Videos

Optimal Design for Social Learning

Optimal Design for Social Learning

1 year ago
We study the design of a recommender system for organizing social learning on a product. The optimal design trades off fully transparent social learning to improve incentives for early experimentation, by selectively over-recommending a product in the early phase of the product release. Under the optimal scheme, experimentation occurs faster than under full transparency but […]
Introduction to Machine Learning in Python with Scikit-Learn

Introduction to Machine Learning in Python with Scikit-Learn

1 year ago
This talk will introduce scikit-learn, an Open Source project for Machine Learning in Python and review some new features from the recent 0.15 release: faster randomized ensemble of decision trees and optimization for the memory usage when working on multiple cores. Finally we will demo the typical usage of scikit-learn for interactive predictive analytics in […]
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction

Local Deep Kernel Learning for Efficient Non-linear SVM Prediction

1 year ago
The time taken by an algorithm to make predictions is of critical importance as machine learning transitions to becoming a service available on the cloud. Algorithms that are efficient at prediction can service more calls and utilize fewer cloud resources and thereby generate more revenue. They can also be used in real time applications where […]
F# Type Providers: DBpedia and the Combinator Framework

F# Type Providers: DBpedia and the Combinator Framework

1 year ago
Wikipedia has become a knowledge repository for virtually every topic in existence, but its pages are intended to be read by humans, not computers. The DBpedia organisation has extracted much of this knowledge into an RDF-based entity graph format, and we introduce and demonstrate a type provider that brings this knowledge into the F# language […]
Vowpal Wabbit Future Plans

Vowpal Wabbit Future Plans

1 year ago
The goal of this workshop is to inform people about open source machine learning systems being developed, aid the coordination of such projects, and discuss future plans.
Enabling more Girls in Computing: Office Mix CS Toolkit for middle school and CS Principles Gaming C

Enabling more Girls in Computing: Office Mix CS Toolkit for middle school and CS Principles Gaming C

1 year ago
Approximately 16 million students are attending high school in the U.S., 1/5 of them will become graduating seniors. This means that 3.2 million new students have the opportunity to become computer science majors. Unfortunately, just 3%, a tiny fraction of a number will choose computer science. This 3% of students will have the composition of […]
Computer Vision – StAR Lecture Series: Object Recognition

Computer Vision – StAR Lecture Series: Object Recognition

1 year ago
The state-of-the-art in object recognition has undergone dramatic changes in the last 20 years. In this talk, I will review the progression of the field and discuss why various approaches both succeeded and failed. The talk will cover visual recognition from the early 90’s, including handwritten digit and face detection, to the current state-of-the-art in […]
Checking microarchitectural implementations of weak memory

Checking microarchitectural implementations of weak memory

1 year ago
In parallel programs, threads communicate according to the memory consistency model: the set of memory ordering rules enforced by a given architecture. A great deal of research effort has gone into rigorous formalization of memory models. However, comparatively little attention has been paid to the microarchitectural implementation of these models. Standard testing-based techniques are insufficient: […]
Blind Deconvolution Using Unconventional Beamforming

Blind Deconvolution Using Unconventional Beamforming

1 year ago
When an acoustic wave travels in a medium which encounters the boundary of a second medium, recorded signals by a receiver array (an array of microphones or hydrophones) is commonly distorted by reflected waves from the boundaries. Such recordings are the convolution of the source signal and the impulse response of environment at the time […]
Symmetry-Based Learning

Symmetry-Based Learning

1 year ago
Learning representations is arguably the central problem in machine learning, and symmetry group theory is a natural foundation for it. A symmetry of a classifier is a representation change that doesn’t change the examples’ classes. The goal of representation learning is to get rid of unimportant variations, making important ones easy to detect, and unimportant […]
Deep Learning for Text Processing

Deep Learning for Text Processing

1 year ago
Deep learning has enjoyed tremendous success in recent years in speech and visual object recognition, as well as in language processing (although to somewhat less extent). The focus of this session is on deep learning approaches to problems in language or text processing, with particular emphasis on important applications with vital significance to Microsoft. First, […]
Towards Scalable Quantum Computation

Towards Scalable Quantum Computation

1 year ago
Three decades have passed since Richard Feynman first proposed devising a “quantum computer” founded on the laws of quantum physics to achieve computational speed-ups over classical methods. In that time, quantum algorithms have been developed that offer fast solutions to problems in a variety of fields including number theory, chemistry, and materials science. To execute […]