Katja Hofmann

Researcher at Microsoft Research Cambridge, UK

About

Future interactive systems will learn directly from their users, and continuously adapt to their preferences. My research goal is to develop exploration, reward, and learning approaches that will make this possible. [...]

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Katja Hofmann

Intelligent Systems Lab Amsterdam
Informatics Institute
University of Amsterdam

Room C3.258
Science Park 904
1098 XH Amsterdam

+31 (20) 525 6767

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Recent Posts

Query Formulation with Query Auto-Completion
RUSSIR 2014: Lectures on Online Experimentation for Information Retrieval
Fast and Reliably Online Learning to Rank for Information Retrieval
Practical Online Retrieval Evaluation
Balancing Exploration and Exploitation in Online Learning to Rank for IR

Recent Tweets

RT @rbanks: We're looking for a great social science researcher who wants to join us in Cambridge for an internship! Help us understand how… 18 hours ago
RT @MSFTResearch: Congratulations to the 2020 Ada Lovelace and PhD Fellowship recipients! Their work, ranging from applications in mental h… 1 day ago
RT @haldaume3: Reminders of @icmlconf #icml2020 deadlines: Papers: abstracts due 30 Jan, papers due 6 Feb Workshops: due 14 Feb Tutorials:… 1 day ago

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Microsoft Research News

2020 Ada Lovelace and PhD Fellowships help recipients achieve broad research and educational goals
In their second and thirteenth years respectively, the Ada Lovelace Fellowship and PhD Fellowship continue a Microsoft Research tradition of providing promising doctoral students in North America with funding to support their studies and research. This year, there were over 600 submissions between both fellowships. Microsoft Research is proud to announce the […]
Transparency and Intelligibility Throughout the Machine Learning Life Cycle Webinar
Jan. 22, 2020 – In this webinar led by Microsoft researcher Jenn Wortman Vaughan, explore how to best incorporate transparency into the machine learning life cycle. Here, we will explore these three components of transparency (with examples): traceability, communication, and intelligibility. The post Transparency and Intelligibility Throughout the Machine Le […]
Project Rocket platform—designed for easy, customizable live video analytics—is open source
Thanks to advances in computer vision and deep neural networks (DNNs) in what can arguably be described as the golden age of vision, AI, and machine learning, video analytics systems—systems performing analytics on live camera streams—are becoming more accurate. This accuracy offers opportunities to support individuals and society in exciting ways, like info […]

Recent MSR Publications

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