Microsoft Research

Data Interesting

Sequential Decision Analytics Lecture with Warren Powell

Microsoft Research  recently had Warren Powell speak on Sequential Decision Analytics: A unified framework Warren Powell is Professor Emeritus at Princeton University and Chief Analytics Officer of Optimal Dynamics. He’s also Founder and Director of Castle Labs at Princeton which manages over 70 grants and contracts with government agencies and leading companies working to develop […]

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AI Research

Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization

Microsoft Research shares this amazing talk on  the optimization of many deep learning hyperparameters can be formulated as a bilevel optimization problem. While most black-box and gradient-based approaches require many independent training runs, we aim to adapt hyperparameters online as the network trains. The main challenge is to approximate the response Jacobian, which captures how […]

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Hardware Interesting

Ultra-Dense Data Storage and Extreme Parallelism with Electronic-Molecular Systems

Sustaining growth in storage and computational needs is increasingly challenging thanks to those pesky laws of physics. For over a decade, exponentially more information has been produced year after year while data storage solutions are pressed to keep up. Soon, current solutions will be unable to match new information in need of storage. Computing is […]

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Natural Language Processing

Domain-specific Language Model Pretraining for Biomedical Natural Language Processing

Microsoft Research presents this talk on pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks.  However, most pretraining efforts focus on general-domain corpora, such as in newswire and web text. Biomedical text is very different from general-domain text, yet biomedical NLP has been relatively […]

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Virtual Reality

Enhancing mobile work and productivity with virtual reality

As people work from home, new opportunities and challenges arise around mobile office work. On one hand, people may have flexible work hours and may not need to deal with traffic or long commutes. On the other hand, they may need to work at makeshift spaces, with less-than-optimal working conditions while physically separated from co-workers. […]

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AI Ethics

Responsible AI: Bringing Principles to Practice

As AI is becoming part of user-facing applications and is directly impacting society, deploying AI reliably and responsibly has become a priority for Microsoft and several other industry leaders. In recent years, Microsoft has developed a set of AI principles and standards alongside a company-wide ecosystem to guide responsible AI development and deployment. In this webinar, Microsoft […]

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Reinforcement Learning

A Beginner’s Guide to Reinforcement Learning

Reinforcement learning is one of the most exciting collections of techniques for building self-learning systems. Over the past five years, we’ve seen RL successfully meet such challenges as exceeding human performance on popular video games and board games. Despite the excitement around the success of these RL agents, it has remained extraordinarily difficult for most […]

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AI

AI and Gaming Research Summit 2021 – Understanding Players (Day 2 Track 1.2)

Here’s an interesting talk from the Microsoft Research AI and Gaming Research Summit 2021 on matching up players for online play.

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AI Research

Directions in ML: Taking Advantage of Randomness in Expensive Optimization Problems

Optimization is at the heart of machine learning, and gradient computation is central to many optimization techniques. Stochastic optimization, in particular, has taken center stage as the principal method of fitting many models, from deep neural networks to variational Bayesian posterior approximations. Generally, one uses data subsampling to efficiently construct unbiased gradient estimators for stochastic […]

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Machine Learning Research

Automating ML Performance Metric Selection

Microsoft Research hosts this talk on Automating ML Performance Metric Selection From music recommendations to high-stakes medical treatment selection, complex decision-making tasks are increasingly automated as classification problems. Thus, there is a growing need for classifiers that accurately reflect complex decision-making goals. One often formalizes these learning goals via a performance metric, which, in turn, […]

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