Differential Privacy for Growing Databases
We study the design of differentially private algorithms for adaptive analysis of dynamically growing databases, where a database accumulates new data entries while the analysis is ongoing. We provide a collection of tools for machine…
On momentum methods and acceleration in stochastic optimization
It is well known that momentum gradient methods (e.g., Polyak’s heavy ball, Nesterov’s acceleration) yield significant improvements over vanilla gradient descent in deterministic optimization (i.e., where we have access to exact gradient of the function…
Learning Models of Language, Action and Perception for Human-Robot Collaboration
Robots can act as a force multiplier for people, whether a robot assisting an astronaut with a repair on the International Space station, a UAV taking flight over our cities, or an autonomous vehicle driving…
Sounding the Future: Microsoft Research brings its best to ICASSP 2018 in Calgary
Introduction Speech technology has come a long way since Alexander Graham Bell’s famous Mr. Watson – Come here – I want to see you became the first speech to be heard over the telephone in…
Rethinking Distributed State Management in Networks
A key challenge in scaling network control and data planes is to maintain access to shared state without comprimising performance. In this talk, I present Tasvir, a versioned distributed shared memory system, that achieves this…
PNW PLSE Workshop: Project Everest: Theory meets Reality
The PNW PLSE workshop provides an opportunity for programming languages and software engineering researchers throughout the Pacific Northwest to meet, interact, and share work in progress as well as recent results. The meeting on May…
Connecting Vision and Language via Interpretation, Grounding and Imagination
Understanding how to model vision and language jointly is a long-standing challenge in artificial intelligence. Vision is one of the primary sensors we use to perceive the world, while language is our data structure to…
Collaborative Research: From Algorithms to Application Impact at Pacific Northwest National Lab (PNNL)
As a Department of Energy lab, computer science research at Pacific Northwest National Lab (PNNL) is closely tied to or motivated by the needs of scientific applications. In this talk, I will present a brief…
On Intrinsic Rewards and Continual Learning
Continual learning is the problem faced by intelligent agents of the sort that people and other animals are, that of learning increasingly complex skills and knowledge over time from experience, of becoming increasingly competent over…