in recent years. Without double, sm...
Data is driving the future of computation: analysis, visualization, and learning algorithms power sy...
[[abstract]]Many studies about learning in limited data were made in recent years. Without double, s...
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...
International audienceMany fields are now snowed under with an avalanche of data, which raises consi...
Over the past decade, deep learning has pro- foundly transformed the landscape of science and tech-...
While robotics has made tremendous progress over the last few decades, most success stories are stil...
The availability of large labelled datasets has played a crucial role in the recent success of deep ...
Being able to learn from small amounts of data is a key characteristic of human intelligence, but ex...
International audienceMost policy search algorithms require thousands of training episodes to find a...
iii The volume of data that humans create has increased explosively as information science and techn...
The Problem: Learning from data with both labeled training points (x,y pairs) and unlabeled training...
Machine learning is widely regarded as a tool for overcoming the bottleneck in knowledge acquisition...
Data science has gained importance since available data and hardware facilities have been ubiquitous...
Technology drives advances in science. Giving scientists access to more powerful tools for collectin...
Abstract:- Many studies about learning in limited data were made in recent years. Without double, sm...
Data is driving the future of computation: analysis, visualization, and learning algorithms power sy...
[[abstract]]Many studies about learning in limited data were made in recent years. Without double, s...
Machine learning is a model that learns patterns in data and then calculates similar patterns in new...